- \n
- Nominations, from the university or Microsoft nominators, closed February 22, 2021<\/li>\n\n\n\n
- Qualified nominees were sent an invitation email on March 1, 2021 to submit their proposal<\/li>\n\n\n\n
- Proposals and reference letters were accepted through March 29, 2021<\/li>\n\n\n\n
- Finalists notified in early May and interviewed virtually May 17-18, 2021<\/strong><\/li>\n\n\n\n
- Recipients announced by early July 2021<\/li>\n<\/ul>\n\n\n\n
Eligibility criteria<\/h2>\n\n\n\n
How to submit a proposal<\/h3>\n\n\n\n
Candidates must be nominated by their university or a Microsoft nominator before receiving an invitation to submit a proposal.<\/p>\n\n\n\n
Nominators<\/h3>\n\n\n\n
- \n
- Microsoft\u2019s mission is to empower every person and every organization on the planet to achieve more. Fellows should support this mission by fostering diverse and inclusive cultures within their communities.<\/li>\n\n\n\n
- Faculty must be nominated by their university or a Microsoft Research lab member or a researcher within an applied research group in other parts of Microsoft.<\/li>\n\n\n\n
- A maximum of three nominations per university will be accepted; if more than one is nominated, then the other one or two nominees should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.<\/li>\n\n\n\n
- Microsoft Research lab members and researchers within an applied research group in other parts of Microsoft may nominate a maximum of two faculty. If more than one faculty is nominated, then at least one nominee should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.<\/li>\n\n\n\n
- Nominators must agree to write and submit a one-page recommendation letter in support of their nominee, if requested by the nominee.<\/li>\n<\/ul>\n\n\n\n
Nominees<\/h3>\n\n\n\n
- \n
- Full-time faculty at a degree-granting college or university in North America or South America.<\/li>\n\n\n\n
- Faculty must have received their terminal degree (e.g., PhD, DSc) in May 2016 or later. We will take into account approved delays, like leaves of absences from the workplace and postdocs, on a case by case basis if you contact us at msfellow@microsoft.com<\/a>.<\/li>\n\n\n\n
- Currently conducting research, advising graduate students, and teaching in a classroom.<\/li>\n\n\n\n
- Proposed research must be closely related to the general research areas carried out by Microsoft as noted in the Our research<\/em> tab above.<\/li>\n<\/ul>\n\n\n\n
Recipients<\/h2>\n\n\n\n
- \n
- If awarded, the recipient must remain an active, full-time faculty during the two consecutive academic years of the award or forfeit the award. Fellowships are not available for extension. If you require time away for family or medical leave, this will be accommodated. If you are unsure if a particular need for time away will affect the award, you can contact us at Microsoft Research Fellowships (msfellow@microsoft.com<\/a>).<\/li>\n\n\n\n
- Payment of the award, as described above, will be made directly to the university and dispersed according to the university\u2019s policies. Microsoft will have discretion as to how any remaining funds will be used if the faculty is no longer qualified to receive funding.<\/li>\n\n\n\n
- A recipient of the Microsoft Research Faculty Fellowship subject to disciplinary proceedings for inappropriate behavior, including but not limited to discrimination, harassment (including sexual harassment), or plagiarism will forfeit their funding.<\/li>\n<\/ul>\n\n\n\n
If you do not meet the above criteria, you may be eligible for other Academic Programs<\/a>.<\/p>\n\n\n\n
Microsoft actively seeks to foster greater levels of diversity in our workforce and in our pipeline of future researchers. We are always looking for the best and brightest talent and celebrate individuality. We invite candidates to come as they are and do what they love.<\/p>\n\n\n\n
Contact us<\/h2>\n\n\n\n
Direct any questions not answered in the FAQ<\/a> to the Fellowship\u2019s Program Chair, John Krumm<\/a>, or the Program Manager at msfellow@microsoft.com<\/a>.<\/p>\n\n\n\n\n\n
How to submit a nomination<\/h2>\n\n\n\n
Nominations for the 2021 Microsoft Research Faculty Fellowship closed on Monday, February 22, 2021 at 12:00 PM (Noon) Pacific Time. Universities and Microsoft nominators should inform faculty nominees once they have submitted their nomination so the nominees can begin collecting the details on the Proposal tab<\/a>. Nominated faculty will receive an invitation email in early March 2021 to submit their proposal.<\/p>\n\n\n\n
A maximum of three nominations per university will be accepted; if more than one is nominated, then the other one or two nominees should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.<\/p>\n\n\n\n
Microsoft Research lab members and researchers within an applied research group in other parts of Microsoft may nominate a maximum of two faculty. If more than one faculty is nominated, then at least one nominee should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.<\/p>\n\n\n\n
Nominations must include:<\/p>\n\n\n\n
- \n
- Your name, email, and job title as the person submitting the nomination on behalf of your university or as a Microsoft nominator<\/li>\n\n\n\n
- For university nominations, a brief description (a few sentences) of your university\u2019s process for determining which faculty to nominate for this fellowship<\/li>\n\n\n\n
- For university nominations, attestation that the process used to determine which faculty to nominate from your university for this fellowship was fair and non-discriminatory<\/li>\n\n\n\n
- Nominee\u2019s name, email, country, university, and department<\/li>\n\n\n\n
- Nominee\u2019s primary and secondary areas of research (click on the Our research<\/em> tab at the top of the page for a full list)<\/li>\n\n\n\n
- Attestation that the nominee received their terminal degree (e.g. PhD, DSc) in May 2016 or later (having taken into account approved delays)<\/li>\n\n\n\n
- Attestation that the nominee is a full-time faculty at a degree-granting college or university, conducting research, advising graduate students, and teaching in a classroom<\/li>\n\n\n\n
- Attestation that the nominee you are putting forth is either someone who self-identifies as underrepresented in the field of computing (as detailed above) or not<\/li>\n<\/ul>\n\n\n\n\n\n
How to submit a proposal<\/h2>\n\n\n\n
If you were nominated by your university or a Microsoft nominator, then you should have received an email from Microsoft Research Faculty Fellowship on March 1, 2021, which includes a private link to submit your proposal. Please check your junk email folder if you do not see it in your inbox.<\/p>\n\n\n\n
If you are a nominee, the below outlines the information necessary to submit your proposal in our submission portal.<\/p>\n\n\n\n
You will be asked to answer the below questions in a form:<\/p>\n\n\n\n
- \n
- Name, email, job title, country, university, and department<\/li>\n\n\n\n
- Primary and secondary areas of research (click on the Our research<\/em> tab at the top of the page for a full list)<\/li>\n\n\n\n
- Month and year you received your terminal degree (e.g. PhD, DSc)<\/li>\n\n\n\n
- Month and year you started your career as a professor<\/li>\n\n\n\n
- URL to your professional website (optional, but strongly recommended; you are encouraged to make certain it is up-to-date)<\/li>\n\n\n\n
- List up to 5 of the top awards received for best paper or long-term impact paper, if applicable (include award name like \u201cbest paper\u201d, authors, titles, conferences, and years)<\/li>\n\n\n\n
- List up to 5 of the top awards received for teaching or mentoring, if applicable<\/li>\n\n\n\n
- List up to 5 other top awards received not already listed above, if applicable<\/li>\n\n\n\n
- List up to 5 top ranks held in a professional society, if applicable (e.g. \u201cSenior member ACM\u201d)<\/li>\n\n\n\n
- List up to 5 research grants received, if applicable (include titles of the projects, years received, amounts, and other principle investigators)<\/li>\n\n\n\n
- Attestation that you received your terminal degree (e.g. PhD, DSc) in May 2016 or later (having taken into account approved delays)<\/li>\n\n\n\n
- Attestation that you are a full-time faculty at a degree-granting college or university, conducting research, advising graduate students, and teaching in a classroom<\/li>\n\n\n\n
- Attestation as to whether or not you are a faculty who is underrepresented in the field of computing which include those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability \u2013 if more than one faculty is nominated, then the other one or two should help us increase the opportunities for faculty who are underrepresented in the field of computing<\/li>\n\n\n\n
- Self-assessment of the Statement of Good Standing: \u201cI declare I have never been disciplined for inappropriate behavior, including, but not limited to discrimination, harassment (including sexual harassment), or plagiarism. If I am selected to receive funding under Microsoft\u2019s Fellowship program, during my funding time period, I agree to inform Microsoft should I be subjected to disciplinary proceedings for inappropriate behavior, including but not limited to discrimination, harassment (including sexual harassment), or plagiarism which would result in forfeiture of funding under Microsoft\u2019s Fellowship program<\/em>.\u201d<\/li>\n<\/ul>\n\n\n\n
You will be asked to upload 2 documents:<\/p>\n\n\n\n
Your curriculum vitae and two-page statement of research will be uploaded separately. Accepted formats are docx, doc, and pdf. Email or hard-copy submissions will not be considered. Name the individual files using the convention indicated below. Include your first name and last name as part of your file name each separated by an underscore (e.g. Jane_Smith_cv.docx).<\/p>\n\n\n\n
- \n
- Curriculum vitae \u2013 file name: cv<\/strong><\/li>\n\n\n\n
- Two-page statement of research to include: your major research initiatives, what makes your approaches especially innovative, and how you would use the funding and the impact it would have on your research; a paragraph describing how you support the mission of fostering diversity and inclusive cultures within your student and researcher communities and how you plan to in the future; we suggest a font no smaller than 10-point and references should be included as part of the two pages \u2013 file name: research<\/strong><\/li>\n<\/ul>\n\n\n\n
You will be asked to request 3 letters of recommendation via the submission portal:<\/p>\n\n\n\n
- \n
- Add the contact information (name, affiliation, email) and send the email request through the submission portal to your three recommenders as soon as possible so they have ample time to provide a letter. Their deadline is the same as your proposal deadline on Monday, March 29, 2021<\/strong>. They should be established researchers familiar with your research. Once you send the request through the submission portal, they will receive a private link to upload a letter of recommendation for you. Please note that you and your recommenders may need to check your junk folders in order to find emails from our portal. As reference, here is a list of the various system email addresses (opens in new tab)<\/span><\/a> you can add to allowed emails.<\/li>\n<\/ul>\n\n\n\n
Proposals submitted to Microsoft will not be returned. Microsoft cannot assume responsibility for the confidentiality of information in submitted proposals. Therefore, proposals should not contain information that is confidential, restricted, or sensitive. Microsoft reserves the right to make public the information on those proposals that receive awards, except those portions containing budgetary or personally identifiable information.<\/p>\n\n\n\n
Incomplete proposals will not be considered.<\/p>\n\n\n\n
Due to the volume of submissions, Microsoft cannot provide individual feedback on proposals.<\/p>\n\n\n\n\n\n
Below are the answers to frequently asked questions about the 2021 Microsoft Research Faculty Fellowship.<\/p>\n\n\n\n
Eligibility criteria<\/h3>\n\n\n\n\n\n
The Microsoft Research Faculty Fellowship includes only schools from the Americas. If you are a faculty at a school outside North America or South America, you are not eligible for this fellowship.<\/p>\n\n\n\n\n\n
To be considered for the award, you must be nominated by your university or a Microsoft Research lab member or a researcher within an applied research group in other parts of Microsoft. If you are nominated, you will be contacted to submit a proposal.<\/p>\n\n\n\n\n\n
Employees and directors of Microsoft Corporation, and its subsidiaries and affiliates are not eligible, nor are persons involved in the execution or administration of this fellowship, or the family members of each above (parents, children, siblings, spouse\/domestic partners, or individuals residing in the same household).<\/p>\n\n\n\n\n\n
\n\n\n\nNominations<\/h3>\n\n\n\n\n\n
No, universities do not need to coordinate with Microsoft nominators. It is acceptable to nominate the same faculty.<\/p>\n\n\n\n\n\n
Yes, the Microsoft limit is independent of the university limit.<\/p>\n\n\n\n\n\n
The university can designate any staff other than the nominee to submit the nomination. The nomination simply needs to be a coordinated effort to ensure there are no more than three submissions from each university.<\/p>\n\n\n\n\n\n
No, we do not require a letter from the university.<\/p>\n\n\n\n\n\n
Not from our perspective.<\/p>\n\n\n\n\n\n
\n\n\n\nResearch areas<\/h3>\n\n\n\n\n\n
- \n
- Your choices of primary and secondary areas help us choose who reviews your proposal.<\/li>\n\n\n\n
- Pick areas that align with conferences\/journals where you would publish.<\/li>\n\n\n\n
- The statement of research is the appropriate place to describe how research areas relate to your research.<\/li>\n<\/ul>\n\n\n\n\n\n
Microsoft Research is interdisciplinary, so it is something we understand. What you choose as a research area is a \u201csoft\u201d preference and will simply help us better route your proposal. Utilize the primary and secondary research area option to help capture and communicate your research area the best you can.<\/p>\n\n\n\n
Here are some suggestions and guiding questions to help you choose a research area:<\/p>\n\n\n\n
- \n
- Do you have a home conference? Are there one or two conferences you go to in a more specific area?<\/li>\n\n\n\n
- Who do you want to be reading your proposal?<\/li>\n\n\n\n
- Who would you want to network with? What area of research are they in?<\/li>\n\n\n\n
- Who would be most excited about my topic? What area of research are they in?<\/li>\n<\/ul>\n\n\n\n\n\n
Your work should be of interest to Microsoft Research lab members or researchers within an applied research group in other parts of Microsoft; however, it doesn\u2019t need to directly line up with an existing project or topic. It is important for your work to be related enough that Microsoft Research will be able to review it and have interest in supporting it. Microsoft Research is large, interdisciplinary, and covers a broad area \u2014 use the Our research<\/em> tab above as a guideline for the areas we cover. When in doubt, we suggest you browse the webpages of Microsoft Research lab members and researchers within an applied research group in other parts of Microsoft who look like they may be related to your area and see if they have papers in the similar topics or publish in conferences you publish in and\/or attend. If you find one or more such people that share these connections with you, then you can feel confident that your work is related enough to submit a proposal.<\/p>\n\n\n\n\n\n
\n\n\n\nLetters of recommendation<\/h3>\n\n\n\n\n\n
Given you need three letters, it would be good to include a letter from one person who can speak about your current research and one person who has known you longer, even if it may not be in your current research area. The longer-term perspective is definitely important and valuable. The value of a letter is evaluating how you work, how you collaborate with people, and what your process is as a researcher. This transcends what your particular topic is. Keep in mind that one letter doesn\u2019t have to address all things; across all three letters, we want to get a full picture of who you are over a longer term, but also insight into your recent work.<\/p>\n\n\n\n\n\n
The purpose of a letter of recommendation is to provide us with the bigger picture of what you are doing, how you work as a researcher, how you learn, how you approach projects, and how you collaborate with others. The letter will also provide us with insight from people who have been working with you and observing you for some amount of time.<\/p>\n\n\n\n\n\n
Those you provided as recommenders in our system will be sent an auto-generated email with instructions to upload their letters of recommendation.<\/p>\n\n\n\n\n\n
