{"id":1151895,"date":"2025-10-30T07:00:40","date_gmt":"2025-10-30T14:00:40","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2026-07-07T08:08:28","modified_gmt":"2026-07-07T15:08:28","slug":"aiei","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/group\/aiei\/","title":{"rendered":"AI Economy Institute"},"content":{"rendered":"
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AI Economy Institute<\/h1>\n\n\n\n
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About Us \u2013 Microsoft AI Economy Institute <\/h2>\n\n\n\n
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Who We Are<\/h3>\n\n\n\n

The AI Economy Institute (AIEI) is Microsoft\u2019s flagship think tank dedicated to shaping an inclusive, trustworthy AI economy. We building a network of scholars and convening that network with our subject matter experts to explore how artificial intelligence is transforming work, education, and productivity \u2013 and making this knowledge base available to policy-makers, educators, and leaders for informed-decision-making. Our north star is an economic future by design. And one we design together.<\/p>\n\n\n\n

Our Mission<\/h3>\n\n\n\n

We advance actionable research and policy guidance that helps societies, governments, and organizations adapt intentionally to AI-driven change.<\/p>\n<\/div>

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What We Do<\/h3>\n\n\n\n

Research & Insights<\/strong>
We sponsor interdisciplinary studies on AI\u2019s economic and social impact, producing peer-reviewed articles, policy playbooks, and practical frameworks.<\/p>\n\n\n\n

Collaborative Network<\/strong>
Through calls for proposals, workshops, and global partnerships, we convene diverse voices to accelerate knowledge sharing and innovation.<\/p>\n\n\n\n

Real-World Impact<\/strong>
Our work informs Microsoft\u2019s strategy and public policy engagement, shaping education, workforce development, and equitable AI adoption worldwide.<\/p>\n<\/div><\/div>\n\n\n\n

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Why It Matters<\/h3>\n\n\n\n

AI is reshaping economies faster than any prior technology. AIEI exists to ensure this transformation strengthens opportunity, trust, and shared prosperity.<\/p>\n\n\n\n

Interested in becoming an advisor, share research question ideas or have general questions – contact us (opens in new tab)<\/span><\/a>!<\/p>\n\n\n\n

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AI Adoption in 2026 \u2013 Key Insights and Trends<\/h1>\n\n\n\n\n\n
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View the Latest Global AI Diffusion Report<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n
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View the Latest US AI Diffusion Report<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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Introducing our newest AIEI Cohort!<\/h3>\n\n\n\n

As AI moves from experimentation to widespread deployment, understanding how it reshapes firms, labor markets, and economies has become increasingly important. The AI Economy Institute\u2019s third research cohort focuses on AI at the Frontier<\/strong>\u2014examining how AI adoption spreads across organizations, industries, and regions, and what factors determine its economic impact. Bringing together a multidisciplinary group of researchers from around the world, the cohort explores topics including productivity and organizational transformation, workforce change, economic diffusion, historical parallels to technological disruption, and the emergence of agentic systems in labor markets. <\/p>\n\n\n\n

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Edoardo Maria Acabbia (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Mannheim<\/em><\/p>\n\n\n\n

Edoardo Maria Acabbi is a tenure-track Assistant Professor of Economics at the University of Mannheim (PhD, Harvard, 2020), working at the intersection of macroeconomics, labor economics, and corporate finance with administrative microdata and structural models. As a Microsoft AI Economy Institute Senior Fellow, he models how physical supply constraints \u2014 compute and energy \u2014 shape which firms adopt AI, how they reorganize work around it, and how fast labor markets adjust.   <\/p>\n\n\n\n

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Theme:<\/strong> The Speed Limit on AI
Subtheme:<\/strong> Forecasting the Frontier: Capabilities, Diffusion, and Labor Market Sign<\/p>\n\n\n\n

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Luca Mazonne (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Montreal<\/em><\/p>\n\n\n\n

Luca Mazzone is an Assistant Professor of Economics at the Universit\u00e9 de Montr\u00e9al. He previously worked as an economist at the International Monetary Fund, as an assistant professor at CERGE-EI, and has been a visiting scholar at the University of Pennsylvania. His work combines economic modeling, administrative and survey microdata, and computational methods to study questions at the frontier of labor-market dynamics and policy design. His research studies the mechanisms through which economic shocks and institutions translate into long-run differences in productivity, inequality, and mobility. <\/p>\n\n\n\n

Theme:<\/strong> The Speed Limit on AI
Subtheme:<\/strong> Forecasting the Frontier: Capabilities, Diffusion, and Labor Market Signals<\/p>\n\n\n\n

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Caspar David Peter (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Erasmus University, Rotterdam<\/em><\/em><\/p>\n\n\n\n

Caspar David Peter is an Associate Professor of Accounting at the Rotterdam School of Management, Erasmus University. His research examines the economic consequences of transparency – how changes in the information environment affect corporate behavior, professional labor markets, and the organization of economic activity. His work has been published in the Journal of Financial Economics, The Accounting Review, and The Review of Financial Studies. In 2024\/25 he was included in the Netherlands’ Economenparade, an annual list of the country’s published economists. He holds a doctorate from WHU \u2013\u2013 Otto Beisheim School of Management. <\/p>\n\n\n\n

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Theme:<\/strong> From Ledgers to Lotus: Spreadsheet Technology and Auditor Wages
Subtheme:<\/strong> When History Rhymes: GPT Analogues and Structural Shifts<\/p>\n\n\n\n

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Ilan Strauss (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

AI Disclosures Project<\/em><\/p>\n\n\n\n

Dr. Ilan Strauss is the Co-Director of the AI Disclosures Project. He recently co-led a Rockefeller-sponsored convening at Bellagio on protocols and mechanisms for Human+AI markets. He holds a Ph.D. in economics from the New School for Social Research (New York) and an M.Sc. in International Development Economics from SOAS (University of London). He is an Honorary Senior Research Fellow at University College London’s Institute for Innovation and Public Purpose and a Visiting Associate Professor at the University of Johannesburg (SARChI-ID). Previously, he consulted widely for United Nations bodies and the African Development Bank on international investment, industrial policies, and COVID-19 employment impacts. He is on the editorial board of Data & Policy (Cambridge University Press).<\/p>\n\n\n\n

Theme:<\/strong> Unfulfilled Promises? Macroeconomic Constraints on AI\u2019s Technological Diffusion 
Subtheme:<\/strong> When History Rhymes: GPT Analogues and Structural Shifts <\/p>\n\n\n\n

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Daniel Yue (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Georgia Institute of Technology<\/em><\/em><\/em><\/p>\n\n\n\n

