Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Y. Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart
ICLR 2024 | September 2023
Amit Sharma
Principal Researcher
Publications
Publications by Year
-
Towards Modular Machine Learning Pipelines
Aditya Modi, Jivat Neet Kaur, Maggie Makar, Pavan Mallapragada, Amit Sharma, Emre Kiciman, Adith Swaminathan
2023 International Conference on Machine Learning | July 2023
Combinatorial categorized bandits with expert rankings
Gaurav Sinha, Sayak Ray Chowdhury, Nagarajan Natarajan, Amit Sharma
UAI | July 2023
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
Jivat Neet Kaur, Emre Kiciman, Amit Sharma
International Conference on Learning Representations (ICLR) | January 2023
Notable Top-25% of accepted papers
-
A Causal AI Suite for Decision-Making
Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang
NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022
Counterfactual Generation Under Confounding
Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
The Counterfactual-Shapley Value: Attributing Change in System Metrics
Amit Sharma, Hua Li, Jian Jiao
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems
Parikshit Bansal, Yashoteja Prabhu, Emre Kiciman, Amit Sharma
NeurIPS 2022 Workshop on Distribution Shifts (DistShift) | November 2022
Probing Classifiers are Unreliable for Concept Removal and Detection
Abhinav Kumar, Chenhao Tan, Amit Sharma
2022 Neural Information Processing Systems | October 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
ICML 2022 | July 2022
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman (emrek), Amit Sharma, Martin Kukla, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
MSR-TR-2022-1 | February 2022
Published by Microsoft
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals
Saloni Dash, Vineeth Balasubramanian, Amit Sharma
Winter Conference on Applications of Computer Vision (WACV) | January 2022
-
MINDNOTES: A Mobile Platform to enable users to break stigma around mental health and connect with therapists
Prateek Chanda, Amogh Wagh, Jemimah A Johnson, Swaraj Renghe, Vageesh D C, George Mathews, Sapna Behar, Poornima Bhola, Girish Rao, Paulomi Sudhir, T K Srikanth, Amit Sharma, Seema Mehrotra
October 2021
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
Amit Sharma, Cheng Zhang, Vasilis Syrgkanis, Emre Kiciman
MSR-TR-2021-15 | July 2021
Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
AAAI/ACM Conference on AI, Ethics, and Society (AIES) | April 2021
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman
ACM Intl. Conf. on Web Search and Data Mining (WSDM) | March 2021
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayeulas, Amit Deshpande, Amit Sharma
AAAI Conference on Artificial Intelligence (AAAI) | February 2021
-
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
DoWhy: An End-to-End Library for Causal Inference
November 2020
Causal Data Science Meeting (https://causalscience.org/)
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Amit Sharma, Koustuv Saha
Proceedings of the 14th International AAAI Conference on Web and Social Media (ICWSM) | August 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Koustuv Saha, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms
Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Inframarginality Audit of Group-Fairness
Amit Sharma, Arpita Biswas, Siddharth Barman
June 2020
Using Mobile Airtime Credits to Incentivize Learning, Sharing and Survey Response: Experiences from the Field
Devansh Mehta, Ramaravind K. Mothilal, Alok Sharma, Bill Thies, Amit Sharma
ACM COMPASS: Conference on Computing and Sustainable Societies | June 2020
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi
Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava, Alok Sharma, Anurag Shukla, Vishnu Prasad, Venkanna U, Amit Sharma, Kalika Bali
Language Resources and Evaluation Conference (LREC) | May 2020
“Like Shock Absorbers”: Understanding the Human Infrastructures of Technology-Mediated Mental Health Support
Sachin Pendse, Faisal Lalani, Munmun De Choudhury, Amit Sharma, Neha Kumar
ACM CHI Conference on Human Factors in Computing Systems | April 2020
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums
Taisa Kushner, Amit Sharma
ACM Web Conference (WWW) | April 2020
Facilitating Media Distribution With Monetary Incentives
Devansh Mehta, Alok Sharma, Ramaravind K. Kommiya Mothilal, Chiraag, Anurag Shukla, Vishnu Prasad, Bill Thies, Venkanna U, Colin Scott, Amit Sharma
2020 CHI Conference on Human Factors in Computing Systems | April 2020
Barriers to Professional Help-seeking for Distress and Potential Utility of a Mental Health App: Stakeholder Perspectives
Jemimah Johnson, Janhavi Devdutt, Seema Mehrotra, Poornima Bhola, Paulomi Sudhir, Amit Sharma
Cureus Journal of Medical Science | February 2020
Explaining Machine Learning Classifiers through Diverse Counterfactual Examples