\n\n\n\nReview process<\/h3>\n\n\n\n\n\n
Proposals will be reviewed by Microsoft Research lab members and researchers within an applied research group in other parts of Microsoft whose expertise covers a wide range of disciplines. After the first review, a selection of faculty will be invited to interview. Award recipients are chosen from those finalists.<\/p>\n\n\n\n\n\n
We look at how cutting edge your research is as well as the significance and impact of the research. We carefully read through your two-page statement of research, three letters of recommendation, and your CV to try to gauge this. Best paper and other top awards are not required, but are helpful signals. The two-page statement of research should include your major research initiatives, what makes your approaches especially innovative, and how you would use the funding and the impact it would have on your research.<\/p>\n\n\n\n\n\n
Finalists will be contacted in early May about the virtual interview. Due to the volume of submissions, Microsoft cannot provide individual feedback on proposals.<\/p>\n\n\n\n\n\n
There were nearly 200 nominations submitted last year.<\/p>\n\n\n\n\n\n
\n\n\n\nAward details<\/h3>\n\n\n\n\n\n
Persons awarded a fellowship in June will receive their financial awards by September of that year. Microsoft sends payment directly to the university, who will disperse funds according to their guidelines. This award will be provided as an unrestricted gift with no terms and restrictions applied to it. No portion of these funds should be applied to overhead or other indirect costs.<\/p>\n\n\n\n\n\n
The tax implications for your award are based on the policy at your university and applicable tax laws.<\/p>\n\n\n\n\n\n
The Microsoft Research Faculty Fellowship is not subject to any intellectual property (IP) restrictions.<\/p>\n\n\n\n\n\n
Absolutely! There is no limit to the amount of your award that can be used for childcare.<\/p>\n\n\n\n\n\n\n\n
Microsoft Research Faculty Fellows<\/h2>\n
2021 Faculty Fellows<\/h3>\n
![\"2021](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2021\/01\/Baris-Kasikci_150x208.jpg\")
Baris Kasikci (opens in new tab)<\/span><\/a><\/h3>\nAssistant Professor<\/p>\n
University of Michigan<\/p>\n
Baris Kasikci is an assistant professor of Electrical Engineering and Computer Science at the University of Michigan. His group builds efficient and trustworthy computer systems that improve the efficiency of data center applications, provide systems support for heterogeneous platforms, find and fix bugs, and improve hardware security. Previously, Baris was a researcher in the Systems and Networking Group at Microsoft Research Cambridge. He completed his PhD in Computer Science at EPFL and held roles at Intel, VMware, and Siemens. He is the recipient of an NSF CAREER award, Intel Rising Star Award, Google Faculty Award, VMware Early Career Grant, Jay Lepreau Best Paper Award at OSDI\u201918, IEEE MICRO Top Picks Award, VMware fellowship, Roger Needham Ph.D. Award for the best PhD thesis in computer systems in Europe, and the Patrick Denantes Memorial Prize for best PhD thesis in Computer Science at EPFL.<\/p>\n
\n![\"2021](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2021\/01\/Boyla-Mainsah_150x208.jpg\")
Boyla Mainsah (opens in new tab)<\/span><\/a><\/h3>\nAssistant Research Professor<\/p>\n
Duke University<\/p>\n
Boyla Mainsah is an Assistant Research Professor of Electrical and Computer Engineering (ECE) at Duke University. She received her PhD and master\u2019s degrees in Electrical and Computer Engineering at Duke University. Her research interests are in biomedical applications of signal processing and machine learning\/deep learning, with a focus on developing solutions for enhancing neuroprosthetics and for the discovery of novel biomarkers for diagnosis and prognosis. Her recent work includes leveraging information theory and active learning to improve the efficiency of brain-computer interfaces, leveraging natural language processing for speech enhancement in cochlear implants, and acoustic surveillance in individuals with left ventricular assist devices. Her work has received several recognitions, including the Duke ECE Outstanding PhD Dissertation Award, and best paper commendations from the Journal of Neural Engineering and the International Medical Informatics Association Yearbook. She is the recipient of an NIDCD Early Career Research Award.<\/p>\n
\n![\"2021](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2021\/01\/Shuran-Song_150x208.jpg\")
Shuran Song (opens in new tab)<\/span><\/a><\/h3>\nAssistant Professor<\/p>\n
Columbia University<\/p>\n
Shuran Song is an assistant professor in the Department of Computer Science at Columbia University. Before that, she received her PhD in Computer Science at Princeton University. Her research interests lie at the intersection of computer vision and robotics. She is a recipient of several awards including the Best Paper Award at T-RO \u201820, Best Systems Paper Award at RSS \u201819, Best Manipulation Systems Paper Award from Amazon \u201818, and has been finalist for Best Paper Awards at conferences ICRA \u201820, CVPR\u201919, RSS \u201819, IROS \u201818.<\/p>\n
\n![\"2021](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2021\/01\/David-Wu_150x208.jpg\")
David Wu (opens in new tab)<\/span><\/a><\/h3>\nAssistant Professor<\/p>\n
University of Texas at Austin<\/p>\n
David Wu is joining the Department of Computer Science at the University of Texas at Austin as an assistant professor in Fall 2021. Since 2019, he has been the Anita Jones Career Enhancement Assistant Professor in Computer Science at the University of Virginia. David\u2019s research interests are in applied and theoretical cryptography as well as computer security, with a particular focus on developing new cryptographic primitives and systems to enable privacy-preserving computations. His research has been recognized by two Best Young-Researcher Paper Awards at CRYPTO, an Outstanding Paper Award at ESORICS, and the NSF CAREER Award. David received his PhD in computer science from Stanford University in 2018.<\/p>\n
\n![\"2021](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2021\/01\/Diyi-Yang_150x208.jpg\")
Diyi Yang (opens in new tab)<\/span><\/a><\/h3>\nAssistant Professor<\/p>\n
Georgia Institute of Technology<\/p>\n
Diyi Yang is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology, where she leads the Social and Language Technologies (SALT) Lab. Her primary research interests span across fields in natural language processing, machine learning, and computational social science. Her research focuses on understanding the social aspects of language and building responsible NLP systems with social intelligence. Dr. Yang received her PhD from the Language Technologies Institute at Carnegie Mellon University, and her bachelor\u2019s degree from Shanghai Jiao Tong University in China. Her work has received multiple best paper awards and nominations at top human computer interaction and natural language processing conferences. Dr. Yang has won prestigious awards and recognitions such as Forbes 30 under 30 in Science and IEEE AI 10 to Watch, and has received several faculty research awards from Amazon, Facebook and Salesforce.<\/p>\n
\n\n\n \t2020 Faculty Fellows <\/h4>\n
\n\n
2020 Faculty Fellows<\/h3>\n
![\"2020](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/11\/FacFellow2020_Loris-DAntoni_150x208.jpg\")
Loris D\u2019Antoni<\/h3>\nAssistant Professor, Department of Computer Sciences<\/p>\n
University of Wisconsin-Madison<\/p>\n
Loris D\u2019Antoni is an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin-Madison. There, he\u2019s affiliated with the madPL (Madison Programming Languages) Group. He received his bachelor\u2019s and master\u2019s degrees in Computer Science from the University of Torino in 2008 and 2010, respectively, and his PhD in Computer Science from the University of Pennsylvania in 2015. His research is centered on building fundamental verification and synthesis techniques that help programmers write software that meets their intent. In particular, his current main focus is on building practical and predictable program synthesis techniques that can be applied to computer networks, program repair, and machine learning. He has won several awards, including the NSF CAREER Award, Google Research Award, Morris and Dorothy Rubinoff Dissertation Award, and his papers were selected for special journal issues (TOPLAS (opens in new tab)<\/span><\/a>, FMSD (opens in new tab)<\/span><\/a>) and nominated for best paper awards (TACAS (opens in new tab)<\/span><\/a>).<\/p>\n
\n![\"2020](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/11\/FacFellow2020_Christina-Delimitrou_150x208.jpg\")
Christina Delimitrou<\/h3>\nAssistant Professor, Electrical and Computer Engineering<\/p>\n
Cornell University<\/p>\n
Christina is an Assistant Professor and the John and Norma Balen Sesquicentennial Faculty Fellow at Cornell University, where she leads the Systems, Architecture, and Infrastructure Lab (SAIL). Her research interests are in the areas of cloud computing, computer architecture, and applied machine learning. Her recent work focuses on leveraging ML to improve the performance predictability, resource efficiency, and security of large-scale datacenters. Christina\u2019s work has garnered significant industry impact, with several of the systems she has built being deployed in production cloud providers. Christina is the recipient of a Sloan Research Fellowship, an NSF CAREER Award, two Google Faculty Research Awards, a Facebook Faculty Research Award, four IEEE Micro Top Picks, and several best paper awards. Christina received her PhD in Electrical Engineering from Stanford University. Prior to that, she had earned an MS in Electrical Engineering, also from Stanford, and a diploma in Electrical and Computer Engineering from the National Technical University of Athens.<\/p>\n
\n![\"2020](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/11\/FacFellow2020_Chelsea-Finn_150x208.jpg\")
Chelsea Finn<\/h3>\nAssistant Professor, Computer Science and Electrical Engineering Departments<\/p>\n
Stanford University<\/p>\n
Chelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the ability of robots to develop broadly intelligent behavior through learning and interaction. To this end, her work spans machine learning, robotics, and computer vision, including deep learning for end-to-end robotic perception and control, meta-learning algorithms that enable flexible adaptation to new tasks and environments, and methods for self-supervised robot learning at scale. Dr. Finn received her Bachelor\u2019s degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at University of California, Berkeley. Her research has been recognized through the ACM Doctoral Dissertation Award, an NSF graduate research fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 Innovators under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg.<\/p>\n
\n![\"2020](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/11\/FacFellow2020_Stefanie-Mueller_150x208.jpg\")
Stefanie Mueller<\/h3>\nX-Window Consortium Career Development Assistant Professor, Department of Electrical Engineering and Computer Science (MIT EECS), Computer Science and Artificial Intelligence Laboratory (MIT CSAIL)<\/p>\n
Massachusetts Institute of Technology<\/p>\n
Stefanie Mueller is the X-Career Development Assistant Professor in the MIT EECS department joint with MIT Mechanical Engineering and Head of the HCI Engineering Group at MIT CSAIL. In her research, she develops novel hardware and software systems that advance personal fabrication technologies. For her work, Stefanie has received multiple best paper awards at the most selective human-computer interaction venues (ACM CHI and ACM UIST), received an NSF CAREER award, and was named an Alfred P. Sloan Fellow as well as a Forbes 30 under 30 in Science. Over the last years, Stefanie has served as an ACM CHI Subcommittee Chair in 2019 and 2020 and is currently serving as the ACM UIST 2020 program chair. She has also been an invited speaker at more than 50 universities and research labs, such as MIT, Stanford University, Harvard University, University of California Berkeley, Carnegie Mellon University, and Microsoft Research.<\/p>\n
\n![\"2020](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/11\/FacFellow2020_Aaron-Sidford_150x208.jpg\")
Aaron Sidford<\/h3>\nAssistant Professor, Management Science and Engineering<\/p>\n
Stanford University<\/p>\n
Aaron Sidford is an Assistant Professor of Management Science and Engineering at Stanford University, where he also has a courtesy appointment in Computer Science and an affiliation with the Institute for Computational and Mathematical Engineering (ICME). Aaron\u2019s research interests lie in optimization, the theory of computation, and the design and analysis of algorithms, with an emphasis on work at the intersection of continuous optimization, graph theory, numerical linear algebra, and data structures. His work focuses on the design of provably efficient algorithm for solving fundamental and pervasive large-scale problems in optimization and data-analysis. He has received multiple awards for his work in these areas including a Sloan Research Fellowship, an NSF CAREER Award, an ACM Doctoral Dissertation Award honorable mention, best paper awards in FOCS (opens in new tab)<\/span><\/a> and SODA (opens in new tab)<\/span><\/a>, and two best student paper awards in FOCS.<\/p>\n
\n<\/div>\n\n \t2019 Faculty Fellows <\/h4>\n
\n\n
![\"2019](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/04\/2018_FacFellow_Mohammad-Alizadeh_150x208.jpg\")
Mohammad Alizadeh<\/h3>\nAssistant Professor, Electrical Engineering and Computer Science<\/p>\n
Massachusetts Institute of Technology<\/p>\n
Mohammad Alizadeh is the TIBCO Career Development Assistant Professor of Computer Science at MIT. His research interests are in the areas of networked computer systems and applied machine learning. His current research focuses on learning-augmented network systems, programmable networks, and network protocols and algorithms for datacenters. Mohammad\u2019s research has garnered significant industry interest. His work on datacenter transport protocols has been implemented in Linux and Windows, and has been deployed by large network operators; his work on adaptive network load balancing algorithms has been implemented in Cisco\u2019s flagship datacenter switching products. Mohammad received his PhD from Stanford University and then spent two years at Insieme Networks (a datacenter networking startup) and Cisco before joining MIT. He is a recipient of the NSF CAREER Award (2018), SIGCOMM Rising Star Award (2017), Alfred P. Sloan Research Fellowship (2017), and multiple best paper awards.<\/p>\n
\n![\"2019](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/04\/2018_FacFellow_Stefano-Ermon_150x208.jpg\")
Stefano Ermon<\/h3>\nAssistant Professor, Computer Science Department<\/p>\n
Stanford University<\/p>\n
Stefano Ermon is an assistant professor of computer science in the CS Department at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory, and is a fellow of the Woods Institute for the Environment. His research is centered on techniques for probabilistic modeling of data, inference, and optimization, and is motivated by applications in the emerging field of computational sustainability. He has won several awards, including the IJCAI Computers and Thought Award, NSF CAREER Award, ONR Young Investigator Award, AFOSR Young Investigator Award, Sony Faculty Innovation Award, AWS Machine Learning Award, Hellman Faculty Fellowship, and four Best Paper Awards (AAAI, UAI and CP). Stefano earned his PhD in Computer Science at Cornell University in 2015.<\/p>\n
\n![\"2019](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/04\/2018_FacFellow_Jessica-Hullman_150x208.jpg\")
Jessica Hullman<\/h3>\nAssistant Professor, Computer Science + Journalism<\/p>\n
Northwestern University<\/p>\n
Jessica Hullman is an assistant professor in computer science and journalism at Northwestern. The goal of her research is to develop computational tools that improve how people reason with and make decisions from data. She is especially interested in challenges that arise in presenting data to non-expert audiences, where the need to convey a clear story often conflicts with goals of transparency and faithful presentation of uncertainty. Her current research focus is on uncertainty representation through interactive visual interfaces that enable users to articulate and reason about their prior beliefs. Jessica\u2019s research has been supported by the NSF (CRII, CAREER), Navy, Google, Tableau, and Adobe. Prior to joining Northwestern, she was an assistant professor at the University of Washington Information School. Her PhD is from the University of Michigan, and she spent a year as a postdoctoral scholar in computer science at the University of California, Berkeley.<\/p>\n