Daniel Yue is an Assistant Professor of Information Technology Management at the Scheller College of Business, Georgia Institute of Technology. His research examines open disclosure \u2014 why firms openly share valuable knowledge without directly profiting from it \u2014 and, more broadly, how the digital infrastructure underpinning the AI economy, from open-source ecosystems to data centers and compute markets, is built, governed, and valued. Studying scientific publications and open-source software in AI, his work develops frameworks at the intersection of open innovation, AI research, and technology strategy. Recent projects estimate the impact of corporate involvement on AI research and the latent economic role of open models in the AI economy. He holds a PhD in Business Administration from Harvard Business School and an AB in Physics from Harvard College.<\/p>\n\n\n\n

Theme:<\/strong> Competition and Lock-In in the AI Inference Market: Evidence from OpenRouter
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Frank Nagle, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Massachusetts Institute of Technology (co-PI)<\/em><\/p>\n\n\n\n

Frank Nagle is a Research Scientist at MIT where he studies AI, open source, cybersecurity, and technology strategy. He is also the Chief Economist for The Linux Foundation. <\/p>\n\n\n\n

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Theme: <\/strong>Competition and Lock-In in the AI Inference Market: Evidence from OpenRouter
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Pierre-Alexandre Balland (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Centre for European Policy Studies (CEPS)<\/em><\/em><\/p>\n\n\n\n

Pierre-Alexandre Balland is Chief Data Scientist at the Centre for European Policy Studies (CEPS), Visiting Professor at the Harvard Growth Lab, and director of AI World, a global initiative mapping the evolution of AI ecosystems. He was recently named among Clarivate’s 2025 Highly Cited Researchers (top 1% most-cited scientists worldwide) and regularly advises the European Commission and several governments on AI, industrial policy, and innovation strategy. He teaches AI for business leaders, machine learning, and economic complexity, and is a frequent keynote speaker – most recently at Slush, Unleash World, VivaTech, the AI & Big Data Expo, and SuperReturn. He is also an entrepreneur who has co-founded startups in AI and robotics.  <\/p>\n\n\n\n

Theme:<\/strong> The Rise of the Multi-AI Economy – AI Specializations Across Cities 
Subtheme:<\/strong> Economic Geography and Diffusion: Regional and Market Level Spillovers <\/p>\n\n\n\n

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Laura Nurski, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Centre for European Policy Studies (CEPS)<\/em>, Belgium<\/em>  <\/em><\/p>\n\n\n\n

Prof. Dr. Laura Nurski is Head of Program on the Future of Work at the Centre for European Policy Studies (CEPS) in Brussels, where she leads policy research on the impact of artificial intelligence on labor markets, work organization and job quality. She is also Assistant Professor in the Work and Organizations Studies department at KU Leuven (Belgium) where she leads the Acerta Chair AI at Work, conducting experimental (workplace) research on AI and job design.  <\/p>\n\n\n\n

Theme:<\/strong> The Rise of the Multi-AI Economy – AI Specializations Across Cities 
Subtheme:<\/strong> Economic Geography and Diffusion: Regional and Market Level Spillovers<\/p>\n\n\n\n

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Nuriye Melisa Bilgin (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Ko\u00e7 University<\/em><\/p>\n\n\n\n

Nuriye Melisa Bilgin is a lecturer in economics at Ko\u00e7 University in Istanbul. She earned her PhD in economics from Ko\u00e7 University in 2020 and served as a consultant at the World Bank from 2019 to 2021, subsequently taking up post-doctoral research positions at Bocconi University and the University of Turin. Her research examines the interplay between networks, firm dynamics, technology adoption, international trade, and sustainability, with recent work focusing on the diffusion of AI and digital technologies across firms and their implications for a sustainable economy.<\/p>\n\n\n\n

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Theme:<\/strong> Beyond Cost and Skills: Barriers to AI Adoption in Emerging Economies
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design <\/p>\n\n\n\n

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Gianmarco Ottaviano (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Bocconi University<\/em><\/p>\n\n\n\n

JGianmarco Ottaviano is Full Professor of Economics and holds the Achille and Giulia Boroli Chair in European Studies at Bocconi University, where he co-directs the Globalization and Industrial Dynamics Research Unit at the Baffi Centre. He previously held professorships at the London School of Economics\u2014where he directed the Centre for Economic Performance’s Trade Programme\u2014and the University of Bologna. An expert in international trade, urban economics, and economic geography, his recent research examines corporate competitiveness, digital infrastructure, and the economic impacts of immigration and delocalization. Professor Ottaviano is a Fellow of both the Academia Europaea and the Royal Society of Arts, and maintains research affiliations with several leading international institutions, including the CEPR, CEP, and the Kiel Institute.<\/p>\n\n\n\n

Theme:<\/strong> Beyond Cost and Skills: Barriers to AI Adoption in Emerging Economies
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design  <\/p>\n\n\n\n

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Wesley Rosslyn-Smith (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Pretoria<\/em><\/p>\n\n\n\n

Dr. Wesley Rosslyn-Smith is an Associate Professor at the University of Pretoria and Director of the Centre for the Future of Work. He is also an adjunct Professor at the Gordon Institute of Business Science (GIBS). His research explores how the future of work is unfolding across Africa, with a focus on how artificial intelligence, automation, and emerging technologies are reshaping labor, skills, and organizations. He also directs the South African Centre for Industry and Technology (SACIT), a World Economic Forum Centre for the Fourth Industrial Revolution focused on accelerating technology adoption across South African industry through collaboration between academia, government, and the private sector.<\/p>\n\n\n\n

Theme:<\/strong> At the Frontier of the Informal Economy: AI Adoption and Productivity Among South Africa’s Informal Entrepreneurs
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design <\/p>\n\n\n\n

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Johannes Wachs  (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Corvinus University, Budapest<\/em><\/em><\/p>\n\n\n\n

Johannes Wachs is a Senior Research Fellow at the Centre for Economic and Regional Studies and Faculty at the Complexity Science Hub Vienna. His research studies the digital economy and its economic geography. In recent work he examines how people build software together, how AI is transforming knowledge work, and what role geography plays in these processes. He develops data and network science methods to address these questions. He has a PhD in Network Science from Central European University and has previously worked at the Vienna University of Economics and Business and RWTH Aachen.<\/p>\n\n\n\n

Theme:<\/strong> The Network Geography of AI Adoption 
Subtheme:<\/strong> Economic Geography and Diffusion: Regional and Market Level Spillovers     <\/p>\n\n\n\n

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Nataliya Wright (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University<\/em><\/p>\n\n\n\n

Nataliya Langburd Wright is an Assistant Professor in the strategy area and Chazen Senior Scholar at Columbia Business School. Her research focuses on entrepreneurial strategy, particularly how strategic technological and market choices shape global entrepreneurial growth. Her research draws inspiration from her prior policy work as a senior consultant and staff economist at the World Bank and White House and startup work as a co-founder, adviser, and board member. She earned her PhD from Harvard Business School, MPhil from the University of Cambridge, and BA from Yale University.<\/p>\n\n\n\n

Theme:<\/strong> Economic Geography and Diffusion: Regional and Market Level Spillovers
Subtheme:<\/strong> Economic Geography and Diffusion: Regional and Market Level Spillovers   <\/p>\n\n\n\n