Ramaravind K. Mothilal, Amit Sharma, Chenhao Tan
ACM Conference on Fairness, Accountability, and Transparency | January 2020
-
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
Divyat Mahajan, Chenhao Tan, Amit Sharma
CausalML: Machine Learning and Causal Inference for Improved Decision Making Workshop, NeurIPS 2019 | December 2019
Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness
Ramaravind Kommiya Mothilal, Devansh Mehta, Alok Sharma, Bill Thies, Amit Sharma
November 2019
Cross-Cultural Differences in the Use of Online Mental Health Support Forums
Sachin R. Pendse, Kate Niederhoffer, Amit Sharma
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns
Saiganesh Swaminathan, Indrani Medhi Thies, Devansh Mehta, Ed Cutrell, Amit Sharma, Bill Thies (thies)
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Best of CSCW honorable mention
Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention
John A. Naslund, Pattie P. Gonsalves, Oliver Gruebner, Sachin R. Pendse, Stephanie L. Smith, Amit Sharma, Giuseppe Raviola
Current Treatment Options in Psychiatry | September 2019
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
Jackson Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | August 2019
Learnings from deploying a voice-based social platform for people with disability
Karn Dubey, Palash Gupta, Rachna Shriwas, Gayatri Gulvady, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Mental health in the global south: Challenges and opportunities in HCI for development
Sachin R. Pendse, Naveena Karusala, Divya Siddarth, Pattie Gonsalves, Seema Mehrotra, John A. Naslund, Mamta Sood, Neha Kumar, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Optimizing peer referrals for public awareness using contextual bandits
Ramaravind K. Mothilal, Amulya Yadav, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums
Yada Pruksachatkun, Sachin Pendse, Amit Sharma
2019 CHI Conference on Human Factors in Computing Systems | May 2019
Predicting History
Joseph Risi, Amit Sharma, Rohan Shah, Matthew Connelly, Duncan J. Watts
Nature Human Behavior | April 2019
-
Necessary and Probably Sufficient Test for Finding Valid Instrumental Variables
December 2018
Split-door criterion: Identification of causal effects through auxiliary outcomes
Amit Sharma, Jake Hofman, Duncan Watts
Annals of Applied Statistics | December 2018, Vol 12(4): pp. 2699-2733
Tutorial on Causal Inference and Counterfactual Reasoning
ACM KDD International Conference on Knowledge Discovery and Data Mining | August 2018
-
Harvesting Randomness to Optimize Distributed Systems
Mathias Lecuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins
16th ACM Workshop on Hot Topics in Networks (HotNets) | November 2017
Auditing Search Engines for Differential Satisfaction Across Demographics
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna Wallach, Emine Yilmaz
Proceedings of the 26th International Conference on World Wide Web (Industry Track) | April 2017
Prediction and explanation in social systems
Jake Hofman, Amit Sharma, Duncan Watts
Science | February 2017, Vol 355: pp. 486-488
-
Exploring Limits to Prediction in Complex Social Systems: Predicting Cascade Size on Twitter
Travis Martin, Jake Hofman, Amit Sharma, Ashton Anderson, Duncan Watts
Proceedings of the 25th International Conference on World Wide Web | April 2016
-
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
Publications by Research Area
-
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Y. Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart
ICLR 2024 | September 2023
Towards Modular Machine Learning Pipelines
Aditya Modi, Jivat Neet Kaur, Maggie Makar, Pavan Mallapragada, Amit Sharma, Emre Kiciman, Adith Swaminathan
2023 International Conference on Machine Learning | July 2023
Combinatorial categorized bandits with expert rankings
Gaurav Sinha, Sayak Ray Chowdhury, Nagarajan Natarajan, Amit Sharma
UAI | July 2023
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
Jivat Neet Kaur, Emre Kiciman, Amit Sharma
International Conference on Learning Representations (ICLR) | January 2023
Notable Top-25% of accepted papers
A Causal AI Suite for Decision-Making
Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang
NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022
Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems
Parikshit Bansal, Yashoteja Prabhu, Emre Kiciman, Amit Sharma
NeurIPS 2022 Workshop on Distribution Shifts (DistShift) | November 2022
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
The Counterfactual-Shapley Value: Attributing Change in System Metrics
Amit Sharma, Hua Li, Jian Jiao
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Probing Classifiers are Unreliable for Concept Removal and Detection
Abhinav Kumar, Chenhao Tan, Amit Sharma
2022 Neural Information Processing Systems | October 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