\n![\"2019](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/04\/2018_FacFellow_Yin-Tat-Lee_150x208.jpg\")
Yin Tat Lee<\/h3>\nAssistant Professor, Paul G. Allen School of Computer Science & Engineering<\/p>\n
University of Washington<\/p>\n
Yin Tat Lee is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. His research interests are primarily in algorithms, and they span a wide range of topics such as convex optimization, convex geometry, spectral graph theory, and online algorithms. His primary research goal is to find algorithms for solving a general class of convex optimization problems. He has received a variety of awards for his work, including Best Paper Award and 2x Best Student Paper Awards at FOCS, Best Paper Award at SODA, Best Paper Award at NeurIPS, Sprowls Award and NSF CAREER Award, and A.W. Tucker Prize.<\/p>\n
\n![\"2019](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/04\/2018_FacFellow_Raluca-Ada-Popa_150x208.jpg\")
Raluca Ada Popa<\/h3>\nAssistant Professor, Electrical Engineering and Computer Science<\/p>\n
University of California, Berkeley<\/p>\n
Raluca Ada Popa is an assistant professor of computer science at UC Berkeley working in computer security, systems, and applied cryptography. She is a co-founder and co-director of the RISELab at UC Berkeley, as well as a co-founder and CTO of a cybersecurity startup called PreVeil. Raluca received her PhD in computer science from MIT as well as her Masters and two BS degrees in computer science and in mathematics. She is the recipient of a Sloan Foundation Fellowship, a George M. Sprowls Award for best MIT CS doctoral thesis, and a Johnson Award for best CS Masters of Engineering thesis from MIT.<\/p>\n<\/p>\n<\/div>\n
\n \t2014 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/yong-yeolahn75x105.jpg\")
Yong-Yeol Ahn<\/h3>\nAssistant Professor, School of Informatics and Computing<\/p>\n
Indiana University Bloomington<\/p>\n
Yong-Yeol Ahn\u2019s research develops and leverages mathematical and computational methods to study complex systems such as cells, the brain, society, and culture. His recent contribution includes a new framework to identify pervasively overlapping modules in networks, network-based algorithms to predict viral memes, and a new computational approach to study food culture. He is currently an assistant professor at the School of Informatics and Computing at Indiana University, Bloomington. He worked as a postdoctoral research associate at Northeastern University and at the Dana-Farber Cancer Institute for three years after earning his PhD in Statistical Physics from KAIST in 2008.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/byung-gonchun75x105.jpg\")
Byung-Gon Chun<\/h3>\nAssistant Professor, Department of Computer Science and Engineering<\/p>\n
Seoul National University<\/p>\n
Byung-Gon Chun is interested in creating new platforms for operating and distributed systems. He is currently developing a big data platform that makes it easy to implement large-scale, fault-tolerant, heterogeneous data processing applications. He has also built systems that seamlessly integrate cloud computing with mobile devices for improved performance, reliability, and security. Chun received his PhD in Computer Science from the University of California, Berkeley. Prior to joining Seoul National University, Chun was a principal scientist at Microsoft, a research scientist at Yahoo! Research and Intel Research, and a postdoctoral researcher at ICSI.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/diegofernandezslezak75x105.jpg\")
Diego Fern\u00e1ndez Slezak<\/h3>\nAssistant Professor, Department of Computer Science<\/p>\n
University of Buenos Aires<\/p>\n
Diego Fern\u00e1ndez Slezak\u2019s work focuses on novel methods for text analysis in massive-scale repositories to find stereotyped patterns in human thought. The goal is the development and use of machine-learning techniques to study digital text corpora associated with cognitive processes, aiming at identifying the mental operations underlying behavioral processes, with application to mental health and education. Diego Fern\u00e1ndez Slezak received his PhD in Computer Science in 2010 from University of Buenos Aires and was recipient of the IBM PhD Fellowship.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/roxanageambasu75x105.jpg\")
Roxana Geambasu<\/h3>\nAssistant Professor, Computer Science Department<\/p>\n
Columbia University<\/p>\n
Roxana Geambasu works at the intersection of three computer science fields: distributed systems, operating systems, and security and privacy. Her research aims to increase privacy in today\u2019s data-driven world. Privacy has become a rare commodity in today\u2019s world, due to users who are too eager to share their data online and Web services that aggressively collect and use that information. Roxana\u2019s goal is to forge a new world, in which Web services are designed from the ground up with privacy in mind, and where users are more aware of the privacy implications of their online actions. Roxana obtained her Ph.D. from the University of Washington and was awarded a 2014 NSF CAREER award, an Honorable Mention for the 2013 inaugural Dennis M. Ritchie Doctoral Dissertation Award, a William Chan Memorial Dissertation Award, two best paper awards, and a 2013 Google Faculty Research Award.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/percyliang75x105.jpg\")
Percy Liang<\/h3>\nAssistant Professor, Computer Science Department<\/p>\n
Stanford University<\/p>\n
Percy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His research interests include (i) parsing natural language into semantic representations (e.g., executable code), for supporting intelligent user interfaces; and (ii) developing machine learning algorithms that infer rich latent structures (e.g., programs) from limited supervision (e.g., program output), balancing computational and statistical tradeoffs. He won a best student paper at the International Conference on Machine Learning in 2008, received the NSF, GAANN, and NDSEG fellowships, and is also a 2010 Siebel Scholar.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/davidsteurer75x105.jpg\")
David Steurer<\/h3>\nAssistant Professor, Department of Computer Science<\/p>\n
Cornell University<\/p>\n
David Steurer investigates the power and limitations of efficient algorithms for optimization problems that are at the heart of computer science and its applications. A focus of his work has been the Unique Games Conjectures whose resolution\u2014no matter in which direction\u2014promises new insights into the capabilities of efficient algorithms. As part of the research effort to resolve this conjecture, he studies provable guarantees of the sum-of-squares method, a compelling meta-algorithm that applies to a wide-range of problems and has the potential to unify the design of efficient algorithms for difficult optimization problems. Steurer received his PhD from Princeton University and was a postdoctoral researcher at Microsoft Research for two years before joining Cornell University. He is the recipient of the 2010 FOCS best paper award, the 2011 ACM Doctoral Dissertation Award Honorable Mention, an NSF CAREER Award, and an Alfred P. Sloan Research Fellowship.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/vinodvaikuntanathan75x105.jpg\")
Vinod Vaikuntanathan<\/h3>\nAssistant Professor, Electrical Engineering and Computer Science Department<\/p>\n
Massachusetts Institute of Technology<\/p>\n
Vinod Vaikuntanathan is a Steven and Renee Finn Career Development Assistant Professor of Computer Science at MIT. His main research interest is in the theory and practice of cryptography. He works on lattice-based cryptography, building advanced cryptographic primitives using integer lattices; leakage-resilient cryptography, defining and developing algorithms resilient against adversarial information leakage; and more recently, the theory and practice of computing on encrypted data, constructing powerful cryptographic objects such as fully homomorphic encryption and functional encryption. Vinod got his Ph.D. from MIT where he received a 2009 George M. Sprowls Award for the best MIT Ph.D. thesis in Computer Science. He is also a recipient of the 2008 IBM Josef Raviv Postdoctoral Fellowship, the 2009, the 2013 Alfred P. Sloan Research Fellowship, and a 2014 NSF CAREER award.<\/p>\n<\/p>\n<\/div>\n
\n \t2013 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/anima_anandkumar.jpg\")
Animashree Anandkumar<\/h3>\nAssistant Professor, Department of Electrical Engineering and Computer Science<\/p>\n
University of California, Irvine<\/p>\n
Animashree Anandkumar\u2019s research lies at the interface of theory and practice of large-scale machine learning and high dimensional statistics. Her theoretical contributions include analysis of high-dimensional estimation of graphical models and developing tensor methods for learning latent variable models. She has applied the developed algorithms to various problems in social networks and computational biology. She is currently an assistant professor at the Department of Electrical Engineering and Computer Science at the University of California, Irvine. She spent a year as a postdoctoral researcher at MIT and got her PhD from Cornell University. She has been a visiting researcher at Microsoft Research New England. She is the recipient of the ARO Young Investigator Award, NSF CAREER Award, IBM Fran Allen PhD fellowship, and several paper awards.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/katrina_ligett.jpg\")
Katrina Ligett<\/h3>\nAssistant Professor, Computer Science and Economics<\/p>\n
California Institute of Technology<\/p>\n
Katrina Ligett is an assistant professor of Computer Science and Economics at Caltech. In her research, she develops theoretical tools to address problems in data privacy and to understand individual incentives in other complex settings. She received her PhD from Carnegie Mellon University in 2009 and was a postdoctoral fellow at Cornell University before joining the California Institute of Technology in 2011. She is a recipient of the AT&T Labs Graduate Research Fellowship, the NSF Graduate Research Fellowship, the CIFellows Postdoctoral Research Fellowship, the NSF Mathematical Sciences Postdoctoral Research Fellowship, and an NSF CAREER award.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/michael_milford75x100.jpg\")
Michael Milford<\/h3>\nSenior Lecturer, School of Electrical Engineering and Computer Science<\/p>\n
Queensland University of Technology<\/p>\n
Michael Milford\u2019s research investigates how robots and biological systems map and navigate the world. He builds computational models based on experimental results and theories from the fields of neuroscience and biology and deploys them on robotic systems navigating in challenging real world environments. This novel research methodology has produced state-of-the-art results in robotics and yielded insights into how the brain may map and navigate the world. Milford received his PhD from the University of Queensland in 2006 and is the recipient of an Australian Research Council DECRA Fellowship and Discovery Project award.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/ruslan_salakhutdinov.jpg\")
Ruslan Salakhutdinov<\/h3>\nAssistant Professor, Department of Statistics and Computer Science<\/p>\n
University of Toronto<\/p>\n
Ruslan Salakhutdinov received his PhD in computer science from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an assistant professor in the departments of Statistics and Computer Science. His primary interests lie in artificial intelligence, machine learning, deep learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data. He is an action editor of the Journal of Machine Learning Research<\/em> and served on the senior programme committee of several learning conferences, including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, a recipient of the Early Researcher Award and Connaught New Researcher Award, and is a Scholar of the Canadian Institute for Advanced Research.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/michael_schapira.jpg\")
Michael Schapira<\/h3>\nSenior Lecturer, School of Computer Science and Engineering<\/p>\n
Hebrew University of Jerusalem<\/p>\n
Michael Schapira\u2019s research draws ideas from algorithmic and economic theory to design practical Internet protocols with provable guarantees (for example, for routing and traffic management). His research aims to both \u201cfix\u201d\u2019 today\u2019s Internet protocols and to design new and improved (better performing, secure, failure-resilient, and so forth) protocols for the future Internet. Schapira also has a broad research interest in the interface of computer science, game theory, and economics. He is a recipient of the Allon Fellowship (2011) and a member of the Israeli Center of Research Excellence in Algorithms. Prior to joining Hebrew University, Schapira was a postdoctoral researcher at the University of California, Berkeley, Yale University, and Princeton University, and a visiting scientist in Google New York\u2019s Infrastructure Networking group.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/monica_tentori-75x105.jpg\")
Monica Tentori<\/h3>\nAssistant Professor, Department of Computer Science<\/p>\n
Center for Scientific Research and Higher Education (CICESE)<\/p>\n
Monica Tentori investigates the human experience of ubiquitous computing to inform the design of ubiquitous environments that effectively enhance humans\u2019 interactions with their world. Her research intersecting human-computer interaction and ubiquitous computing particularly focuses on designing, developing, and evaluating natural user interfaces, self-reflection capture tools, and new interaction models for ubiquitous computing. Her work is being applied to healthcare and urban living to support the needs of urban citizens, hospital workers, elders, and individuals with autism and their caregivers. Tentori\u2019s research demonstrates that effectively designed ubiquitous environments have the potential to promote healthy lifestyles and independence, and positively impact attention, behavior, and workload.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/ryan_williams.jpg\")
Ryan Williams<\/h3>\nAssistant Professor, Computer Science Department<\/p>\n
Stanford University<\/p>\n
Ryan Williams works in algorithm design and complexity theory. He studies how to construct more efficient algorithms for solving computational problems, as well as how to mathematically rule out the possibility of efficient algorithms for other problems. Such impossibility results are generally perceived as very difficult; algorithms can be very clever, and it is hard to reason about all cleverness one could have. The famous P versus NP question asks about the power of efficient algorithms. Williams\u2019 work shows how the design and analysis of algorithms for core problems in computer science can often be exploited to rule out efficient algorithms for other core problems, raising new questions about our understanding of efficient computation. Williams received his PhD from Carnegie Mellon University in 2007 under Manuel Blum. His honors include some best paper awards and an Alfred P. Sloan Fellowship.<\/p>\n<\/p>\n<\/div>\n
\n \t2012 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/emma_brunskill.jpg\")
Emma Brunskill<\/h3>\nAssistant Professor, Department of Computer Science<\/p>\n
Carnegie Mellon University<\/p>\n
Emma Brunskill\u2019s research focuses on creating automated decision systems that interact with people, a challenge that spans artificial intelligence, machine learning, and human-computer interaction. She is particularly interested in adaptive, individualized tutoring systems that learn and self-optimize. Emma also works on health applications and on using information communication technologies to address challenges in low resource settings and developing regions.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/constantinos_daskalakis.jpg\")
Constantinos Daskalakis<\/h3>\nAssistant Professor, Department of Electrical Engineering and Computer Science<\/p>\n
Massachusetts Institute of Technology<\/p>\n
Constantinos Daskalakis is the X Consortium Assistant Professor of Computer Science at MIT. His research studies the interface of computer science and economics, with a focus on computational aspects of the Internet, online markets, and social networks. Daskalakis has been honored with the 2007 Microsoft Graduate Research Fellowship, the 2008 ACM Doctoral Dissertation Award, the 2010 Sloan Fellowship, the 2011 SIAM Outstanding Paper Prize, and the MIT Ruth and Joel Spira Award for Distinguished Teaching. His work on the complexity of the Nash equilibrium was honored by the Game Theory Society with the First Computer Science and Game Theory prize. Daskalakis received his PhD in Computer Science from UC Berkeley and was a post-doctoral researcher at Microsoft Research prior to joining MIT.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/stephen_gould.jpg\")