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Salman Khan (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)<\/em><\/p>\n\n\n\n

Dr. Salman Khan is an Associate Professor at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), where he leads large-scale initiatives at the intersection of artificial intelligence, multimodal understanding and reasoning, and Earth observation. His work focuses on building robust, generalizable, and scalable AI systems that operate reliably in open-world settings. He works on vision\u2013language models, lifelong and continual learning, and geospatial AI, translating advances in machine learning and computer vision into real-world applications in climate science, sustainable agriculture, and environmental monitoring. He has authored over 200 publications and has received multiple recognitions, including a CVPR Best Paper nomination, ACCV Best Student Paper Honorable Mention, CVPR MONTI Best Paper Award, and the ICML TerraBytes Best Paper Award. Before joining MBZUAI, he served as a Senior Scientist at the Inception Institute and as a Research Scientist at Data61\/CSIRO. He received his PhD in Computer Vision from the University of Western Australia.<\/p>\n\n\n\n

Theme:<\/strong> At the Frontier: Occupational Restructuring and Early Labor Market Signals in the World’s #1 AI Economy
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Mustafa Afacan (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

MBZUAI; Sabanc\u0131 University<\/em><\/p>\n\n\n\n

Dr. Afacan earned his Ph.D. in Economics from Stanford University in 2012. His research interests include market design, applied microeconomics, and game theory. His research articles have been published in prestigious economics journals. Dr. Afacan\u2019s projects have also received support from renowned institutions, including the European Research Council, the Qatar National Research Fund, and the Scientific and Technological Research Council of Turkey. He is a recipient of the Science Academy Young Scientist Award, the Turkish Academy of Sciences Young Scientist Award, the Middle East Technical University Parlar Foundation Research Incentive Award, and the Qatar University Faculty of Business and Economics Outstanding Research Impact Award. He is currently a full-time faculty member at MBZUAI (UAE) and a network faculty member at Sabanc\u0131 University (Turkey). He also serves as an Associate Editor of the Journal of Mathematical Economics.<\/p>\n\n\n\n

Theme: <\/strong>At the Frontier: Occupational Restructuring and Early Labor Market Signals in the World’s #1 AI Economy
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design <\/p>\n\n\n\n

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Friederike Mengel (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Essex; Erasmus University Rotterdam<\/em><\/p>\n\n\n\n

Friederike Mengel is a Professor of Economics at the University of Essex (UK) and Rotating Chair in Behavioral Economics at Erasmus University Rotterdam (NL). She received her PhD from the University of Alicante in Spain and has held positions at Maastricht University and the University of Nottingham. Friederike is a Behavioral Economist working on Evolutionary Game Theory and the study of social networks. Her research investigates opinion dynamics in networks, how people form and revise beliefs about themselves and the world, how information diffuses in networks to generate innovation and how social norms and social influence emerge. She is currently a co-editor at Experimental Economics and a Fellow of the Academy of Social Sciences. In 2019 she received the Philipp Leverhulme Prize in Economics.<\/p>\n\n\n\n

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Theme: <\/strong>How does AI impact productivity, innovation, and teamwork in organizations? 
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Christoph Siemroth (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Essex<\/em><\/p>\n\n\n\n

Christoph Siemroth is an Associate Professor of Economics at the University of Essex in England. His research focuses on organizational economics, including innovation, remote work, productivity, and AI-use in firms. His work has appeared in journals for economics, finance, psychology, and tech. <\/p>\n\n\n\n

Theme: <\/strong>How does AI impact productivity, innovation, and teamwork in organizations? 
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Yingfei Wang (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Foster School of Business, University of Washington<\/em>  <\/em><\/p>\n\n\n\n

Yingfei Wang is an Associate Professor of Information Systems at the Foster School of Business, University of Washington. Before joining UW, she received her Ph.D. from the Computer Science Department at Princeton University. She earned her bachelor\u2019s degree in Computer Science, with a dual degree in Economics, from Peking University. Her research lies at the intersection of machine learning, statistics, sociotechnical AI design, and the economics of information systems. She develops adaptive algorithms and decision-making frameworks, drawing on reinforcement learning, multi-armed bandits, and adaptive experimentation, to address complex challenges in dynamic organizational and societal contexts.<\/p>\n\n\n\n

Theme:<\/strong> From Friction to Lift: Repeated Human-AI Interaction and Learning-Aware Delegation in Frontier Firms
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Serena Booth (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Brown University<\/em><\/p>\n\n\n\n

Serena studies the design and governance of AI systems, and what governance structures society should put in place to protect workers in light of these technological advances. Serena previously worked in the U.S. Senate as a AAAS AI Policy Fellow (2023-2025) on issues related to AI and consumer protection, economic policy, and labor.  <\/p>\n\n\n\n

Theme:<\/strong> Governing the AI Workplace: Worker Voice and Institutional Change 
Subtheme: <\/strong>Occupational Change, Leadership Expectation, and Workforce Transformation<\/p>\n\n\n\n

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Meeyoung (Mia) Cha (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Korea Advanced Institute of Science and Technology (KAIST)<\/em><\/p>\n\n\n\n

Meeyoung (Mia) Cha is a Scientific Director at the Max Planck Institute for Security and Privacy (MPI-SP) and a Professor at the KAIST School of Computing. Working at the intersection of AI, computing, and society, she focuses on engineering human-centric technologies that address complex global challenges for well-being and safety. Her research tackles critical socio-technical issues, ranging from AI models to track the spread of misinformation to deploying machine learning for sustainability. Her work leverages high-resolution satellite imagery for slum detection and global poverty mapping. These practical frameworks have been adopted by international bodies like UNICEF and the World Customs Organization to drive economic transparency. <\/p>\n\n\n\n

Theme:<\/strong> Agents as Employers: Characterizing the Transformation of Human Work in the AI-Mediated Economy
Subtheme:<\/strong> Occupational Change, Leadership Expectation, and Workforce Transformation <\/p>\n\n\n\n

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Brian Jabarian (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Carnegie Mellon University<\/em><\/p>\n\n\n\n

Brian Jabarian is an Assistant Professor at Carnegie Mellon University\u2019s Heinz College of Information Systems and Public Policy, with a courtesy appointment in the School of Computer Science. He is an economist studying how frontier AI systems are transforming work, productivity, firms, and labor markets. His research develops partnerships with organizations deploying AI systems in real-world workflows and combines large-scale natural field experiments, synthetic experiments, and prediction markets to measure and forecast the economic impacts of AI. He received his Ph.D. in Economics from the Paris School of Economics and his Ph.D. in Philosophy from the Sorbonne, both in 2023. His research has been supported by grants from leading institutions and published in leading academic journals, including Nature Human Behaviour. His work has also been covered by The Wall Street Journal, NPR\u2019s Planet Money, Bloomberg, the Financial Times, and The Information, among others. <\/p>\n\n\n\n