ICML 2022 | July 2022
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman (emrek), Amit Sharma, Martin Kukla, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
MSR-TR-2022-1 | February 2022
Published by Microsoft
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals
Saloni Dash, Vineeth Balasubramanian, Amit Sharma
Winter Conference on Applications of Computer Vision (WACV) | January 2022
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
Amit Sharma, Cheng Zhang, Vasilis Syrgkanis, Emre Kiciman
MSR-TR-2021-15 | July 2021
Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
AAAI/ACM Conference on AI, Ethics, and Society (AIES) | April 2021
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman
ACM Intl. Conf. on Web Search and Data Mining (WSDM) | March 2021
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayeulas, Amit Deshpande, Amit Sharma
AAAI Conference on Artificial Intelligence (AAAI) | February 2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
DoWhy: An End-to-End Library for Causal Inference
November 2020
Causal Data Science Meeting (https://causalscience.org/)
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Amit Sharma, Koustuv Saha
Proceedings of the 14th International AAAI Conference on Web and Social Media (ICWSM) | August 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
Inframarginality Audit of Group-Fairness
Amit Sharma, Arpita Biswas, Siddharth Barman
June 2020
Explaining Machine Learning Classifiers through Diverse Counterfactual Examples
Ramaravind K. Mothilal, Amit Sharma, Chenhao Tan
ACM Conference on Fairness, Accountability, and Transparency | January 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
Divyat Mahajan, Chenhao Tan, Amit Sharma
CausalML: Machine Learning and Causal Inference for Improved Decision Making Workshop, NeurIPS 2019 | December 2019
Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness
Ramaravind Kommiya Mothilal, Devansh Mehta, Alok Sharma, Bill Thies, Amit Sharma
November 2019
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
Jackson Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | August 2019
Optimizing peer referrals for public awareness using contextual bandits
Ramaravind K. Mothilal, Amulya Yadav, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Predicting History
Joseph Risi, Amit Sharma, Rohan Shah, Matthew Connelly, Duncan J. Watts
Nature Human Behavior | April 2019
Necessary and Probably Sufficient Test for Finding Valid Instrumental Variables
December 2018
Split-door criterion: Identification of causal effects through auxiliary outcomes
Amit Sharma, Jake Hofman, Duncan Watts
Annals of Applied Statistics | December 2018, Vol 12(4): pp. 2699-2733
Tutorial on Causal Inference and Counterfactual Reasoning
ACM KDD International Conference on Knowledge Discovery and Data Mining | August 2018
-
Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems
Parikshit Bansal, Yashoteja Prabhu, Emre Kiciman, Amit Sharma
NeurIPS 2022 Workshop on Distribution Shifts (DistShift) | November 2022
Auditing Search Engines for Differential Satisfaction Across Demographics
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna Wallach, Emine Yilmaz
Proceedings of the 26th International Conference on World Wide Web (Industry Track) | April 2017
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
-
Counterfactual Generation Under Confounding
Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Amit Sharma, Koustuv Saha
Proceedings of the 14th International AAAI Conference on Web and Social Media (ICWSM) | August 2020
Cross-Cultural Differences in the Use of Online Mental Health Support Forums
Sachin R. Pendse, Kate Niederhoffer, Amit Sharma
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns
Saiganesh Swaminathan, Indrani Medhi Thies, Devansh Mehta, Ed Cutrell, Amit Sharma, Bill Thies (thies)
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Best of CSCW honorable mention
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
-
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Amit Sharma, Koustuv Saha
Proceedings of the 14th International AAAI Conference on Web and Social Media (ICWSM) | August 2020
Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms
Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Koustuv Saha, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums
Taisa Kushner, Amit Sharma
ACM Web Conference (WWW) | April 2020
“Like Shock Absorbers”: Understanding the Human Infrastructures of Technology-Mediated Mental Health Support
Sachin Pendse, Faisal Lalani, Munmun De Choudhury, Amit Sharma, Neha Kumar
ACM CHI Conference on Human Factors in Computing Systems | April 2020
Barriers to Professional Help-seeking for Distress and Potential Utility of a Mental Health App: Stakeholder Perspectives
Jemimah Johnson, Janhavi Devdutt, Seema Mehrotra, Poornima Bhola, Paulomi Sudhir, Amit Sharma