Stephen Gould<\/h3>\nSenior Lecturer, School of Computer Science<\/p>\n
Australian National University<\/p>\n
Stephen Gould is a faculty member in the Research School of Computer Science at the Australian National University. He received his PhD from Stanford University in 2010. Prior to his PhD, Stephen founded and worked in a number of start-up companies. Stephen\u2019s current research interests are in developing mathematical models that allow computers to learn how to interpret scenes from images. This involves recognizing objects and understanding how they interact with other objects and with their environment.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/andreas_krause.jpg\")
Andreas Krause<\/h3>\nAssistant Professor, Department of Computer Science<\/p>\n
ETH Zurich<\/p>\n
Andreas Krause\u2019s research is in learning and adaptive systems that actively acquire information; reason; and make decisions in large, distributed, and uncertain domains, such as sensor networks and the web. It spans theoretical aspects in machine learning and optimization, as well as interdisciplinary applications, ranging from community sensing to computational sustainability to social networks. He got his PhD in Computer Science from Carnegie Mellon University in 2008. He is a Kavli Frontiers Fellow of the U.S. National Academy of Sciences, and received an NSF CAREER award as well as several best paper awards.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/miriah_meyer.jpg\")
Miriah Meyer<\/h3>\nAssistant Professor, School of Computing<\/p>\n
University of Utah<\/p>\n
Miriah Meyer\u2019s research lives at the interface of computer science and data-intensive domains, where she designs interactive visualization systems that help scientists make sense of complex data. Her current work focuses on nimble and intuitive visualization tools that support research in genomics and molecular biology. Meyer takes a user-centered, problem-driven approach to developing visualizations that target specific scientific questions, working closely with scientists in an iterative and collaborative process. Her tools are integrated into the workflow of numerous biological labs and have led to several scientific discoveries, as well as to the validation and refinement of experimental and computational methods.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/juan_carlos_niebles.jpg\")
Juan Carlos Niebles<\/h3>\nAssistant Professor, Electrical and Electronic Engineering<\/p>\n
Universidad del Norte<\/p>\n
Juan Carlos is interested in helping computers and robots see the world. In particular, his research is focused on designing novel algorithms for automatic recognition and detailed understanding of human motions, activities, and behaviors from images and videos. This technology has the potential to enable new life-improving activity-aware systems, such as personal robots and smart homes, smart video surveillance, medical diagnosis and monitoring, automated sports analysis, and semantic video search.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/ashutosh_saxena.jpg\")
Ashutosh Saxena<\/h3>\nAssistant Professor, Department of Computer Science<\/p>\n
Cornell University<\/p>\n
Ashutosh Saxena works on a new generation of robots that will operate fully autonomously in human environments. His research is focused on the development of new machine-learning algorithms that enable robots to process massive amounts of sensory input data in real time and learn how to perform tasks in unstructured environments. His primary application domain is in assistive robotics, where his algorithms have enabled robots to perform tasks such as fetching items on verbal request, perform basic household chores, and identify and assist in human activities. He hopes to see such assistive robots appear in our homes, offices, and nursing homes soon.<\/p>\n<\/p>\n<\/div>\n
\n \t2011 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/maria_florina_balcan.jpg\")
Maria Florina Balcan<\/h3>\nAssistant Professor, School of Computer Science<\/p>\n
Georgia Institute of Technology<\/p>\n
Maria Florina Balcan is an assistant professor in the School of Computer Science at Georgia Institute of Technology. She received her PhD in Computer Science from Carnegie Mellon University under the supervision of Avrim Blum. From October 2008 until July 2009, she was a postdoc at Microsoft Research, New England. Her main research interests are computational and statistical machine learning, computational aspects in economics and game theory, and algorithms. She is a recipient of the Carnegie Mellon University SCS Distinguished Dissertation Award and the National Science Foundation NSF CAREER Award.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/krishnendu_chatterjee.jpg\")
Krishnendu Chatterjee<\/h3>\nAssistant Professor<\/p>\n
Institute of Science and Technology Austria<\/p>\n
Krishnendu is interested in graph games that arise in the formal verification of systems, and has deep connections with logic and automata theory. He established many fundamental results related to stochastic games on graphs, and is currently working on quantitative graph games and its application to synthesis of correct systems. He got his PhD from University of California, Berkeley in 2007, and his thesis won the David Sakrison Memorial Prize and Ackermann Award.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/jure_leskovec.jpg\")
Jure Leskovec<\/h3>\nAssistant Professor, Department of Computer Science<\/p>\n
Stanford University<\/p>\n
Jure Leskovec is an assistant professor of Computer Science at Stanford University. His research focuses on the analysis and modeling of large social and information networks as the study of phenomena across the social, technological, and natural worlds. Problems he investigates are motivated by large scale data, the Web and Social Media. Jure received his PhD in Machine Learning from Carnegie Mellon University in 2008 and spent a year at Cornell University. His work received six best paper awards, won the ACM KDD cup and topped the Battle of the Sensor Networks competition.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/alistair-mcewan.jpg\")
Alistair McEwan<\/h3>\nLecturer of Computer Engineering, School of Electrical and Information Engineering<\/p>\n
The University of Sydney<\/p>\n
Alistair McEwan\u2019s work aims to solve major health issues with technology, and involves research in the emerging field of bioelectronics\u2014the interaction between electronics and biology. His current investigation of the electrode\u2013skin interface aims to improve emergency diagnosis of heart attack and stroke as well as long-term monitoring of cardiovascular disease. He also works on related projects in electrical-impedance imaging systems, microelectronic circuits and systems, and neuromorphic engineering.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/shwetak_patel.jpg\")
Shwetak Patel<\/h3>\nAssistant Professor, Departments of Computer Science and Electrical Engineering<\/p>\n
University of Washington<\/p>\n
Shwetak Patel\u2019s research is at the intersection of hardware, software, and human-computer interaction. His research focuses on building easy-to-deploy and practical sensing systems for the home. His work is being applied to sustainability, elder care, home safety, and the creation of new approaches for natural user interfaces. Many of his techniques use the existing utilities infrastructure as a \u201csensor,\u201d thereby reducing the need for additional instrumentation. In one example, Patel has developed techniques for energy and water monitoring that provide a detailed breakdown of consumption in the home through monitoring a single point on the utility infrastructure. Through these new sensing approaches, Patel envisions the ability to instrument homes easily with smart technology for high-value applications.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/anderson_rocha.jpg\")
Anderson de Rezende Rocha<\/h3>\nAssistant Professor, Institute of Computing<\/p>\n
University of Campinas<\/p>\n
Professor Rocha\u2019s research interests include digital image and video forensics, computer vision, pattern analysis, and machine intelligence\u2014focused on the field of digital document forensics. He seeks solutions for problems regarding collection, organization, and classification of digital evidence that is used by law enforcement agencies in Brazil and abroad. He is investigating how to reduce the misuse of important evidence and is working on digital categorization solutions to reduce the technical effort that is required to analyze each piece of evidence. Professor Rocha\u2019s work emphasizes tracking the source of the evidence, new techniques for establishing authenticity, and exposing possible tampering.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/noah_snavely.jpg\")
Keith Noah Snavely<\/h3>\nAssistant Professor, Computer Science Department<\/p>\n
Cornell University<\/p>\n
Noah Snavely is interested in using massive collections of images on the web to better understand and visualize our world. His research builds new computer-vision algorithms for scalable 3-D reconstruction, new graphics techniques for experiencing places through online photos, and new ways to enable communities of photographers to capture useful image collections. His software is being used by educators, artists, and scientists across a range of disciplines.<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/brent_waters.jpg\")
Brent Waters<\/h3>\nAssistant Professor, Department of Computer Sciences<\/p>\n
University of Texas<\/p>\n
Brent Waters studies cryptography and computer security. His research is laying the foundations for a new vision of encryption called Functional Encryption. Instead of encrypting to individual users, in a Functional Encryption system, one can embed any access predicate into the cipher text itself. In addition, he is interested in understanding the foundational underpinnings of cryptography and in developing security primitives that are both practical and provably secure.<\/p>\n<\/p>\n<\/div>\n
\n \t2010 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/sinanaral2010_75px.jpg\")
Sinan Aral<\/h3>\nDepartment of Information, Operations, and Management Sciences<\/p>\n
New York University Stern School of Business<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/dougdowney2010_75px.jpg\")
Doug Downey<\/h3>\nDepartment of Electrical Engineering and Computer Science<\/p>\n
Northwestern University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/raananfattal2010_75px.jpg\")
Raanan Fattal<\/h3>\nSchool of Computer Science and Engineering<\/p>\n
The Hebrew University of Jerusalem<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/abhishelat2010_75px.jpg\")
abhi shelat<\/h3>\nDepartment of Computer Science<\/p>\n
University of Virginia<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/haiyingshen2010_75px.jpg\")
Haiying Shen<\/h3>\nDepartment of Electrical and Computer Engineering<\/p>\n
Clemson University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/cyrillstachniss2010_75px.jpg\")
Cyrill Stachniss<\/h3>\nDepartment of Computer Science<\/p>\n
University of Freiburg, Germany<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/evimariaterzi2010_75px.jpg\")
Evimaria Terzi<\/h3>\nComputer Science Department<\/p>\n
Boston University<\/p>\n<\/p>\n<\/div>\n
\n \t2009 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/bejerano_2009.jpg\")
Gill Bejerano<\/h3>\nDevelopmental Biology and Computer Science<\/p>\n
Stanford University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/ceze_2009.jpg\")
Luis Ceze<\/h3>\nComputer Science and Engineering<\/p>\n
University of Washington<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/immorlica_2009.jpg\")
Nicole Immorlica<\/h3>\nElectrical Engineering and Computer Science Department<\/p>\n
Northwestern University, McCormick School of Engineering<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/lazebnik_2009.jpg\")
Svetlana Lazebnik<\/h3>\nDepartment of Computer Science<\/p>\n
University of North Carolina at Chapel Hill<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/pass_2009.jpg\")
Rafael Pass<\/h3>\nDepartment of Computer Science<\/p>\n
Cornell University<\/p>\n<\/p>\n<\/div>\n
\n \t2008 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/grauman.jpg\")
Kristen Grauman<\/h3>\nComputer Sciences<\/p>\n
University of Texas at Austin<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/hohenberger.jpg\")
Susan Hohenberger<\/h3>\nDepartment of Computer Science<\/p>\n
Johns Hopkins University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/kleinberg.jpg\")
Robert Kleinberg<\/h3>\nComputer Science<\/p>\n
Cornell University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/levis.jpg\")
Philip Levis<\/h3>\nDepartments of Computer Science and Engineering<\/p>\n
Stanford University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/karen_lipkow.jpg\")
Karen Lipkow<\/h3>\nDepartment of Biochemistry<\/p>\n
University of Cambridge<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/tedrake.jpg\")
Russell Tedrake<\/h3>\nElectrical Engineering and Computer Science<\/p>\n
Massachusetts Institute of Technology<\/p>\n<\/p>\n<\/div>\n
\n \t2007 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/balazinska.jpg\")
Magdalena Balazinska<\/h3>\nDepartment of Computer Science and Engineering<\/p>\n
University of Washington<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/bongard.jpg\")
Josh Bongard<\/h3>\nDepartment of Computer Science<\/p>\n
University of Vermont<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/cheny.jpg\")
Yixin Chen<\/h3>\nDepartment of Computer Science and Engineering<\/p>\n
Washington University in St. Louis<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/siepel.jpg\")
Adam Siepel<\/h3>\nBiological Statistics and Computational Biology<\/p>\n
Cornell University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/vonahn.jpg\")
Luis von Ahn<\/h3>\nDepartment of Computer Science<\/p>\n
Carnegie Mellon University<\/p>\n<\/p>\n<\/div>\n
\n \t2006 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/barzilay.jpg\")
Regina Barzilay<\/h3>\nComputer Science and Artificial Intelligence<\/p>\n
Massachusetts Institute of Technology<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/hertzmann.jpg\")
Aaron Hertzmann<\/h3>\nComputer Science<\/p>\n
University of Toronto<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/klemmer.jpg\")
Scott Klemmer<\/h3>\nComputer Science<\/p>\n
Stanford University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/kohler.jpg\")
Eddie Kohler<\/h3>\nComputer Science<\/p>\n
University of California, Los Angeles<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/lif.jpg\")
Fei-Fei Li<\/h3>\nComputer Science<\/p>\n
Stanford University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/no_photo.png\")
Mark Rouncefield<\/h3>\nComputing Department<\/p>\n
University of Lancaster<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/andrey_rybalchenko.jpg\")
Andrey Rybalchenko<\/h3>\nMax Planck Institute for Software Systems<\/p>\n<\/p>\n<\/div>\n
\n \t2005 Faculty Fellows <\/h4>\n
\n\n
![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/ruth_baker.jpg\")
Ruth Baker<\/h3>\nCentre for Mathematical Biology<\/p>\n
University of Oxford<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/durand.jpg\")
Fr\u00e9do Durand<\/h3>\nComputer Graphics<\/p>\n
Massachusetts Institute of Technology<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/khot.jpg\")
Subhash Khot<\/h3>\nCollege of Computing<\/p>\n
Georgia Institute of Technology<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/klein.jpg\")
Dan Klein<\/h3>\nComputer Science Division<\/p>\n
University of California, Berkeley<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/nagpal.jpg\")
Radhika Nagpal<\/h3>\nSchool of Engineering and Applied Sciences<\/p>\n
Harvard University<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/wangw.jpg\")
Wei Wang<\/h3>\nDepartment of Computer Science<\/p>\n
University of North Carolina at Chapel Hill<\/p>\n
\n![\"Portrait](\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/07\/klaus-peter_zauner.jpg\")
Klaus-Peter Zauner<\/h3>\nSchool of Electronic and Computer Science<\/p>\n