Theme:<\/strong> Designing End-to-End Agentic Hiring: Signal Elicitation, Evaluation, and Decision-Making  
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Luca Henkel (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Erasmus University, Rotterdam  <\/em><\/p>\n\n\n\n

Luca Henkel is an Assistant Professor of Finance (tenure-track) at the Erasmus School of Economics, Erasmus University Rotterdam. He received his Ph.D. in 2023 from the University of Bonn. His research fields are behavioral economics and household finance. In particular, he examines determinants and consequences of prosocial and financial decision-making using experiments (field, lab, and online), surveys, and linked survey-administrative data. In addition, he uses natural field experiments to study AI-based automation and its impact on workers and firms.\u202f <\/p>\n\n\n\n

Theme:<\/strong> Designing End-to-End Agentic Hiring: Signal Elicitation, Evaluation, and Decision-Making
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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\"bio<\/figure>\n\n\n\n

P\u00ebllumb Reshidi<\/h4>\n\n\n\n

Florida State University <\/em><\/p>\n\n\n\n

Dr. P\u00ebllumb Reshidi is an Assistant Professor of Economics at Florida State University. His research focuses on how information diffuses and distorts across individuals, networks, and institutions, and how the timing and structure of that flow governs the beliefs and decisions made at scale. A parallel strand of his work examines market design questions, including the design of human-AI screening systems in labor markets, studying how the introduction of AI into hiring reshapes incentives, match quality, and worker welfare. He complements his theoretical findings with controlled laboratory experiments and large-scale field studies, allowing him to not only derive but also rigorously test predictions about economic behavior. Prior to joining FSU, he was a Research Associate at Duke University. P\u00ebllumb holds a PhD in Economics from Princeton University.<\/p>\n\n\n\n

Theme:<\/strong> Designing End-to-End Agentic Hiring: Signal Elicitation, Evaluation, and Decision-Making
Subtheme:<\/strong> Productivity at the Frontier and Firm-Level Transformation: How AI Is Reshaping Production and Organizational Design<\/p>\n\n\n\n

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Meet the second cohort of AIEI senior fellows <\/h3>\n\n\n\n

As AI continues to transform economies and societies, understanding how its adoption spreads is critical to shaping an inclusive future. The AI Economy Institute\u2019s second research cohort builds on this mission by focusing on Education in the AI Economy<\/em>\u2014examining how AI diffusion impacts classrooms, educators, and workforce pathways worldwide. With researchers from eight countries and leading institutions, this multidisciplinary team explores national strategies, educational innovation, and labor market transitions to ensure AI-driven change benefits all. Their work will provide actionable insights for policy, education reform, and global collaboration across academia, industry, and government.<\/p>\n\n\n\n\n\n

\"Dr.<\/figure>\n\n\n\n

Andrew Stokols, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

MIT\/Singapore Management University, Singapore<\/em> <\/em><\/p>\n\n\n\n

Andrew Stokols is Assistant Professor of urban studies at Singapore Management University. Dr. Stokols research examines the geopolitics of digital infrastructure, including smart cities, data platforms, cloud computing, and data regulation in China and Southeast Asia.  <\/p>\n\n\n\n

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Theme:<\/strong> AI and National Diffusion Differences 
Subtheme:<\/strong> Examining National Strategies for AI Diffusion in East and Southeast Asia: Policies, Networks, and Early Adopters<\/p>\n\n\n\n

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\"Carolina<\/figure>\n\n\n\n

Carolina Calvo, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

National Center for AI (CENIA), Chile<\/em> <\/em><\/p>\n\n\n\n

Carolina Calvo is an economist with 15 years of experience in program and policy evaluation, innovation systems, and strategic trade controls. Specializing in econometric analysis and impact evaluation, she focuses on R&D, productivity, and trade, bridging applied research with evidence-based policymaking. Her work centers on promoting innovation, advancing technology transfer, and generating evidence for effective public policy. <\/p>\n\n\n\n

Theme:<\/strong> AI and National Diffusion Differences 
Subtheme:<\/strong> Explaining AI Diffusion in Latin America: Human Capital, Institutions, and Infrastructure <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Xin Skye Zhao, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Manchester, England<\/em> <\/em><\/em><\/p>\n\n\n\n

Xin Zhao (Skye) is a Lecturer in Generative AI for Education at the Manchester Institute of Education and a partner in UNESCO\u2019s AI competency frameworks. Dr. Zhao also serves on the UN expert panel for Generative AI. Her research focuses on ethical, inclusive uses of AI in education. <\/p>\n\n\n\n

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Theme:<\/strong> AI and National Diffusion Differences 
Subtheme:<\/strong> Global Pathways of AI Diffusion: Skills, Governance, and Policy Strategies Across Regions <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Arun Sundararajan, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

New York University (AIEI Cohort 1 Senior Fellow<\/em>) <\/em><\/p>\n\n\n\n

Arun Sundararajan is the Harold Price Professor of Entrepreneurship and Professor of Technology, Operations, and Statistics at NYU Stern School of Business, where he also serves as Director of the Fubon Center for Technology, Business, and Innovation. Dr. Sundararajan is widely recognized as an expert on the economics of digital goods and network effects, the regulation of AI and digital platforms, and the future of work. His award-winning book, \u201cThe Sharing Economy,\u201d has been translated into multiple languages. He co-chairs the World Economic Forum\u2019s Global Future Council on Data Frontiers. <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> Mapping High-Impact AI Transitions: Linking Occupations, Retraining Pathways, and Educational Institutions <\/p>\n\n\n\n

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\"Robert<\/figure>\n\n\n\n

Robert Seamans, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

New York University (AIEI Cohort 1 Senior Fellow<\/em>) <\/em><\/em><\/em><\/p>\n\n\n\n

Robert Seamans is a Professor at NYU’s Stern School of Business, Director of the Stern Center for the Future of Management, and a nonresident Senior Fellow at the Brookings Institution. His research focuses on the economic impact of AI, robotics, and advanced technologies. His work has been published in top academic journals and cited by outlets like The Atlantic, The Economist, and The New York Times. In 2015, he served as the senior economist for technology and innovation on President Obama’s Council of Economic Advisers. <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> Mapping High-Impact AI Transitions: Linking Occupations, Retraining Pathways, and Educational Institutions <\/p>\n\n\n\n

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\"Dr.\u202fJason<\/figure>\n\n\n\n

Jason Jabbari, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Washington University, St. Louis <\/em><\/p>\n\n\n\n

Jason Jabbari is an Assistant Professor at the Brown School at Washington University in St. Louis and leads the Center for Education Research, Practice, and Policy Partnerships (CERP3). His research focuses on improving outcomes for vulnerable populations, with a current emphasis on AI\u2019s impact in education and workforce development. He also directs the Clark-Fox Policy Institute and leads research in career education, student mental health, and neighborhood effects. Dr. Jabbari serves as a Captain in the US Army Reserves. <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> Stacking AI Skills through Education-Industry Partnerships: Case Studies and Causal Evidence on Technology Training, Non-Degree Credentials, and Apprenticeships<\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Sarah Rodriguez, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Virginia Tech Foundation<\/em><\/em><\/p>\n\n\n\n