Cureus Journal of Medical Science | February 2020
Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention
John A. Naslund, Pattie P. Gonsalves, Oliver Gruebner, Sachin R. Pendse, Stephanie L. Smith, Amit Sharma, Giuseppe Raviola
Current Treatment Options in Psychiatry | September 2019
Mental health in the global south: Challenges and opportunities in HCI for development
Sachin R. Pendse, Naveena Karusala, Divya Siddarth, Pattie Gonsalves, Seema Mehrotra, John A. Naslund, Mamta Sood, Neha Kumar, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums
Yada Pruksachatkun, Sachin Pendse, Amit Sharma
2019 CHI Conference on Human Factors in Computing Systems | May 2019
-
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Amit Sharma, Koustuv Saha
Proceedings of the 14th International AAAI Conference on Web and Social Media (ICWSM) | August 2020
Using Mobile Airtime Credits to Incentivize Learning, Sharing and Survey Response: Experiences from the Field
Devansh Mehta, Ramaravind K. Mothilal, Alok Sharma, Bill Thies, Amit Sharma
ACM COMPASS: Conference on Computing and Sustainable Societies | June 2020
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi
Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava, Alok Sharma, Anurag Shukla, Vishnu Prasad, Venkanna U, Amit Sharma, Kalika Bali
Language Resources and Evaluation Conference (LREC) | May 2020
Facilitating Media Distribution With Monetary Incentives
Devansh Mehta, Alok Sharma, Ramaravind K. Kommiya Mothilal, Chiraag, Anurag Shukla, Vishnu Prasad, Bill Thies, Venkanna U, Colin Scott, Amit Sharma
2020 CHI Conference on Human Factors in Computing Systems | April 2020
“Like Shock Absorbers”: Understanding the Human Infrastructures of Technology-Mediated Mental Health Support
Sachin Pendse, Faisal Lalani, Munmun De Choudhury, Amit Sharma, Neha Kumar
ACM CHI Conference on Human Factors in Computing Systems | April 2020
Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness
Ramaravind Kommiya Mothilal, Devansh Mehta, Alok Sharma, Bill Thies, Amit Sharma
November 2019
Cross-Cultural Differences in the Use of Online Mental Health Support Forums
Sachin R. Pendse, Kate Niederhoffer, Amit Sharma
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns
Saiganesh Swaminathan, Indrani Medhi Thies, Devansh Mehta, Ed Cutrell, Amit Sharma, Bill Thies (thies)
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Best of CSCW honorable mention
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
Jackson Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | August 2019
Optimizing peer referrals for public awareness using contextual bandits
Ramaravind K. Mothilal, Amulya Yadav, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Mental health in the global south: Challenges and opportunities in HCI for development
Sachin R. Pendse, Naveena Karusala, Divya Siddarth, Pattie Gonsalves, Seema Mehrotra, John A. Naslund, Mamta Sood, Neha Kumar, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Learnings from deploying a voice-based social platform for people with disability
Karn Dubey, Palash Gupta, Rachna Shriwas, Gayatri Gulvady, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
-
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
MINDNOTES: A Mobile Platform to enable users to break stigma around mental health and connect with therapists
Prateek Chanda, Amogh Wagh, Jemimah A Johnson, Swaraj Renghe, Vageesh D C, George Mathews, Sapna Behar, Poornima Bhola, Girish Rao, Paulomi Sudhir, T K Srikanth, Amit Sharma, Seema Mehrotra
October 2021
Predicting History
Joseph Risi, Amit Sharma, Rohan Shah, Matthew Connelly, Duncan J. Watts
Nature Human Behavior | April 2019
Prediction and explanation in social systems
Jake Hofman, Amit Sharma, Duncan Watts
Science | February 2017, Vol 355: pp. 486-488
Exploring Limits to Prediction in Complex Social Systems: Predicting Cascade Size on Twitter
Travis Martin, Jake Hofman, Amit Sharma, Ashton Anderson, Duncan Watts
Proceedings of the 25th International Conference on World Wide Web | April 2016
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
-
Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness
Ramaravind Kommiya Mothilal, Devansh Mehta, Alok Sharma, Bill Thies, Amit Sharma
November 2019
-
Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness
Ramaravind Kommiya Mothilal, Devansh Mehta, Alok Sharma, Bill Thies, Amit Sharma
November 2019
Harvesting Randomness to Optimize Distributed Systems
Mathias Lecuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins
16th ACM Workshop on Hot Topics in Networks (HotNets) | November 2017
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Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms
Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Koustuv Saha, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi
Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava, Alok Sharma, Anurag Shukla, Vishnu Prasad, Venkanna U, Amit Sharma, Kalika Bali
Language Resources and Evaluation Conference (LREC) | May 2020
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums
Taisa Kushner, Amit Sharma
ACM Web Conference (WWW) | April 2020
Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums
Yada Pruksachatkun, Sachin Pendse, Amit Sharma
2019 CHI Conference on Human Factors in Computing Systems | May 2019
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Necessary and Probably Sufficient Test for Finding Valid Instrumental Variables
December 2018
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
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Learnings from deploying a voice-based social platform for people with disability
Karn Dubey, Palash Gupta, Rachna Shriwas, Gayatri Gulvady, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Publications by Type
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Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Y. Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart
ICLR 2024 | September 2023
Towards Modular Machine Learning Pipelines
Aditya Modi, Jivat Neet Kaur, Maggie Makar, Pavan Mallapragada, Amit Sharma, Emre Kiciman, Adith Swaminathan
2023 International Conference on Machine Learning | July 2023
Combinatorial categorized bandits with expert rankings
Gaurav Sinha, Sayak Ray Chowdhury, Nagarajan Natarajan, Amit Sharma
UAI | July 2023
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
Jivat Neet Kaur, Emre Kiciman, Amit Sharma
International Conference on Learning Representations (ICLR) | January 2023
Notable Top-25% of accepted papers
A Causal AI Suite for Decision-Making
Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang
NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022
Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems
Parikshit Bansal, Yashoteja Prabhu, Emre Kiciman, Amit Sharma
NeurIPS 2022 Workshop on Distribution Shifts (DistShift) | November 2022
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Counterfactual Generation Under Confounding
Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
The Counterfactual-Shapley Value: Attributing Change in System Metrics
Amit Sharma, Hua Li, Jian Jiao
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Probing Classifiers are Unreliable for Concept Removal and Detection
Abhinav Kumar, Chenhao Tan, Amit Sharma
2022 Neural Information Processing Systems | October 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramainan, Amit Sharma
ICML 2022 | July 2022
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals
Saloni Dash, Vineeth Balasubramanian, Amit Sharma
Winter Conference on Applications of Computer Vision (WACV) | January 2022
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
AAAI/ACM Conference on AI, Ethics, and Society (AIES) | April 2021
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman
ACM Intl. Conf. on Web Search and Data Mining (WSDM) | March 2021
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayeulas, Amit Deshpande, Amit Sharma
AAAI Conference on Artificial Intelligence (AAAI) | February 2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Amit Sharma, Koustuv Saha
Proceedings of the 14th International AAAI Conference on Web and Social Media (ICWSM) | August 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
Using Mobile Airtime Credits to Incentivize Learning, Sharing and Survey Response: Experiences from the Field
Devansh Mehta, Ramaravind K. Mothilal, Alok Sharma, Bill Thies, Amit Sharma
ACM COMPASS: Conference on Computing and Sustainable Societies | June 2020
Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms
Ashish Sharma, Monojit Choudhury, Tim Althoff, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities
Koustuv Saha, Amit Sharma
AAAI International Conference on Web and Social Media (ICWSM) | June 2020
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi
Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava, Alok Sharma, Anurag Shukla, Vishnu Prasad, Venkanna U, Amit Sharma, Kalika Bali
Language Resources and Evaluation Conference (LREC) | May 2020
Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums
Taisa Kushner, Amit Sharma
ACM Web Conference (WWW) | April 2020
Facilitating Media Distribution With Monetary Incentives
Devansh Mehta, Alok Sharma, Ramaravind K. Kommiya Mothilal, Chiraag, Anurag Shukla, Vishnu Prasad, Bill Thies, Venkanna U, Colin Scott, Amit Sharma
2020 CHI Conference on Human Factors in Computing Systems | April 2020
“Like Shock Absorbers”: Understanding the Human Infrastructures of Technology-Mediated Mental Health Support
Sachin Pendse, Faisal Lalani, Munmun De Choudhury, Amit Sharma, Neha Kumar
ACM CHI Conference on Human Factors in Computing Systems | April 2020
Explaining Machine Learning Classifiers through Diverse Counterfactual Examples