University of Southampton<\/p>\n<\/p>\n<\/div>\n<\/div>\n\n\n","protected":false},"featured_media":498236,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":true,"_classifai_error":"","footnotes":""},"msr-opportunity-type":[155533],"msr-region":[197900,243744],"msr-locale":[268875],"msr-program-audience":[243727],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-493265","msr-academic-program","type-msr-academic-program","status-publish","has-post-thumbnail","hentry","msr-opportunity-type-grants-and-fellowships","msr-region-north-america","msr-region-south-america","msr-locale-en_us","msr-program-audience-faculty"],"msr_description":"Two-year fellowship that recognizes innovative, promising early-career professors in North America who are exploring breakthrough, high-impact research.","msr_social_media":[],"related-researchers":[],"tab-content":[{"id":0,"name":"About","content":"
What it is<\/h2>\r\nTwo-year fellowship that recognizes innovative, promising early-career professors in the Americas who are exploring breakthrough, high-impact research in computer science or a related field.\r\n\r\nThe Microsoft Research Faculty Fellowship recognizes innovative, promising new faculty, whose exceptional talent for research and innovation identifies them as emerging leaders in their fields. Provisions of the 2021 award include $100,000 USD awarded annually for two years starting in the fall of 2021.\r\n
Timeline<\/h2>\r\n
- \r\n \t
- Nominations, from the university or Microsoft nominators, closed February 22, 2021<\/li>\r\n \t
- Qualified nominees were sent an invitation email on March 1, 2021 to submit their proposal<\/li>\r\n \t
- Proposals and reference letters were accepted through March 29, 2021<\/li>\r\n \t
- Finalists notified in early May and interviewed virtually May 17-18, 2021<\/strong><\/li>\r\n \t
- Recipients announced by early July 2021<\/li>\r\n<\/ul>\r\n
Eligibility criteria<\/h2>\r\n
How to submit a proposal<\/h3>\r\nCandidates must be nominated by their university or a Microsoft nominator before receiving an invitation to submit a proposal.\r\n
Nominators<\/h3>\r\n
- \r\n \t
- Microsoft\u2019s mission is to empower every person and every organization on the planet to achieve more. Fellows should support this mission by fostering diverse and inclusive cultures within their communities.<\/li>\r\n \t
- Faculty must be nominated by their university or a Microsoft Research lab member or a researcher within an applied research group in other parts of Microsoft.<\/li>\r\n \t
- A maximum of three nominations per university will be accepted; if more than one is nominated, then the other one or two nominees should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.<\/li>\r\n \t
- Microsoft Research lab members and researchers within an applied research group in other parts of Microsoft may nominate a maximum of two faculty. If more than one faculty is nominated, then at least one nominee should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.<\/li>\r\n \t
- Nominators must agree to write and submit a one-page recommendation letter in support of their nominee, if requested by the nominee.<\/li>\r\n<\/ul>\r\n
Nominees<\/h3>\r\n
- \r\n \t
- Full-time faculty at a degree-granting college or university in North America or South America.<\/li>\r\n \t
- Faculty must have received their terminal degree (e.g., PhD, DSc) in May 2016 or later. We will take into account approved delays, like leaves of absences from the workplace and postdocs, on a case by case basis if you contact us at msfellow@microsoft.com<\/a>.<\/li>\r\n \t
- Currently conducting research, advising graduate students, and teaching in a classroom.<\/li>\r\n \t
- Proposed research must be closely related to the general research areas carried out by Microsoft as noted in the Our research<\/em> tab above.<\/li>\r\n<\/ul>\r\n
Recipients<\/h2>\r\n
- \r\n \t
- If awarded, the recipient must remain an active, full-time faculty during the two consecutive academic years of the award or forfeit the award. Fellowships are not available for extension. If you require time away for family or medical leave, this will be accommodated. If you are unsure if a particular need for time away will affect the award, you can contact us at Microsoft Research Fellowships (msfellow@microsoft.com<\/a>).<\/li>\r\n \t
- Payment of the award, as described above, will be made directly to the university and dispersed according to the university\u2019s policies. Microsoft will have discretion as to how any remaining funds will be used if the faculty is no longer qualified to receive funding.<\/li>\r\n \t
- A recipient of the Microsoft Research Faculty Fellowship subject to disciplinary proceedings for inappropriate behavior, including but not limited to discrimination, harassment (including sexual harassment), or plagiarism will forfeit their funding.<\/li>\r\n<\/ul>\r\nIf you do not meet the above criteria, you may be eligible for other Academic Programs<\/a>.\r\n\r\nMicrosoft actively seeks to foster greater levels of diversity in our workforce and in our pipeline of future researchers. We are always looking for the best and brightest talent and celebrate individuality. We invite candidates to come as they are and do what they love.\r\n
Contact us<\/h2>\r\nDirect any questions not answered in the FAQ<\/a> to the Fellowship\u2019s Program Chair, John Krumm<\/a>, or the Program Manager at msfellow@microsoft.com<\/a>."},{"id":1,"name":"Nomination","content":"
How to submit a nomination<\/h2>\r\nNominations for the 2021 Microsoft Research Faculty Fellowship closed on Monday, February 22, 2021 at 12:00 PM (Noon) Pacific Time. Universities and Microsoft nominators should inform faculty nominees once they have submitted their nomination so the nominees can begin collecting the details on the Proposal tab<\/a>. Nominated faculty will receive an invitation email in early March 2021 to submit their proposal.\r\n\r\nA maximum of three nominations per university will be accepted; if more than one is nominated, then the other one or two nominees should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.\r\n\r\nMicrosoft Research lab members and researchers within an applied research group in other parts of Microsoft may nominate a maximum of two faculty. If more than one faculty is nominated, then at least one nominee should help us increase the opportunities for faculty who are underrepresented in the field of computing. This includes those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability.\r\n\r\nNominations must include:\r\n
- \r\n \t
- \r\n
- \r\n \t
- Your name, email, and job title as the person submitting the nomination on behalf of your university or as a Microsoft nominator<\/li>\r\n \t
- For university nominations, a brief description (a few sentences) of your university's process for determining which faculty to nominate for this fellowship<\/li>\r\n \t
- For university nominations, attestation that the process used to determine which faculty to nominate from your university for this fellowship was fair and non-discriminatory<\/li>\r\n \t
- Nominee\u2019s name, email, country, university, and department<\/li>\r\n \t
- Nominee\u2019s primary and secondary areas of research (click on the Our research<\/em> tab at the top of the page for a full list)<\/li>\r\n \t
- Attestation that the nominee received their terminal degree (e.g. PhD, DSc) in May 2016 or later (having taken into account approved delays)<\/li>\r\n \t
- Attestation that the nominee is a full-time faculty at a degree-granting college or university, conducting research, advising graduate students, and teaching in a classroom<\/li>\r\n \t
- Attestation that the nominee you are putting forth is either someone who self-identifies as underrepresented in the field of computing (as detailed above) or not<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>"},{"id":2,"name":"Proposal","content":"
How to submit a proposal<\/h2>\r\nIf you were nominated by your university or a Microsoft nominator, then you should have received an email from Microsoft Research Faculty Fellowship on March 1, 2021, which includes a private link to submit your proposal. Please check your junk email folder if you do not see it in your inbox.\r\n\r\nIf you are a nominee, the below outlines the information necessary to submit your proposal in our submission portal.\r\n\r\nYou will be asked to answer the below questions in a form:\r\n
- \r\n \t
- \r\n
- \r\n \t
- Name, email, job title, country, university, and department<\/li>\r\n \t
- Primary and secondary areas of research (click on the Our research<\/em> tab at the top of the page for a full list)<\/li>\r\n \t
- Month and year you received your terminal degree (e.g. PhD, DSc)<\/li>\r\n \t
- Month and year you started your career as a professor<\/li>\r\n \t
- URL to your professional website (optional, but strongly recommended; you are encouraged to make certain it is up-to-date)<\/li>\r\n \t
- List up to 5 of the top awards received for best paper or long-term impact paper, if applicable (include award name like \u201cbest paper\u201d, authors, titles, conferences, and years)<\/li>\r\n \t
- List up to 5 of the top awards received for teaching or mentoring, if applicable<\/li>\r\n \t
- List up to 5 other top awards received not already listed above, if applicable<\/li>\r\n \t
- List up to 5 top ranks held in a professional society, if applicable (e.g. \u201cSenior member ACM\u201d)<\/li>\r\n \t
- List up to 5 research grants received, if applicable (include titles of the projects, years received, amounts, and other principle investigators)<\/li>\r\n \t
- Attestation that you received your terminal degree (e.g. PhD, DSc) in May 2016 or later (having taken into account approved delays)<\/li>\r\n \t
- Attestation that you are a full-time faculty at a degree-granting college or university, conducting research, advising graduate students, and teaching in a classroom<\/li>\r\n \t
- Attestation as to whether or not you are a faculty who is underrepresented in the field of computing which include those who self-identify as a woman, African American, Black, Hispanic, Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and\/or person with a disability \u2013 if more than one faculty is nominated, then the other one or two should help us increase the opportunities for faculty who are underrepresented in the field of computing<\/li>\r\n \t
- Self-assessment of the Statement of Good Standing: \u201cI declare I have never been disciplined for inappropriate behavior, including, but not limited to discrimination, harassment (including sexual harassment), or plagiarism. If I am selected to receive funding under Microsoft\u2019s Fellowship program, during my funding time period, I agree to inform Microsoft should I be subjected to disciplinary proceedings for inappropriate behavior, including but not limited to discrimination, harassment (including sexual harassment), or plagiarism which would result in forfeiture of funding under Microsoft\u2019s Fellowship program<\/em>.\u201d<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\nYou will be asked to upload 2 documents:\r\n\r\nYour curriculum vitae and two-page statement of research will be uploaded separately. Accepted formats are docx, doc, and pdf. Email or hard-copy submissions will not be considered. Name the individual files using the convention indicated below. Include your first name and last name as part of your file name each separated by an underscore (e.g. Jane_Smith_cv.docx).\r\n
- \r\n \t
- \r\n
- \r\n \t
- Curriculum vitae \u2013 file name: cv<\/strong><\/li>\r\n \t
- Two-page statement of research to include: your major research initiatives, what makes your approaches especially innovative, and how you would use the funding and the impact it would have on your research; a paragraph describing how you support the mission of fostering diversity and inclusive cultures within your student and researcher communities and how you plan to in the future; we suggest a font no smaller than 10-point and references should be included as part of the two pages - file name: research<\/strong><\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\nYou will be asked to request 3 letters of recommendation via the submission portal:\r\n
- \r\n \t
- \r\n
- \r\n \t
- Add the contact information (name, affiliation, email) and send the email request through the submission portal to your three recommenders as soon as possible so they have ample time to provide a letter. Their deadline is the same as your proposal deadline on Monday, March 29, 2021<\/strong>. They should be established researchers familiar with your research. Once you send the request through the submission portal, they will receive a private link to upload a letter of recommendation for you. Please note that you and your recommenders may need to check your junk folders in order to find emails from our portal. As reference, here is a list of the various system email addresses<\/a> you can add to allowed emails.<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\nProposals submitted to Microsoft will not be returned. Microsoft cannot assume responsibility for the confidentiality of information in submitted proposals. Therefore, proposals should not contain information that is confidential, restricted, or sensitive. Microsoft reserves the right to make public the information on those proposals that receive awards, except those portions containing budgetary or personally identifiable information.\r\n\r\nIncomplete proposals will not be considered.\r\n\r\nDue to the volume of submissions, Microsoft cannot provide individual feedback on proposals."},{"id":3,"name":"FAQ","content":"Below are the answers to frequently asked questions about the 2021 Microsoft Research Faculty Fellowship.\r\n
Eligibility criteria<\/h3>\r\n[accordion]\r\n[panel header=\"What if I\u2019m a faculty attending a university outside the Americas?\"]\r\nThe Microsoft Research Faculty Fellowship includes only schools from the Americas. If you are a faculty at a school outside North America or South America, you are not eligible for this fellowship.\r\n[\/panel]\r\n[panel header=\"Do I have to be nominated by my university or can I nominate myself?\"]\r\nTo be considered for the award, you must be nominated by your university or a Microsoft Research lab member or a researcher within an applied research group in other parts of Microsoft. If you are nominated, you will be contacted to submit a proposal.\r\n[\/panel]\r\n[panel header=\"Can Microsoft employees or their family members be nominated?\"]\r\nEmployees and directors of Microsoft Corporation, and its subsidiaries and affiliates are not eligible, nor are persons involved in the execution or administration of this fellowship, or the family members of each above (parents, children, siblings, spouse\/domestic partners, or individuals residing in the same household).\r\n[\/panel]\r\n[\/accordion]\r\n
Nominations<\/h3>\r\n[accordion]\r\n[panel header=\"Do the universities need to coordinate with Microsoft nominators so they do not nominate the same person?\"]\r\nNo, universities do not need to coordinate with Microsoft nominators. It is acceptable to nominate the same faculty.\r\n[\/panel]\r\n[panel header=\"Is the limit on Microsoft nominators independent of the university limit on the number of individuals that can be nominated?\"]\r\nYes, the Microsoft limit is independent of the university limit.\r\n[\/panel]\r\n[panel header=\"Who is meant to submit the nomination?\"]\r\nThe university can designate any staff other than the nominee to submit the nomination. The nomination simply needs to be a coordinated effort to ensure there are no more than three submissions from each university.\r\n[\/panel]\r\n[panel header=\"Does the university have to submit a letter through the online tool as well in support of my nomination?\"]\r\nNo, we do not require a letter from the university.\r\n[\/panel]\r\n[panel header=\"If the faculty\u2019s research is already being funded, does it impact their eligibility for nomination and\/or receiving the award?\"]\r\nNot from our perspective.\r\n[\/panel]\r\n[\/accordion]\r\n
Research areas<\/h3>\r\n[accordion]\r\n[panel header=\"How do I determine my primary and secondary research areas? Where is the appropriate place to describe how they relate to my work (whether it's methodologically or theoretically)?\"]\r\n
- \r\n \t
- Your choices of primary and secondary areas help us choose who reviews your proposal.<\/li>\r\n \t
- Pick areas that align with conferences\/journals where you would publish.<\/li>\r\n \t
- The statement of research is the appropriate place to describe how research areas relate to your research.<\/li>\r\n<\/ul>\r\n[\/panel]\r\n[panel header=\"How do I choose which to pick for my research area if my research is very interdisciplinary?\"]\r\nMicrosoft Research is interdisciplinary, so it is something we understand. What you choose as a research area is a \"soft\" preference and will simply help us better route your proposal. Utilize the primary and secondary research area option to help capture and communicate your research area the best you can.\r\n\r\nHere are some suggestions and guiding questions to help you choose a research area:\r\n