Sarah Rodriguez is an Associate Professor of Engineering Education at Virginia Tech. Her research focuses on the engineering and computing identity development of historically marginalized populations in higher education. Dr. Rodriguez is currently involved in large-scale interdisciplinary projects on institutional environments and STEM identity, sponsored by the National Science Foundation (NSF) and the Kapor Center.  <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> A Study of Community Colleges and GenAI Diffusion: Understanding Innovation, Workforce Development, & Regional Pathways <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Bashar Alhafni, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Mohamed bin Zayed University of AI (MBZUAI), UAE<\/em> <\/em><\/p>\n\n\n\n

Bashar Alhafni is an Assistant Professor of Natural Language Processing at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). His research focuses on Arabic NLP, particularly in developing human-centered language technologies. He leads the Arabic AI Modeling (Aram) Lab, working on areas like grammatical error detection, text simplification, and controlled natural language generation. Dr. Alhafni is dedicated to creating Arabic NLP applications that support education and contribute to social good. <\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> Barriers and Opportunities for Generative AI in K-12 Arabic Education <\/p>\n\n\n\n

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\"Carolina<\/figure>\n\n\n\n

Carolina Lopez, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

World Bank<\/em><\/p>\n\n\n\n

Carolina Lopez is a Research Economist in the Poverty, Inequality, and Human Development Team at the World Bank\u2019s Development Research Group. Her research focuses on education, human capital, and behavioral economics, particularly how beliefs influence behavior and welfare. <\/p>\n\n\n\n

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Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> AI in the Classroom: Evaluating the Impact of Teacher Training on Teaching Practices and Student Outcomes  <\/p>\n\n\n\n

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\"Dr<\/figure>\n\n\n\n

Joseph Onderi Orero, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Strathmore University, Kenya<\/em> <\/em><\/p>\n\n\n\n

Joseph Onderi Orero is a Senior Researcher in AI at Strathmore University\u2019s School of Computing and Engineering Sciences. His internationally recognized research explores AI applications in education and health, and he has published extensively in these fields. Currently, Dr. Orero is exploring the use of Generative AI in game-based learning in Africa, aiming to integrate AI into education with an emphasis on ethical, human-centered design. <\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> AI in the Classroom: Evaluating the Impact of Teacher Training on Teaching Practices and Student Outcomes  <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Tingting Li, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Washington State University (Microsoft 50 for 50 awardee<\/em>)  <\/em><\/p>\n\n\n\n

Tingting Li\u2019s research focuses on human-AI collaboration, science assessment, and rural education policy. She leads projects on generative AI in K\u201312 classrooms, particularly in underserved schools, and co-directs CAiRE at WSU, where she collaborates with educators to design AI tools for classroom use. Dr. Li has published 37+ peer-reviewed articles and has received several prestigious fellowships. <\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> RAISE (Rural AI for Societal Equity): A Roadmap Linking Classrooms and Workforce Equity in the AI Economy<\/p>\n\n\n\n

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\"Sarayu<\/figure>\n\n\n\n

Sarayu Sundar, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Colorado Boulder<\/em> (Affiliate Fellow) <\/em><\/p>\n\n\n\n

Dr. Sarayu Sundar is a Higher Education Faculty Research Associate at the Center for Technology Workforce Innovation (formerly NCWIT) at the University of Colorado – Boulder. In this role, Dr. Sundar focuses on leveraging quantitative and qualitative data to understand trends and patterns in computing student outcomes. She also oversees the collection and analysis of longitudinal enrollment, retention, and degree completion data from member institutions.”<\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> Exploring the Preparation of AI-literate, AI-skilled, and AI-ethical college students in the US    <\/p>\n\n\n\n

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\"Wendy<\/figure>\n\n\n\n

Wendy DuBow, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Colorado Boulder<\/em> (Affiliate Fellow)<\/em><\/p>\n\n\n\n

Dr. Wendy DuBow is Director of Strategies for Education Research & Evaluation at the Center for Technology Workforce Innovation (formerly NCWIT) and affiliate faculty member in Women and Gender Studies at the University of Colorado – Boulder. DuBow conducts mixed methods social science research, with a focus on systemic levers that can broaden participation in technology for historically marginalized and excluded populations.<\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> Exploring the Preparation of AI-literate, AI-skilled, and AI-ethical college students in the US    <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Bharat Chandar, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Stanford University <\/em><\/p>\n\n\n\n

Bharat Chandar is a postdoctoral researcher at the Stanford Digital Economy Lab, part of the Institute for Human-Centered AI. Dr. Chandar\u2019s research focuses on AI’s impact on the labor market and productivity using a combination of big data and company partnerships. Bharat is a co-author on the recent \u201cCanaries in the Coalmine\u201d paper from Stanford.<\/p>\n\n\n\n

<\/p>\n\n\n\n

Theme:<\/strong> The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> The Labor Market Impacts of Business AI Adoption  <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Manuel Hoffmann, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of California, Irvine <\/em><\/p>\n\n\n\n

Manuel Hoffmann is an Assistant Professor at the University of California, Irvine, at the Paul Merage School of Business and is also affiliated with Stanford University. Dr. Hoffmann\u2019s research focuses on the social and behavioral aspects of open source software and artificial intelligence, with a broader interest in innovation and technology management. His work aims to deepen understanding of strategic issues facing large, medium-sized, and entrepreneurial firms. <\/p>\n\n\n\n

Theme: <\/strong>The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> How Mentorship Affects AI Adoption and Usage – The Generative AI Gender Puzzle <\/p>\n\n\n\n

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\"Frank<\/figure>\n\n\n\n

Frank Nagle, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Massachusetts Institute of Technology <\/em><\/p>\n\n\n\n

Frank Nagle is a Research Scientist at MIT where he studies AI, open source, cybersecurity, and technology strategy. He is also the Chief Economist for The Linux Foundation. <\/p>\n\n\n\n

<\/div>\n\n\n\n

Theme: <\/strong>The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> How Mentorship Affects AI Adoption and Usage – The Generative AI Gender Puzzle <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Inbal Talgam-Cohen, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Tel Aviv University, Israel<\/em> <\/em><\/p>\n\n\n\n

Inbal Talgam-Cohen is an interdisciplinary researcher focused on incentives, algorithms, and learning, drawing from the fields of computer science, economics, and law. Dr. Talgam-Cohen is a faculty member at Tel Aviv University and a visiting faculty at the Technion, where she began her academic career before moving to TAU. Her research group spans both institutions.  <\/p>\n\n\n\n

Theme: <\/strong>The Impact of AI on Entry-Level Jobs
Subtheme:<\/strong> Contracts for AI-Empowered Online Labor Markets <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Laura Nurski, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Centre for European Policy Studies (CEPS)<\/em>, Belgium<\/em>  <\/em><\/p>\n\n\n\n