Ramaravind K. Mothilal, Amit Sharma, Chenhao Tan
ACM Conference on Fairness, Accountability, and Transparency | January 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
Divyat Mahajan, Chenhao Tan, Amit Sharma
CausalML: Machine Learning and Causal Inference for Improved Decision Making Workshop, NeurIPS 2019 | December 2019
Cross-Cultural Differences in the Use of Online Mental Health Support Forums
Sachin R. Pendse, Kate Niederhoffer, Amit Sharma
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns
Saiganesh Swaminathan, Indrani Medhi Thies, Devansh Mehta, Ed Cutrell, Amit Sharma, Bill Thies (thies)
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) | November 2019
Best of CSCW honorable mention
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
Jackson Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | August 2019
Optimizing peer referrals for public awareness using contextual bandits
Ramaravind K. Mothilal, Amulya Yadav, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Mental health in the global south: Challenges and opportunities in HCI for development
Sachin R. Pendse, Naveena Karusala, Divya Siddarth, Pattie Gonsalves, Seema Mehrotra, John A. Naslund, Mamta Sood, Neha Kumar, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Learnings from deploying a voice-based social platform for people with disability
Karn Dubey, Palash Gupta, Rachna Shriwas, Gayatri Gulvady, Amit Sharma
ACM SIGCAS Conference on Computing & Sustainable Societies (COMPASS) | July 2019
Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums
Yada Pruksachatkun, Sachin Pendse, Amit Sharma
2019 CHI Conference on Human Factors in Computing Systems | May 2019
Tutorial on Causal Inference and Counterfactual Reasoning
ACM KDD International Conference on Knowledge Discovery and Data Mining | August 2018
Harvesting Randomness to Optimize Distributed Systems
Mathias Lecuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins
16th ACM Workshop on Hot Topics in Networks (HotNets) | November 2017
Auditing Search Engines for Differential Satisfaction Across Demographics
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna Wallach, Emine Yilmaz
Proceedings of the 26th International Conference on World Wide Web (Industry Track) | April 2017
Exploring Limits to Prediction in Complex Social Systems: Predicting Cascade Size on Twitter
Travis Martin, Jake Hofman, Amit Sharma, Ashton Anderson, Duncan Watts
Proceedings of the 25th International Conference on World Wide Web | April 2016
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
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Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman (emrek), Amit Sharma, Martin Kukla, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
MSR-TR-2022-1 | February 2022
Published by Microsoft
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
Amit Sharma, Cheng Zhang, Vasilis Syrgkanis, Emre Kiciman
MSR-TR-2021-15 | July 2021
Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
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MINDNOTES: A Mobile Platform to enable users to break stigma around mental health and connect with therapists
Prateek Chanda, Amogh Wagh, Jemimah A Johnson, Swaraj Renghe, Vageesh D C, George Mathews, Sapna Behar, Poornima Bhola, Girish Rao, Paulomi Sudhir, T K Srikanth, Amit Sharma, Seema Mehrotra
October 2021
DoWhy: An End-to-End Library for Causal Inference
November 2020
Causal Data Science Meeting (https://causalscience.org/)
Necessary and Probably Sufficient Test for Finding Valid Instrumental Variables
December 2018
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Inframarginality Audit of Group-Fairness
Amit Sharma, Arpita Biswas, Siddharth Barman
June 2020
Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness
Ramaravind Kommiya Mothilal, Devansh Mehta, Alok Sharma, Bill Thies, Amit Sharma
November 2019
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Barriers to Professional Help-seeking for Distress and Potential Utility of a Mental Health App: Stakeholder Perspectives
Jemimah Johnson, Janhavi Devdutt, Seema Mehrotra, Poornima Bhola, Paulomi Sudhir, Amit Sharma
Cureus Journal of Medical Science | February 2020
Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention
John A. Naslund, Pattie P. Gonsalves, Oliver Gruebner, Sachin R. Pendse, Stephanie L. Smith, Amit Sharma, Giuseppe Raviola
Current Treatment Options in Psychiatry | September 2019
Predicting History
Joseph Risi, Amit Sharma, Rohan Shah, Matthew Connelly, Duncan J. Watts
Nature Human Behavior | April 2019
Split-door criterion: Identification of causal effects through auxiliary outcomes
Amit Sharma, Jake Hofman, Duncan Watts
Annals of Applied Statistics | December 2018, Vol 12(4): pp. 2699-2733
Prediction and explanation in social systems
Jake Hofman, Amit Sharma, Duncan Watts
Science | February 2017, Vol 355: pp. 486-488