- \r\n \t
- Do you have a home conference? Are there one or two conferences you go to in a more specific area?<\/li>\r\n \t
- Who do you want to be reading your proposal?<\/li>\r\n \t
- Who would you want to network with? What area of research are they in?<\/li>\r\n \t
- Who would be most excited about my topic? What area of research are they in?<\/li>\r\n<\/ul>\r\n[\/panel]\r\n[panel header=\"How related does my work need to be to Microsoft Research?\"]\r\nYour work should be of interest to Microsoft Research lab members or researchers within an applied research group in other parts of Microsoft; however, it doesn\u2019t need to directly line up with an existing project or topic. It is important for your work to be related enough that Microsoft Research will be able to review it and have interest in supporting it. Microsoft Research is large, interdisciplinary, and covers a broad area -- use the Our research<\/em> tab above as a guideline for the areas we cover. When in doubt, we suggest you browse the webpages of Microsoft Research lab members and researchers within an applied research group in other parts of Microsoft who look like they may be related to your area and see if they have papers in the similar topics or publish in conferences you publish in and\/or attend. If you find one or more such people that share these connections with you, then you can feel confident that your work is related enough to submit a proposal.\r\n[\/panel]\r\n[\/accordion]\r\n
Letters of recommendation<\/h3>\r\n[accordion]\r\n[panel header=\"Who should write my letters of recommendation?\"]\r\nGiven you need three letters, it would be good to include a letter from one person who can speak about your current research and one person who has known you longer, even if it may not be in your current research area. The longer-term perspective is definitely important and valuable. The value of a letter is evaluating how you work, how you collaborate with people, and what your process is as a researcher. This transcends what your particular topic is. Keep in mind that one letter doesn't have to address all things; across all three letters, we want to get a full picture of who you are over a longer term, but also insight into your recent work.\r\n[\/panel]\r\n[panel header=\"Are you more interested in learning about technical and research specific aspects of my work, or are other things, such as outreach\/other university activities of interest as well?\"]\r\nThe purpose of a letter of recommendation is to provide us with the bigger picture of what you are doing, how you work as a researcher, how you learn, how you approach projects, and how you collaborate with others. The letter will also provide us with insight from people who have been working with you and observing you for some amount of time.\r\n[\/panel]\r\n[panel header=\"For the letters of recommendation, is it a system where you list the people and your system will ask those people?\"]\r\nThose you provided as recommenders in our system will be sent an auto-generated email with instructions to upload their letters of recommendation.\r\n[\/panel]\r\n[\/accordion]\r\n
Review process<\/h3>\r\n[accordion]\r\n[panel header=\"Who will review the proposals?\"]\r\nProposals will be reviewed by Microsoft Research lab members and researchers within an applied research group in other parts of Microsoft whose expertise covers a wide range of disciplines. After the first review, a selection of faculty will be invited to interview. Award recipients are chosen from those finalists.\r\n[\/panel]\r\n[panel header=\"What are you looking for when you review my proposal?\"]\r\nWe look at how cutting edge your research is as well as the significance and impact of the research. We carefully read through your two-page statement of research, three letters of recommendation, and your CV to try to gauge this. Best paper and other top awards are not required, but are helpful signals. The two-page statement of research should include your major research initiatives, what makes your approaches especially innovative, and how you would use the funding and the impact it would have on your research.\r\n[\/panel]\r\n[panel header=\"When will I know the outcome of the review process?\"]\r\nFinalists will be contacted in early May about the virtual interview. Due to the volume of submissions, Microsoft cannot provide individual feedback on proposals.\r\n[\/panel]\r\n[panel header=\"How many nominations were there last year?\"]\r\nThere were nearly 200 nominations submitted last year.\r\n[\/panel]\r\n[\/accordion]\r\n
Award details<\/h3>\r\n[accordion]\r\n[panel header=\"If selected, when will my fellowship begin?\"]\r\nPersons awarded a fellowship in June will receive their financial awards by September of that year. Microsoft sends payment directly to the university, who will disperse funds according to their guidelines. This award will be provided as an unrestricted gift with no terms and restrictions applied to it. No portion of these funds should be applied to overhead or other indirect costs.\r\n[\/panel]\r\n[panel header=\"Are there any tax implications for me if I receive this fellowship?\"]\r\nThe tax implications for your award are based on the policy at your university and applicable tax laws.\r\n[\/panel]\r\n[panel header=\"Will intellectual property be an issue if I am awarded a fellowship?\"]\r\nThe Microsoft Research Faculty Fellowship is not subject to any intellectual property (IP) restrictions.\r\n[\/panel]\r\n[panel header=\"Is childcare an approved use of the award funding?\"]\r\nAbsolutely! There is no limit to the amount of your award that can be used for childcare.\r\n[\/panel]\r\n[\/accordion]"},{"id":4,"name":"Fellows","content":"
Microsoft Research Faculty Fellows<\/h2>\r\n
2021 Faculty Fellows<\/h3>\r\n
Baris Kasikci<\/a><\/h3>\r\nAssistant Professor\r\n\r\nUniversity of Michigan\r\n\r\nBaris Kasikci is an assistant professor of Electrical Engineering and Computer Science at the University of Michigan. His group builds efficient and trustworthy computer systems that improve the efficiency of data center applications, provide systems support for heterogeneous platforms, find and fix bugs, and improve hardware security. Previously, Baris was a researcher in the Systems and Networking Group at Microsoft Research Cambridge. He completed his PhD in Computer Science at EPFL and held roles at Intel, VMware, and Siemens. He is the recipient of an NSF CAREER award, Intel Rising Star Award, Google Faculty Award, VMware Early Career Grant, Jay Lepreau Best Paper Award at OSDI\u201918, IEEE MICRO Top Picks Award, VMware fellowship, Roger Needham Ph.D. Award for the best PhD thesis in computer systems in Europe, and the Patrick Denantes Memorial Prize for best PhD thesis in Computer Science at EPFL.\r\n\r\n
\r\n\r\nBoyla Mainsah<\/a><\/h3>\r\nAssistant Research Professor\r\n\r\nDuke University\r\n\r\nBoyla Mainsah is an Assistant Research Professor of Electrical and Computer Engineering (ECE) at Duke University. She received her PhD and master\u2019s degrees in Electrical and Computer Engineering at Duke University. Her research interests are in biomedical applications of signal processing and machine learning\/deep learning, with a focus on developing solutions for enhancing neuroprosthetics and for the discovery of novel biomarkers for diagnosis and prognosis. Her recent work includes leveraging information theory and active learning to improve the efficiency of brain-computer interfaces, leveraging natural language processing for speech enhancement in cochlear implants, and acoustic surveillance in individuals with left ventricular assist devices. Her work has received several recognitions, including the Duke ECE Outstanding PhD Dissertation Award, and best paper commendations from the Journal of Neural Engineering and the International Medical Informatics Association Yearbook. She is the recipient of an NIDCD Early Career Research Award.\r\n\r\n
\r\n\r\nShuran Song<\/a><\/h3>\r\nAssistant Professor\r\n\r\nColumbia University\r\n\r\nShuran Song is an assistant professor in the Department of Computer Science at Columbia University. Before that, she received her PhD in Computer Science at Princeton University. Her research interests lie at the intersection of computer vision and robotics. She is a recipient of several awards including the Best Paper Award at T-RO \u201820, Best Systems Paper Award at RSS \u201819, Best Manipulation Systems Paper Award from Amazon \u201818, and has been finalist for Best Paper Awards at conferences ICRA \u201820, CVPR'19, RSS \u201819, IROS \u201818.\r\n\r\n
\r\n\r\nDavid Wu<\/a><\/h3>\r\nAssistant Professor\r\n\r\nUniversity of Texas at Austin\r\n\r\nDavid Wu is joining the Department of Computer Science at the University of Texas at Austin as an assistant professor in Fall 2021. Since 2019, he has been the Anita Jones Career Enhancement Assistant Professor in Computer Science at the University of Virginia. David's research interests are in applied and theoretical cryptography as well as computer security, with a particular focus on developing new cryptographic primitives and systems to enable privacy-preserving computations. His research has been recognized by two Best Young-Researcher Paper Awards at CRYPTO, an Outstanding Paper Award at ESORICS, and the NSF CAREER Award. David received his PhD in computer science from Stanford University in 2018.\r\n\r\n
\r\n\r\nDiyi Yang<\/a><\/h3>\r\nAssistant Professor\r\n\r\nGeorgia Institute of Technology\r\n\r\nDiyi Yang is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology, where she leads the Social and Language Technologies (SALT) Lab. Her primary research interests span across fields in natural language processing, machine learning, and computational social science. Her research focuses on understanding the social aspects of language and building responsible NLP systems with social intelligence. Dr. Yang received her PhD from the Language Technologies Institute at Carnegie Mellon University, and her bachelor's degree from Shanghai Jiao Tong University in China. Her work has received multiple best paper awards and nominations at top human computer interaction and natural language processing conferences. Dr. Yang has won prestigious awards and recognitions such as Forbes 30 under 30 in Science and IEEE AI 10 to Watch, and has received several faculty research awards from Amazon, Facebook and Salesforce.\r\n\r\n
\r\n\r\n[accordion]\r\n[panel header=\"2020 Faculty Fellows\"]\r\n2020 Faculty Fellows<\/h3>\r\n
Loris D\u2019Antoni<\/h3>\r\nAssistant Professor, Department of Computer Sciences\r\n\r\nUniversity of Wisconsin-Madison\r\n\r\nLoris D'Antoni is an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin-Madison. There, he\u2019s affiliated with the madPL (Madison Programming Languages) Group. He received his bachelor's and master's degrees in Computer Science from the University of Torino in 2008 and 2010, respectively, and his PhD in Computer Science from the University of Pennsylvania in 2015. His research is centered on building fundamental verification and synthesis techniques that help programmers write software that meets their intent. In particular, his current main focus is on building practical and predictable program synthesis techniques that can be applied to computer networks, program repair, and machine learning. He has won several awards, including the NSF CAREER Award, Google Research Award, Morris and Dorothy Rubinoff Dissertation Award, and his papers were selected for special journal issues (TOPLAS<\/a>, FMSD<\/a>) and nominated for best paper awards (TACAS<\/a>).\r\n\r\n
\r\n\r\nChristina Delimitrou<\/h3>\r\nAssistant Professor, Electrical and Computer Engineering\r\n\r\nCornell University\r\n\r\nChristina is an Assistant Professor and the John and Norma Balen Sesquicentennial Faculty Fellow at Cornell University, where she leads the Systems, Architecture, and Infrastructure Lab (SAIL). Her research interests are in the areas of cloud computing, computer architecture, and applied machine learning. Her recent work focuses on leveraging ML to improve the performance predictability, resource efficiency, and security of large-scale datacenters. Christina\u2019s work has garnered significant industry impact, with several of the systems she has built being deployed in production cloud providers. Christina is the recipient of a Sloan Research Fellowship, an NSF CAREER Award, two Google Faculty Research Awards, a Facebook Faculty Research Award, four IEEE Micro Top Picks, and several best paper awards. Christina received her PhD in Electrical Engineering from Stanford University. Prior to that, she had earned an MS in Electrical Engineering, also from Stanford, and a diploma in Electrical and Computer Engineering from the National Technical University of Athens.\r\n\r\n
\r\n\r\nChelsea Finn<\/h3>\r\nAssistant Professor, Computer Science and Electrical Engineering Departments\r\n\r\nStanford University\r\n\r\nChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the ability of robots to develop broadly intelligent behavior through learning and interaction. To this end, her work spans machine learning, robotics, and computer vision, including deep learning for end-to-end robotic perception and control, meta-learning algorithms that enable flexible adaptation to new tasks and environments, and methods for self-supervised robot learning at scale. Dr. Finn received her Bachelor's degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at University of California, Berkeley. Her research has been recognized through the ACM Doctoral Dissertation Award, an NSF graduate research fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 Innovators under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg.\r\n\r\n
\r\n\r\nStefanie Mueller<\/h3>\r\nX-Window Consortium Career Development Assistant Professor, Department of Electrical Engineering and Computer Science (MIT EECS), Computer Science and Artificial Intelligence Laboratory (MIT CSAIL)\r\n\r\nMassachusetts Institute of Technology\r\n\r\nStefanie Mueller is the X-Career Development Assistant Professor in the MIT EECS department joint with MIT Mechanical Engineering and Head of the HCI Engineering Group at MIT CSAIL. In her research, she develops novel hardware and software systems that advance personal fabrication technologies. For her work, Stefanie has received multiple best paper awards at the most selective human-computer interaction venues (ACM CHI and ACM UIST), received an NSF CAREER award, and was named an Alfred P. Sloan Fellow as well as a Forbes 30 under 30 in Science. Over the last years, Stefanie has served as an ACM CHI Subcommittee Chair in 2019 and 2020 and is currently serving as the ACM UIST 2020 program chair. She has also been an invited speaker at more than 50 universities and research labs, such as MIT, Stanford University, Harvard University, University of California Berkeley, Carnegie Mellon University, and Microsoft Research.\r\n\r\n
\r\n\r\nAaron Sidford<\/h3>\r\nAssistant Professor, Management Science and Engineering\r\n\r\nStanford University\r\n\r\nAaron Sidford is an Assistant Professor of Management Science and Engineering at Stanford University, where he also has a courtesy appointment in Computer Science and an affiliation with the Institute for Computational and Mathematical Engineering (ICME). Aaron\u2019s research interests lie in optimization, the theory of computation, and the design and analysis of algorithms, with an emphasis on work at the intersection of continuous optimization, graph theory, numerical linear algebra, and data structures. His work focuses on the design of provably efficient algorithm for solving fundamental and pervasive large-scale problems in optimization and data-analysis. He has received multiple awards for his work in these areas including a Sloan Research Fellowship, an NSF CAREER Award, an ACM Doctoral Dissertation Award honorable mention, best paper awards in FOCS<\/a> and SODA<\/a>, and two best student paper awards in FOCS.\r\n\r\n
\r\n\r\n[\/panel]\r\n\r\n[panel header=\"2019 Faculty Fellows\"]\r\nMohammad Alizadeh<\/h3>\r\nAssistant Professor, Electrical Engineering and Computer Science\r\n\r\nMassachusetts Institute of Technology\r\n\r\nMohammad Alizadeh is the TIBCO Career Development Assistant Professor of Computer Science at MIT. His research interests are in the areas of networked computer systems and applied machine learning. His current research focuses on learning-augmented network systems, programmable networks, and network protocols and algorithms for datacenters. Mohammad's research has garnered significant industry interest. His work on datacenter transport protocols has been implemented in Linux and Windows, and has been deployed by large network operators; his work on adaptive network load balancing algorithms has been implemented in Cisco\u2019s flagship datacenter switching products. Mohammad received his PhD from Stanford University and then spent two years at Insieme Networks (a datacenter networking startup) and Cisco before joining MIT. He is a recipient of the NSF CAREER Award (2018), SIGCOMM Rising Star Award (2017), Alfred P. Sloan Research Fellowship (2017), and multiple best paper awards.\r\n\r\n