Prof. Dr. Laura Nurski is Head of Program on the Future of Work at the Centre for European Policy Studies (CEPS) in Brussels, where she leads policy research on the impact of artificial intelligence on labor markets, work organization and job quality. She is also Assistant Professor in the Work and Organizations Studies department at KU Leuven (Belgium) where she leads the Acerta Chair AI at Work, conducting experimental (workplace) research on AI and job design.  <\/p>\n\n\n\n

Theme:<\/strong> The Impact of AI on Entry-Level Jobs
Subtheme:<\/strong> First European evidence on AI and entry-level jobs: replicating the Canaries in the Coal Mine <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Michael Impink, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

HEC Paris, France<\/em> <\/em><\/p>\n\n\n\n

Michael Impink is an Assistant Professor of Strategy at HEC Paris and a research affiliate at Hi! Paris (AI for Society and Business) and Boston University TPRI. His research focuses on how digitization impacts firm structure and performance. Prior to the PhD, Michael was a senior manager at Microsoft based in Seattle and Singapore and a fellow at Harvard University’s Weatherhead Center for International Affairs <\/p>\n\n\n\n

Theme:<\/strong> The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> Does the growing use of digital tools pave the way for white-collar apprenticeship programs? <\/p>\n\n\n\n

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Meet the inaugural first cohort of AIEI senior fellows <\/h3>\n\n\n\n

As AI reshapes the global economy, higher education will be crucial in preparing society for these changes. The AI Economy Institute\u2019s first research cohort is studying how colleges and universities can lead this transformation by examining shifts in university structures, curricula, professional training, and their roles in the workforce. With 14 project teams and 24 scholars from various backgrounds, the Institute seeks to\u202fprovide\u202fpractical insights for policy and collaborative action among academia, industry, and government\u202fon the future of education and workforce. <\/p>\n\n\n\n\n\n

\"Dr.<\/figure>\n\n\n\n

Dr. Adam Cannon (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University<\/em><\/p>\n\n\n\n

Dr. Adam Cannon is a computer science faculty member at Columbia University, where he develops and teaches large undergraduate courses for both majors and non-majors. He has contributed to curriculum design at the departmental, school, and university levels, and chaired the development committee for the AP Computer Science Principles Exam. His current focus is on teaching computer science and AI literacy to liberal arts and humanities students. In 2000 he joined Columbia and also served as a visiting scientist at Los Alamos National Laboratory, where his research focused on machine learning methods for building data-dependent hypothesis classes. He holds a BS and MS in aerospace engineering from the University of California and a PhD in applied mathematics from Johns Hopkins University. <\/p>\n\n\n\n

Project 1:<\/strong> The Evolution of CS Education: Integrating AI as a Foundational Element
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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Dr. Vishal Misra (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University<\/em><\/p>\n\n\n\n

Vishal Misra is a Professor of Computer Science and Electrical Engineering at Columbia University and Vice Dean for Computing and AI in the School of Engineering. An ACM and IEEE Fellow, his research focuses on mathematical modeling of systems, bridging practice and analysis. As a graduate student, he co-founded CricInfo, later acquired by ESPN. In 2021, he developed one of the first commercial applications using GPT-3 for ESPNcricinfo and has since modeled LLM behavior. He played a key role in India\u2019s Net Neutrality regulation, with his definition adopted by both activists and regulators. He received Distinguished Alumnus honors from IIT Bombay (2019) and UMass Amherst (2014). <\/p>\n\n\n\n

Project 1:<\/strong> The Evolution of CS Education: Integrating AI as a Foundational Element
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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\"Jeffrey<\/figure>\n\n\n\n

Jeffrey Oakman (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Princeton University <\/em><\/p>\n\n\n\n

Jeffrey Oakman joined the Provost\u2019s Office in September 2024 to lead the creation of the New Jersey AI Hub at Princeton. Collaborating with partners including the NJ Economic Development Authority, Microsoft, and CoreWeave, he is guiding efforts to position Princeton and New Jersey as leaders in AI innovation. The Hub will support advanced AI research, regional economic growth, workforce development, public sector guidance, and startup formation. Previously, Oakman served as a Senior Policy Advisor in Governor Murphy\u2019s Administration, focusing on economic and community development. He holds degrees from Rice University and Princeton SPIA, where he also served as Associate Director of the Graduate Program from 2016 to 2019. <\/p>\n\n\n\n

Project 2:<\/strong> Leveraging Artificial Intelligence to Transform Sectors and Reimagine Jobs Throughout the Economy
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n

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\"Jennifer<\/figure>\n\n\n\n

Jennifer Rexford (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Princeton University <\/em><\/p>\n\n\n\n

As Provost of Princeton University, Dr. Jennifer Rexford oversees the academic mission and long-term financial health of the institution. A 1991 Princeton graduate, she is the Gordon Y.S. Wu Professor in Engineering. After earning her PhD in electrical engineering and computer science from the University of Michigan, she spent over eight years at AT&T Labs, where she developed techniques used in backbone networks. She joined Princeton\u2019s Department of Computer Science as a full professor in 2005, became department chair in 2015, and received her named professorship in 2012. Her research focuses on computer networking, with a broader goal of making the Internet more trustworthy and reliable. <\/p>\n\n\n\n

Project 2:<\/strong> Leveraging Artificial Intelligence to Transform Sectors and Reimagine Jobs Throughout the Economy
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Matthew Connelly (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University <\/em><\/p>\n\n\n\n

Dr. Matthew Connelly is a Professor of International and Global History and Vice Dean of AI initiatives at Columbia University. He co-led Columbia\u2019s Institute for Social and Economic Research and Policy and directs History Lab, which uses data science to study state secrecy, focusing on intelligence, surveillance, and weapons of mass destruction. Prior to that, he directed the Hertog Global Strategy Initiative on planetary threats. His publications include \u201cA Diplomatic Revolution: Algeria\u2019s Fight for Independence and the Origins of the Post-Cold War Era,\u201d which won five prizes, and \u201cFatal Misconception: The Struggle to Control World Population,\u201d an Economist and Financial Times book of the year. His research appears in journals such as\u202fNature Human Behaviour<\/em>,\u202fAnnals of Applied Statistics<\/em>, and\u202fComparative Studies in Society and History.<\/em> <\/p>\n\n\n\n

Project 3:<\/strong> AI and the Transformation of Higher Education: An Integrated Approach
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr.\u202fSJ Beard (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Cambridge <\/em><\/p>\n\n\n\n

Dr. SJ Beard is a leading researcher in the transdisciplinary field of Existential Risk Studies, focusing on global catastrophic risks, future ethics, and building existential hope. Their work explores systemic threats from transformative technologies and environmental breakdown, and they co-authored\u202fDouble Debt Disaster<\/em>\u202fon injustice and disaster recovery. Beard has edited two volumes on existential risk and is writing a monograph on existential hope. They are a Borysiewicz Interdisciplinary Fellow, advisor to the UK\u2019s All-Party Parliamentary Group for Future Generations, BBC New Generation Thinker, and editorial board member of\u202fFutures<\/em>. Their media work includes BBC programs and appearances on\u202fNewsnight<\/em>,\u202fAnalysis<\/em>, and\u202fThe Naked Scientists<\/em>. <\/p>\n\n\n\n