\r\n\r\nStefano Ermon<\/h3>\r\nAssistant Professor, Computer Science Department\r\n\r\nStanford University\r\n\r\nStefano Ermon is an assistant professor of computer science in the CS Department at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory, and is a fellow of the Woods Institute for the Environment. His research is centered on techniques for probabilistic modeling of data, inference, and optimization, and is motivated by applications in the emerging field of computational sustainability. He has won several awards, including the IJCAI Computers and Thought Award, NSF CAREER Award, ONR Young Investigator Award, AFOSR Young Investigator Award, Sony Faculty Innovation Award, AWS Machine Learning Award, Hellman Faculty Fellowship, and four Best Paper Awards (AAAI, UAI and CP). Stefano earned his PhD in Computer Science at Cornell University in 2015.\r\n\r\n
\r\n\r\nJessica Hullman<\/h3>\r\nAssistant Professor, Computer Science + Journalism\r\n\r\nNorthwestern University\r\n\r\nJessica Hullman is an assistant professor in computer science and journalism at Northwestern. The goal of her research is to develop computational tools that improve how people reason with and make decisions from data. She is especially interested in challenges that arise in presenting data to non-expert audiences, where the need to convey a clear story often conflicts with goals of transparency and faithful presentation of uncertainty. Her current research focus is on uncertainty representation through interactive visual interfaces that enable users to articulate and reason about their prior beliefs. Jessica's research has been supported by the NSF (CRII, CAREER), Navy, Google, Tableau, and Adobe. Prior to joining Northwestern, she was an assistant professor at the University of Washington Information School. Her PhD is from the University of Michigan, and she spent a year as a postdoctoral scholar in computer science at the University of California, Berkeley.\r\n\r\n
\r\n\r\nYin Tat Lee<\/h3>\r\nAssistant Professor, Paul G. Allen School of Computer Science & Engineering\r\n\r\nUniversity of Washington\r\n\r\nYin Tat Lee is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. His research interests are primarily in algorithms, and they span a wide range of topics such as convex optimization, convex geometry, spectral graph theory, and online algorithms. His primary research goal is to find algorithms for solving a general class of convex optimization problems. He has received a variety of awards for his work, including Best Paper Award and 2x Best Student Paper Awards at FOCS, Best Paper Award at SODA, Best Paper Award at NeurIPS, Sprowls Award and NSF CAREER Award, and A.W. Tucker Prize.\r\n\r\n
\r\n\r\nRaluca Ada Popa<\/h3>\r\nAssistant Professor, Electrical Engineering and Computer Science\r\n\r\nUniversity of California, Berkeley\r\n\r\nRaluca Ada Popa is an assistant professor of computer science at UC Berkeley working in computer security, systems, and applied cryptography. She is a co-founder and co-director of the RISELab at UC Berkeley, as well as a co-founder and CTO of a cybersecurity startup called PreVeil. Raluca received her PhD in computer science from MIT as well as her Masters and two BS degrees in computer science and in mathematics. She is the recipient of a Sloan Foundation Fellowship, a George M. Sprowls Award for best MIT CS doctoral thesis, and a Johnson Award for best CS Masters of Engineering thesis from MIT.\r\n\r\n[\/panel]\r\n\r\n[panel header=\"2014 Faculty Fellows\"]\r\nYong-Yeol Ahn<\/h3>\r\nAssistant Professor, School of Informatics and Computing\r\n\r\nIndiana University Bloomington\r\n\r\nYong-Yeol Ahn\u2019s research develops and leverages mathematical and computational methods to study complex systems such as cells, the brain, society, and culture. His recent contribution includes a new framework to identify pervasively overlapping modules in networks, network-based algorithms to predict viral memes, and a new computational approach to study food culture. He is currently an assistant professor at the School of Informatics and Computing at Indiana University, Bloomington. He worked as a postdoctoral research associate at Northeastern University and at the Dana-Farber Cancer Institute for three years after earning his PhD in Statistical Physics from KAIST in 2008.\r\n\r\n
\r\n\r\nByung-Gon Chun<\/h3>\r\nAssistant Professor, Department of Computer Science and Engineering\r\n\r\nSeoul National University\r\n\r\nByung-Gon Chun is interested in creating new platforms for operating and distributed systems. He is currently developing a big data platform that makes it easy to implement large-scale, fault-tolerant, heterogeneous data processing applications. He has also built systems that seamlessly integrate cloud computing with mobile devices for improved performance, reliability, and security. Chun received his PhD in Computer Science from the University of California, Berkeley. Prior to joining Seoul National University, Chun was a principal scientist at Microsoft, a research scientist at Yahoo! Research and Intel Research, and a postdoctoral researcher at ICSI.\r\n\r\n
\r\n\r\nDiego Fern\u00e1ndez Slezak<\/h3>\r\nAssistant Professor, Department of Computer Science\r\n\r\nUniversity of Buenos Aires\r\n\r\nDiego Fern\u00e1ndez Slezak's work focuses on novel methods for text analysis in massive-scale repositories to find stereotyped patterns in human thought. The goal is the development and use of machine-learning techniques to study digital text corpora associated with cognitive processes, aiming at identifying the mental operations underlying behavioral processes, with application to mental health and education. Diego Fern\u00e1ndez Slezak received his PhD in Computer Science in 2010 from University of Buenos Aires and was recipient of the IBM PhD Fellowship.\r\n\r\n
\r\n\r\nRoxana Geambasu<\/h3>\r\nAssistant Professor, Computer Science Department\r\n\r\nColumbia University\r\n\r\nRoxana Geambasu works at the intersection of three computer science fields: distributed systems, operating systems, and security and privacy. Her research aims to increase privacy in today\u2019s data-driven world. Privacy has become a rare commodity in today\u2019s world, due to users who are too eager to share their data online and Web services that aggressively collect and use that information. Roxana\u2019s goal is to forge a new world, in which Web services are designed from the ground up with privacy in mind, and where users are more aware of the privacy implications of their online actions. Roxana obtained her Ph.D. from the University of Washington and was awarded a 2014 NSF CAREER award, an Honorable Mention for the 2013 inaugural Dennis M. Ritchie Doctoral Dissertation Award, a William Chan Memorial Dissertation Award, two best paper awards, and a 2013 Google Faculty Research Award.\r\n\r\n
\r\n\r\nPercy Liang<\/h3>\r\nAssistant Professor, Computer Science Department\r\n\r\nStanford University\r\n\r\nPercy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His research interests include (i) parsing natural language into semantic representations (e.g., executable code), for supporting intelligent user interfaces; and (ii) developing machine learning algorithms that infer rich latent structures (e.g., programs) from limited supervision (e.g., program output), balancing computational and statistical tradeoffs. He won a best student paper at the International Conference on Machine Learning in 2008, received the NSF, GAANN, and NDSEG fellowships, and is also a 2010 Siebel Scholar.\r\n\r\n
\r\n\r\nDavid Steurer<\/h3>\r\nAssistant Professor, Department of Computer Science\r\n\r\nCornell University\r\n\r\nDavid Steurer investigates the power and limitations of efficient algorithms for optimization problems that are at the heart of computer science and its applications. A focus of his work has been the Unique Games Conjectures whose resolution\u2014no matter in which direction\u2014promises new insights into the capabilities of efficient algorithms. As part of the research effort to resolve this conjecture, he studies provable guarantees of the sum-of-squares method, a compelling meta-algorithm that applies to a wide-range of problems and has the potential to unify the design of efficient algorithms for difficult optimization problems. Steurer received his PhD from Princeton University and was a postdoctoral researcher at Microsoft Research for two years before joining Cornell University. He is the recipient of the 2010 FOCS best paper award, the 2011 ACM Doctoral Dissertation Award Honorable Mention, an NSF CAREER Award, and an Alfred P. Sloan Research Fellowship.\r\n\r\n
\r\n\r\nVinod Vaikuntanathan<\/h3>\r\nAssistant Professor, Electrical Engineering and Computer Science Department\r\n\r\nMassachusetts Institute of Technology\r\n\r\nVinod Vaikuntanathan is a Steven and Renee Finn Career Development Assistant Professor of Computer Science at MIT. His main research interest is in the theory and practice of cryptography. He works on lattice-based cryptography, building advanced cryptographic primitives using integer lattices; leakage-resilient cryptography, defining and developing algorithms resilient against adversarial information leakage; and more recently, the theory and practice of computing on encrypted data, constructing powerful cryptographic objects such as fully homomorphic encryption and functional encryption. Vinod got his Ph.D. from MIT where he received a 2009 George M. Sprowls Award for the best MIT Ph.D. thesis in Computer Science. He is also a recipient of the 2008 IBM Josef Raviv Postdoctoral Fellowship, the 2009, the 2013 Alfred P. Sloan Research Fellowship, and a 2014 NSF CAREER award.\r\n\r\n[\/panel]\r\n[panel header=\"2013 Faculty Fellows\"]\r\nAnimashree Anandkumar<\/h3>\r\nAssistant Professor, Department of Electrical Engineering and Computer Science\r\n\r\nUniversity of California, Irvine\r\n\r\nAnimashree Anandkumar\u2019s research lies at the interface of theory and practice of large-scale machine learning and high dimensional statistics. Her theoretical contributions include analysis of high-dimensional estimation of graphical models and developing tensor methods for learning latent variable models. She has applied the developed algorithms to various problems in social networks and computational biology. She is currently an assistant professor at the Department of Electrical Engineering and Computer Science at the University of California, Irvine. She spent a year as a postdoctoral researcher at MIT and got her PhD from Cornell University. She has been a visiting researcher at Microsoft Research New England. She is the recipient of the ARO Young Investigator Award, NSF CAREER Award, IBM Fran Allen PhD fellowship, and several paper awards.\r\n\r\n
\r\n\r\nKatrina Ligett<\/h3>\r\nAssistant Professor, Computer Science and Economics\r\n\r\nCalifornia Institute of Technology\r\n\r\nKatrina Ligett is an assistant professor of Computer Science and Economics at Caltech. In her research, she develops theoretical tools to address problems in data privacy and to understand individual incentives in other complex settings. She received her PhD from Carnegie Mellon University in 2009 and was a postdoctoral fellow at Cornell University before joining the California Institute of Technology in 2011. She is a recipient of the AT&T Labs Graduate Research Fellowship, the NSF Graduate Research Fellowship, the CIFellows Postdoctoral Research Fellowship, the NSF Mathematical Sciences Postdoctoral Research Fellowship, and an NSF CAREER award.\r\n\r\n
\r\n\r\nMichael Milford<\/h3>\r\nSenior Lecturer, School of Electrical Engineering and Computer Science\r\n\r\nQueensland University of Technology\r\n\r\nMichael Milford\u2019s research investigates how robots and biological systems map and navigate the world. He builds computational models based on experimental results and theories from the fields of neuroscience and biology and deploys them on robotic systems navigating in challenging real world environments. This novel research methodology has produced state-of-the-art results in robotics and yielded insights into how the brain may map and navigate the world. Milford received his PhD from the University of Queensland in 2006 and is the recipient of an Australian Research Council DECRA Fellowship and Discovery Project award.\r\n\r\n
\r\n\r\nRuslan Salakhutdinov<\/h3>\r\nAssistant Professor, Department of Statistics and Computer Science\r\n\r\nUniversity of Toronto\r\n\r\nRuslan Salakhutdinov received his PhD in computer science from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an assistant professor in the departments of Statistics and Computer Science. His primary interests lie in artificial intelligence, machine learning, deep learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data. He is an action editor of the Journal of Machine Learning Research<\/em> and served on the senior programme committee of several learning conferences, including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, a recipient of the Early Researcher Award and Connaught New Researcher Award, and is a Scholar of the Canadian Institute for Advanced Research.\r\n\r\n
\r\n\r\nMichael Schapira<\/h3>\r\nSenior Lecturer, School of Computer Science and Engineering\r\n\r\nHebrew University of Jerusalem\r\n\r\nMichael Schapira\u2019s research draws ideas from algorithmic and economic theory to design practical Internet protocols with provable guarantees (for example, for routing and traffic management). His research aims to both \u201cfix\u201d\u2019 today\u2019s Internet protocols and to design new and improved (better performing, secure, failure-resilient, and so forth) protocols for the future Internet. Schapira also has a broad research interest in the interface of computer science, game theory, and economics. He is a recipient of the Allon Fellowship (2011) and a member of the Israeli Center of Research Excellence in Algorithms. Prior to joining Hebrew University, Schapira was a postdoctoral researcher at the University of California, Berkeley, Yale University, and Princeton University, and a visiting scientist in Google New York\u2019s Infrastructure Networking group.\r\n\r\n
\r\n\r\nMonica Tentori<\/h3>\r\nAssistant Professor, Department of Computer Science\r\n\r\nCenter for Scientific Research and Higher Education (CICESE)\r\n\r\nMonica Tentori investigates the human experience of ubiquitous computing to inform the design of ubiquitous environments that effectively enhance humans\u2019 interactions with their world. Her research intersecting human-computer interaction and ubiquitous computing particularly focuses on designing, developing, and evaluating natural user interfaces, self-reflection capture tools, and new interaction models for ubiquitous computing. Her work is being applied to healthcare and urban living to support the needs of urban citizens, hospital workers, elders, and individuals with autism and their caregivers. Tentori\u2019s research demonstrates that effectively designed ubiquitous environments have the potential to promote healthy lifestyles and independence, and positively impact attention, behavior, and workload.\r\n\r\n
\r\n\r\nRyan Williams<\/h3>\r\nAssistant Professor, Computer Science Department\r\n\r\nStanford University\r\n\r\nRyan Williams works in algorithm design and complexity theory. He studies how to construct more efficient algorithms for solving computational problems, as well as how to mathematically rule out the possibility of efficient algorithms for other problems. Such impossibility results are generally perceived as very difficult; algorithms can be very clever, and it is hard to reason about all cleverness one could have. The famous P versus NP question asks about the power of efficient algorithms. Williams\u2019 work shows how the design and analysis of algorithms for core problems in computer science can often be exploited to rule out efficient algorithms for other core problems, raising new questions about our understanding of efficient computation. Williams received his PhD from Carnegie Mellon University in 2007 under Manuel Blum. His honors include some best paper awards and an Alfred P. Sloan Fellowship.\r\n\r\n[\/panel]\r\n[panel header=\"2012 Faculty Fellows\"]\r\nEmma Brunskill<\/h3>\r\nAssistant Professor, Department of Computer Science\r\n\r\nCarnegie Mellon University\r\n\r\nEmma Brunskill\u2019s research focuses on creating automated decision systems that interact with people, a challenge that spans artificial intelligence, machine learning, and human-computer interaction. She is particularly interested in adaptive, individualized tutoring systems that learn and self-optimize. Emma also works on health applications and on using information communication technologies to address challenges in low resource settings and developing regions.\r\n\r\n
\r\n\r\nConstantinos Daskalakis<\/h3>\r\nAssistant Professor, Department of Electrical Engineering and Computer Science\r\n\r\nMassachusetts Institute of Technology\r\n\r\nConstantinos Daskalakis is the X Consortium Assistant Professor of Computer Science at MIT. His research studies the interface of computer science and economics, with a focus on computational aspects of the Internet, online markets, and social networks. Daskalakis has been honored with the 2007 Microsoft Graduate Research Fellowship, the 2008 ACM Doctoral Dissertation Award, the 2010 Sloan Fellowship, the 2011 SIAM Outstanding Paper Prize, and the MIT Ruth and Joel Spira Award for Distinguished Teaching. His work on the complexity of the Nash equilibrium was honored by the Game Theory Society with the First Computer Science and Game Theory prize. Daskalakis received his PhD in Computer Science from UC Berkeley and was a post-doctoral researcher at Microsoft Research prior to joining MIT.\r\n\r\n
\r\n\r\nStephen Gould<\/h3>\r\nSenior Lecturer, School of Computer Science\r\n\r\nAustralian National University\r\n\r\nStephen Gould is a faculty member in the Research School of Computer Science at the Australian National University. He received his PhD from Stanford University in 2010. Prior to his PhD, Stephen founded and worked in a number of start-up companies. Stephen\u2019s current research interests are in developing mathematical models that allow computers to learn how to interpret scenes from images. This involves recognizing objects and understanding how they interact with other objects and with their environment.\r\n\r\n
\r\n\r\nAndreas Krause<\/h3>\r\nAssistant Professor, Department of Computer Science\r\n\r\nETH Zurich\r\n\r\nAndreas Krause\u2019s research is in learning and adaptive systems that actively acquire information; reason; and make decisions in large, distributed, and uncertain domains, such as sensor networks and the web. It spans theoretical aspects in machine learning and optimization, as well as interdisciplinary applications, ranging from community sensing to computational sustainability to social networks. He got his PhD in Computer Science from Carnegie Mellon University in 2008. He is a Kavli Frontiers Fellow of the U.S. National Academy of Sciences, and received an NSF CAREER award as well as several best paper awards.\r\n\r\n
\r\n\r\nMiriah Meyer<\/h3>\r\nAssistant Professor, School of Computing\r\n\r\nUniversity of Utah\r\n\r\nMiriah Meyer\u2019s research lives at the interface of computer science and data-intensive domains, where she designs interactive visualization systems that help scientists make sense of complex data. Her current work focuses on nimble and intuitive visualization tools that support research in genomics and molecular biology. Meyer takes a user-centered, problem-driven approach to developing visualizations that target specific scientific questions, working closely with scientists in an iterative and collaborative process. Her tools are integrated into the workflow of numerous biological labs and have led to several scientific discoveries, as well as to the validation and refinement of experimental and computational methods.\r\n\r\n
\r\n\r\nJuan Carlos Niebles<\/h3>\r\nAssistant Professor, Electrical and Electronic Engineering\r\n\r\nUniversidad del Norte\r\n\r\nJuan Carlos is interested in helping computers and robots see the world. In particular, his research is focused on designing novel algorithms for automatic recognition and detailed understanding of human motions, activities, and behaviors from images and videos. This technology has the potential to enable new life-improving activity-aware systems, such as personal robots and smart homes, smart video surveillance, medical diagnosis and monitoring, automated sports analysis, and semantic video search.\r\n\r\n
\r\n\r\nAshutosh Saxena<\/h3>\r\nAssistant Professor, Department of Computer Science\r\n\r\nCornell University\r\n\r\nAshutosh Saxena works on a new generation of robots that will operate fully autonomously in human environments. His research is focused on the development of new machine-learning algorithms that enable robots to process massive amounts of sensory input data in real time and learn how to perform tasks in unstructured environments. His primary application domain is in assistive robotics, where his algorithms have enabled robots to perform tasks such as fetching items on verbal request, perform basic household chores, and identify and assist in human activities. He hopes to see such assistive robots appear in our homes, offices, and nursing homes soon.\r\n\r\n[\/panel]\r\n[panel header=\"2011 Faculty Fellows\"]\r\nMaria Florina Balcan<\/h3>\r\nAssistant Professor, School of Computer Science\r\n\r\nGeorgia Institute of Technology\r\n\r\nMaria Florina Balcan is an assistant professor in the School of Computer Science at Georgia Institute of Technology. She received her PhD in Computer Science from Carnegie Mellon University under the supervision of Avrim Blum. From October 2008 until July 2009, she was a postdoc at Microsoft Research, New England. Her main research interests are computational and statistical machine learning, computational aspects in economics and game theory, and algorithms. She is a recipient of the Carnegie Mellon University SCS Distinguished Dissertation Award and the National Science Foundation NSF CAREER Award.\r\n\r\n
\r\n\r\nKrishnendu Chatterjee<\/h3>\r\nAssistant Professor\r\n\r\nInstitute of Science and Technology Austria\r\n\r\nKrishnendu is interested in graph games that arise in the formal verification of systems, and has deep connections with logic and automata theory. He established many fundamental results related to stochastic games on graphs, and is currently working on quantitative graph games and its application to synthesis of correct systems. He got his PhD from University of California, Berkeley in 2007, and his thesis won the David Sakrison Memorial Prize and Ackermann Award.\r\n\r\n
\r\n\r\nJure Leskovec<\/h3>\r\nAssistant Professor, Department of Computer Science\r\n\r\nStanford University\r\n\r\nJure Leskovec is an assistant professor of Computer Science at Stanford University. His research focuses on the analysis and modeling of large social and information networks as the study of phenomena across the social, technological, and natural worlds. Problems he investigates are motivated by large scale data, the Web and Social Media. Jure received his PhD in Machine Learning from Carnegie Mellon University in 2008 and spent a year at Cornell University. His work received six best paper awards, won the ACM KDD cup and topped the Battle of the Sensor Networks competition.\r\n\r\n
\r\n\r\nAlistair McEwan<\/h3>\r\nLecturer of Computer Engineering, School of Electrical and Information Engineering\r\n\r\nThe University of Sydney\r\n\r\nAlistair McEwan\u2019s work aims to solve major health issues with technology, and involves research in the emerging field of bioelectronics\u2014the interaction between electronics and biology. His current investigation of the electrode\u2013skin interface aims to improve emergency diagnosis of heart attack and stroke as well as long-term monitoring of cardiovascular disease. He also works on related projects in electrical-impedance imaging systems, microelectronic circuits and systems, and neuromorphic engineering.\r\n\r\n
\r\n\r\nShwetak Patel<\/h3>\r\nAssistant Professor, Departments of Computer Science and Electrical Engineering\r\n\r\nUniversity of Washington\r\n\r\nShwetak Patel\u2019s research is at the intersection of hardware, software, and human-computer interaction. His research focuses on building easy-to-deploy and practical sensing systems for the home. His work is being applied to sustainability, elder care, home safety, and the creation of new approaches for natural user interfaces. Many of his techniques use the existing utilities infrastructure as a \u201csensor,\u201d thereby reducing the need for additional instrumentation. In one example, Patel has developed techniques for energy and water monitoring that provide a detailed breakdown of consumption in the home through monitoring a single point on the utility infrastructure. Through these new sensing approaches, Patel envisions the ability to instrument homes easily with smart technology for high-value applications.\r\n\r\n
\r\n\r\nAnderson de Rezende Rocha<\/h3>\r\nAssistant Professor, Institute of Computing\r\n\r\nUniversity of Campinas\r\n\r\nProfessor Rocha\u2019s research interests include digital image and video forensics, computer vision, pattern analysis, and machine intelligence\u2014focused on the field of digital document forensics. He seeks solutions for problems regarding collection, organization, and classification of digital evidence that is used by law enforcement agencies in Brazil and abroad. He is investigating how to reduce the misuse of important evidence and is working on digital categorization solutions to reduce the technical effort that is required to analyze each piece of evidence. Professor Rocha\u2019s work emphasizes tracking the source of the evidence, new techniques for establishing authenticity, and exposing possible tampering.\r\n\r\n
\r\n\r\nKeith Noah Snavely<\/h3>\r\nAssistant Professor, Computer Science Department\r\n\r\nCornell University\r\n\r\nNoah Snavely is interested in using massive collections of images on the web to better understand and visualize our world. His research builds new computer-vision algorithms for scalable 3-D reconstruction, new graphics techniques for experiencing places through online photos, and new ways to enable communities of photographers to capture useful image collections. His software is being used by educators, artists, and scientists across a range of disciplines.\r\n\r\n
\r\n\r\nBrent Waters<\/h3>\r\nAssistant Professor, Department of Computer Sciences\r\n\r\nUniversity of Texas\r\n\r\nBrent Waters studies cryptography and computer security. His research is laying the foundations for a new vision of encryption called Functional Encryption. Instead of encrypting to individual users, in a Functional Encryption system, one can embed any access predicate into the cipher text itself. In addition, he is interested in understanding the foundational underpinnings of cryptography and in developing security primitives that are both practical and provably secure.\r\n\r\n[\/panel]\r\n[panel header=\"2010 Faculty Fellows\"]\r\nSinan Aral<\/h3>\r\nDepartment of Information, Operations, and Management Sciences\r\n\r\nNew York University Stern School of Business\r\n\r\n
\r\n\r\nDoug Downey<\/h3>\r\nDepartment of Electrical Engineering and Computer Science\r\n\r\nNorthwestern University\r\n\r\n
\r\n\r\nRaanan Fattal<\/h3>\r\nSchool of Computer Science and Engineering\r\n\r\nThe Hebrew University of Jerusalem\r\n\r\n
\r\n\r\nabhi shelat<\/h3>\r\nDepartment of Computer Science\r\n\r\nUniversity of Virginia\r\n\r\n
\r\n\r\nHaiying Shen<\/h3>\r\nDepartment of Electrical and Computer Engineering\r\n\r\nClemson University\r\n\r\n
\r\n\r\nCyrill Stachniss<\/h3>\r\nDepartment of Computer Science\r\n\r\nUniversity of Freiburg, Germany\r\n\r\n
\r\n\r\nEvimaria Terzi<\/h3>\r\nComputer Science Department\r\n\r\nBoston University\r\n\r\n[\/panel]\r\n[panel header=\"2009 Faculty Fellows\"]\r\nGill Bejerano<\/h3>\r\nDevelopmental Biology and Computer Science\r\n\r\nStanford University\r\n\r\n
\r\n\r\nLuis Ceze<\/h3>\r\nComputer Science and Engineering\r\n\r\nUniversity of Washington\r\n\r\n
\r\n\r\nNicole Immorlica<\/h3>\r\nElectrical Engineering and Computer Science Department\r\n\r\nNorthwestern University, McCormick School of Engineering\r\n\r\n
\r\n\r\nSvetlana Lazebnik<\/h3>\r\nDepartment of Computer Science\r\n\r\nUniversity of North Carolina at Chapel Hill\r\n\r\n
\r\n\r\nRafael Pass<\/h3>\r\nDepartment of Computer Science\r\n\r\nCornell University\r\n\r\n[\/panel]\r\n[panel header=\"2008 Faculty Fellows\"]\r\nKristen Grauman<\/h3>\r\nComputer Sciences\r\n\r\nUniversity of Texas at Austin\r\n\r\n
\r\n\r\nSusan Hohenberger<\/h3>\r\nDepartment of Computer Science\r\n\r\nJohns Hopkins University\r\n\r\n
\r\n\r\nRobert Kleinberg<\/h3>\r\nComputer Science\r\n\r\nCornell University\r\n\r\n
\r\n\r\nPhilip Levis<\/h3>\r\nDepartments of Computer Science and Engineering\r\n\r\nStanford University\r\n\r\n
\r\n\r\nKaren Lipkow<\/h3>\r\nDepartment of Biochemistry\r\n\r\nUniversity of Cambridge\r\n\r\n
\r\n\r\nRussell Tedrake<\/h3>\r\nElectrical Engineering and Computer Science\r\n\r\nMassachusetts Institute of Technology\r\n\r\n[\/panel]\r\n[panel header=\"2007 Faculty Fellows\"]\r\nMagdalena Balazinska<\/h3>\r\nDepartment of Computer Science and Engineering\r\n\r\nUniversity of Washington\r\n\r\n
\r\n\r\nJosh Bongard<\/h3>\r\nDepartment of Computer Science\r\n\r\nUniversity of Vermont\r\n\r\n
\r\n\r\nYixin Chen<\/h3>\r\nDepartment of Computer Science and Engineering\r\n\r\nWashington University in St. Louis\r\n\r\n
\r\n\r\nAdam Siepel<\/h3>\r\nBiological Statistics and Computational Biology\r\n\r\nCornell University\r\n\r\n
\r\n\r\nLuis von Ahn<\/h3>\r\nDepartment of Computer Science\r\n\r\nCarnegie Mellon University\r\n\r\n[\/panel]\r\n[panel header=\"2006 Faculty Fellows\"]\r\nRegina Barzilay<\/h3>\r\nComputer Science and Artificial Intelligence\r\n\r\nMassachusetts Institute of Technology\r\n\r\n
\r\n\r\nAaron Hertzmann<\/h3>\r\nComputer Science\r\n\r\nUniversity of Toronto\r\n\r\n
\r\n\r\nScott Klemmer<\/h3>\r\nComputer Science\r\n\r\nStanford University\r\n\r\n
\r\n\r\n
- Add the contact information (name, affiliation, email) and send the email request through the submission portal to your three recommenders as soon as possible so they have ample time to provide a letter. Their deadline is the same as your proposal deadline on Monday, March 29, 2021<\/strong>. They should be established researchers familiar with your research. Once you send the request through the submission portal, they will receive a private link to upload a letter of recommendation for you. Please note that you and your recommenders may need to check your junk folders in order to find emails from our portal. As reference, here is a list of the various system email addresses<\/a> you can add to allowed emails.<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\nProposals submitted to Microsoft will not be returned. Microsoft cannot assume responsibility for the confidentiality of information in submitted proposals. Therefore, proposals should not contain information that is confidential, restricted, or sensitive. Microsoft reserves the right to make public the information on those proposals that receive awards, except those portions containing budgetary or personally identifiable information.\r\n\r\nIncomplete proposals will not be considered.\r\n\r\nDue to the volume of submissions, Microsoft cannot provide individual feedback on proposals."},{"id":3,"name":"FAQ","content":"Below are the answers to frequently asked questions about the 2021 Microsoft Research Faculty Fellowship.\r\n
- Two-page statement of research to include: your major research initiatives, what makes your approaches especially innovative, and how you would use the funding and the impact it would have on your research; a paragraph describing how you support the mission of fostering diversity and inclusive cultures within your student and researcher communities and how you plan to in the future; we suggest a font no smaller than 10-point and references should be included as part of the two pages - file name: research<\/strong><\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\nYou will be asked to request 3 letters of recommendation via the submission portal:\r\n
- Curriculum vitae \u2013 file name: cv<\/strong><\/li>\r\n \t
- Recipients announced by early July 2021<\/li>\r\n<\/ul>\r\n
- Two-page statement of research to include: your major research initiatives, what makes your approaches especially innovative, and how you would use the funding and the impact it would have on your research; a paragraph describing how you support the mission of fostering diversity and inclusive cultures within your student and researcher communities and how you plan to in the future; we suggest a font no smaller than 10-point and references should be included as part of the two pages \u2013 file name: research<\/strong><\/li>\n<\/ul>\n\n\n\n
- Recipients announced by early July 2021<\/li>\n<\/ul>\n\n\n\n