Project 3:<\/strong> AI and the Transformation of Higher Education: An Integrated Approach
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Morgan Frank (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Pittsburgh <\/em><\/p>\n\n\n\n

Dr. Morgan Frank is an Assistant Professor at the School of Computing and Information at the University of Pittsburgh in the Department of Informatics and Networked Systems. He is interested in the complexity of AI, the future of work, and the socio-economic consequences of technological change. While many studies focus on phenotypic labor trends, Dr. Frank\u2019s recent research examines how genotypic skill-level processes around AI impact individuals and society. Combining labor research with investigations into the nature of AI research and the social or societal implications of AI adoption, he hopes to inform our understanding of AI\u2019s impact. Dr. Frank has a PhD from MIT\u2019s Media Lab, was a postdoc at MIT Institute for Data, Systems, and Society (IDSS) and the MIT Initiative on the Digital Economy (IDE) and has a master\u2019s degree in applied mathematics from the University of Vermont. <\/p>\n\n\n\n

Project 4:<\/strong> Evaluating College Education in the Age of LLMs
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n

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\"a<\/figure>\n\n\n\n

Dr. Robert Seamans (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

NYU Stern School of Business <\/em><\/p>\n\n\n\n

Dr. Robert Seamans is a Professor at New York University\u2019s Stern School of Business, where he teaches courses in game theory and strategy. His research focuses on how firms use technology in their strategic interactions with each other, and also on the economic consequences of AI, robotics, and other advanced technologies. His research has been published in leading academic journals and cited in numerous outlets, including The Atlantic, Forbes, Harvard Business Review, The New York Times, The Wall Street Journal, and others. Dr. Seamans is also Director of the Center for the Future of Management. In 2015, he was appointed as the Senior Economist for technology and innovation on President Obama\u2019s Council of Economic Advisers. He holds a PhD from UC Berkeley. <\/p>\n\n\n\n

Project 5:<\/strong> Bots and Business School: Lessons for Business Schools in the Era of Generative AI
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Business and Management Contexts <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Arun Sundararajan (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

NYU Stern School of Business <\/em><\/p>\n\n\n\n

Dr. Arun Sundararajan is the Harold Price Professor of Entrepreneurship and Professor of Technology, Operations, and Statistics at NYU Stern School of Business, where he also directs the Fubon Center for Technology, Business, and Innovation, and teaches about AI, digital strategy, and entrepreneurship. His award-winning book, \u201cThe Sharing Economy,\u201d has been translated into multiple languages. He co-chairs the World Economic Forum\u2019s Global Future Council on Data Frontiers and is an expert on the economics of digital goods, network effects, and the regulation of AI and digital platforms. He has published over 50 scientific papers and more than 40 op-eds in major outlets, and his work has earned numerous awards. <\/p>\n\n\n\n

Project 5:<\/strong> Bots and Business School: Lessons for Business Schools in the Era of Generative AI
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Business and Management Contexts <\/p>\n\n\n\n

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Dr. Amy J. Ko (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Washington <\/em><\/p>\n\n\n\n

Dr. Amy J. Ko is a Professor at the University of Washington Information School and the Paul G. Allen School of Computer Science and Engineering. She co-directs the UW Center for Learning, Computing, and Imagination, where she studies computing education, human-computer interaction, and humanity\u2019s individual and collective struggle to understand computing and harness it for creativity, equity, and justice. Alongside her collaborators, she has influenced K\u201312 computer science education policy at local, state, and federal levels. Her work spans more than 140 peer-reviewed publications, with 22 distinguished paper awards and 6 most influential paper awards. She is an ACM Distinguished Member and a member of the SIGCHI Academy. She received her PhD at the Human-Computer Interaction Institute at Carnegie Mellon University and has degrees in Computer Science and Psychology with Honors from Oregon State University. <\/p>\n\n\n\n

Project 6:<\/strong> Imagining Education Futures with Generative AI
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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Dr. Benjamin Shapiro (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Washington <\/em><\/p>\n\n\n\n

Dr. R. Benjamin Shapiro is an Associate Professor and the Associate Director for Community in the Paul G. Allen School of Computer Science & Engineering and in Human-Centered Design & Engineering and Learning Sciences & Human Development at the University of Washington (UW), where he is also co-director of the Center for Learning, Computing, and Imagination. Ben is a learning scientist, and his research concentrates on developing ways for youth and adults to create and use computational media for creative expression, investigation of the world around them, and making positive social change. His award-winning, inter- and trans-disciplinary research engages with topics ranging from AI education and research ethics to feminist re-imagination of science and art education. He earned his PhD in Learning Sciences from Northwestern University and his B.A. in Independent Studies from UC San Diego. <\/p>\n\n\n\n

Project 6:<\/strong> Imagining Education Futures with Generative AI
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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Dr. Karl Gunther (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Florida <\/em><\/p>\n\n\n\n

Dr. Karl Gunther is a historian of the English Reformation. He earned his B.A. in Philosophy and History from Wheaton College (IL), and his M.A. and PhD in History from Northwestern University. His publications include the book\u202fReformation Unbound: Protestant Visions of Reform in England, 1525\u20131590<\/em>\u202f(Cambridge University Press, 2014), which was a finalist for the Royal Historical Society\u2019s Whitfield Prize and runner-up for the American Society of Church History\u2019s Brewer Prize. A fellow of the Royal Historical Society, he has also served as President of the Southern Conference on British Studies. Dr. Gunther was previously Associate Professor of History at the University of Miami, where he taught for fifteen years and held roles including Director of Undergraduate Studies, co-convener of the Medieval and Early Modern Studies Research Group, and chair of the Faculty Senate\u2019s Student Affairs Committee. <\/p>\n\n\n\n

Project 7:<\/strong> Designing Interdisciplinary AI Systems: Challenges and Collaborative Solutions
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Interdisciplinary Nature <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Daniel Maxwell (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Florida <\/em><\/p>\n\n\n\n

Dr. Daniel Maxwell is a humanist at heart, having graduated from a small liberal arts college in Eastern Washington with double majors in History and French. Although his career has focused on technology, Daniel remains committed to the idea and values of a classical liberal arts education. To that end, he positions his work at the intersection of technology and the humanities. Dr. Maxwell is skilled in research system design and open science technologies, including Python, SQL, GitHub, Linux, and deep learning frameworks (PyTorch & TensorFlow). He enjoys helping scholars improve their research workflows through the judicious application of artificial intelligence. Daniel also loves learning Italian and is a student of Italian Renaissance culture, art, and literature. <\/p>\n\n\n\n

Project 7:<\/strong> Designing Interdisciplinary AI Systems: Challenges and Collaborative Solutions
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Interdisciplinary Nature <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Xiaopeng Zhao (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Tennessee <\/em><\/p>\n\n\n\n

Dr. Xiaopeng Zhao is a Professor of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee, Knoxville, specializing in AI and robotics, particularly in healthcare and education. With over 20 years of academic and research experience, he has led innovative AI-driven projects developing assistive technologies to improve life for individuals with disabilities and their caregivers. As founding director of the Applied AI Program at UTK, Dr. Zhao helped establish interdisciplinary AI research and education, fostering collaboration across engineering, healthcare, and policy. He currently serves as an AAAS Congressional Science & Technology Policy Fellow, engaging in legislative work on AI, technology, education, and policy. His expertise bridges academic research, policy, and real-world AI implementation. <\/p>\n\n\n\n

Project 8:<\/strong> Bridging AI Fluency and Workforce Readiness
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI as a New Major\/College <\/p>\n\n\n\n

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Dr. Mehmet Aydeniz (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Tennessee <\/em><\/p>\n\n\n\n

Dr. Mehmet Aydeniz is a Professor of STEM Education and a faculty fellow in the College of Emerging and Collaborative Studies at the University of Tennessee, Knoxville (UTK), where he leads research on innovation in teaching and learning across the K\u201316 continuum. His work focuses on equipping educators and students with the skills needed in a data-driven, AI-powered world. He has published extensively on inquiry-based science education, teacher development, and equity in STEM. He founded COLABS, a research initiative examining scientific collaboration across boundaries. His current research explores how AI integration drives skill turnover and informs curriculum and workforce strategies. He also hosts\u202fNavigating Tomorrow Today in Higher Education<\/em>, a webinar series spotlighting bold ideas for institutional innovation. <\/p>\n\n\n\n

Project 8:<\/strong> Bridging AI Fluency and Workforce Readiness
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI as a New Major\/College <\/p>\n\n\n\n

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Dr. Bassel Daher (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Texas A&M Energy Institute <\/em><\/p>\n\n\n\n

Dr. Bassel Daher is Assistant Director for Sustainable Development at the Texas A&M Energy Institute, Adjunct Assistant Professor of Biological & Agricultural Engineering, and a Research Fellow at the Institute for Science, Technology, and Public Policy. His work applies systems thinking to global challenges such as food system transformation, energy transition, water management, disaster risk reduction, planetary health, and climate action. He promotes evidence-based, cross-sector collaboration to advance sustainable and equitable futures. Daher integrates research, education, network-building, and community engagement, contributing to over $8 million in funding and 70 highly cited publications. He is a frequent international speaker, including a TEDx Talk, and has held research roles at Texas A&M, Purdue, and Qatar Foundation. He serves on the Executive Board of the International Water Resources Association and co-chaired the Zero Hunger Pathways Project (2020\u20132023). <\/p>\n\n\n\n

Project 9:<\/strong> The Evolving Role of Universities in the AI Era: Opportunities for Improving AI Literacy Through Micro-credentials and Interdisciplinary Curriculum Design
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Micro-Credentials and Certifications <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Konstantinos Pappas (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Texas A&M Energy Institute <\/em><\/p>\n\n\n\n

Dr. Konstantinos Pappas is the Associate Director of the Texas A&M Energy Institute. In his 28-year career, he has held senior roles in program management, policy development, and research, including within the European Commission, where he integrated environmental and resource considerations into sustainable development frameworks. Since 2018, he has overseen major projects emphasizing stakeholder engagement in areas such as Carbon Capture and Renewable Technologies. Dr. Pappas\u2019s research focuses on migration economics, international development and sustainability, the societal impacts of energy transition, and stakeholder engagement. Through collaborations with the United Nations Disaster Risk Reduction Office and NATO, his work in the last four years has addressed the interconnected challenges of water, energy, and food in the context of climate change, human mobility, and security. <\/p>\n\n\n\n

Project 9:<\/strong> The Evolving Role of Universities in the AI Era: Opportunities for Improving AI Literacy Through Micro-credentials and Interdisciplinary Curriculum Design
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Micro-Credentials and Certifications <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Kenneth R. Fleischmann (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

The University of Texas at Austin <\/em><\/p>\n\n\n\n

Dr. Kenneth R. Fleischmann is a Professor in the School of Information at The University of Texas at Austin. He is the Founding Chair of the Executive Team for Good Systems, a UT Grand Challenge, and the Founding Director of Undergraduate Studies for the iSchool\u2019s B.A.\/B.S. in Informatics. His research and teaching focus on AI ethics and the role of human values in designing and using information technologies. His work has been funded by the National Science Foundation (NSF), IARPA, Microsoft Research, Cisco Research, Micron Foundation, and the Public Interest Technology University Network. His research has earned awards including the iConference Best Paper Award, ASIS&T SIG-USE Best Information Behavior Conference Paper Award, ALA Library Instruction Round Table Top Twenty Articles, ASIS&T SIG-SI Social Informatics Best Paper Award, ASIS&T SIG-AI Artificial Intelligence Best Paper Award, the Civic Futures Award, and the MetroLab Innovation of the Month Award. He is also the Founding Editor-in-Chief of the ACM Journal on Responsible Computing. <\/p>\n\n\n\n

Project 10:<\/strong> Centering Ethics in the AI Curriculum: Scaling Up AI Ethics Education Nationwide
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> Shift Toward Ethics and Social Sciences <\/p>\n\n\n\n

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Dr. Leo Porter (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of California, San Diego <\/em><\/p>\n\n\n\n

Dr. Leo Porter is a Professor in the Computer Science and Engineering Department at UC San Diego. He is best known for his research on the impact of Peer Instruction in computing courses, the use of clicker data to predict student outcomes, and the development of the Basic Data Structures Concept Inventory. He co-wrote the first book on integrating LLMs into the instruction of programming with Daniel Zingaro, entitled \u201cLearn AI-Assisted Python Programming: With GitHub Copilot and ChatGPT\u201d. He has received six Best Paper Awards, SIGCSE 50th Anniversary Top Ten Symposium Papers of All Time Award, the Outstanding Teaching Award from Warren College, and the Academic Senate Distinguished Teaching Award at UC San Diego. He is a Distinguished Member of the ACM, recently served as Secretary of the SIGCSE Board, and presently serves as Program Chair for ICER. <\/p>\n\n\n\n

Project 11:<\/strong> How Introductory Programming Students Use Generative AI While Coding
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Daniel Zingaro (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Toronto <\/em><\/p>\n\n\n\n

Dr. Daniel Zingaro\u202f<\/strong>is an Associate Teaching Professor at the University of Toronto. He has taught introductory Python programming to thousands of students over the past 15 years and has written both no-GenAI and, with Leo Porter, GenAI Python textbooks. Dan has also authored and co-authored textbooks on algorithms and competitive programming and incorporates as much research-backed instruction as he can into his writing. He is the recipient of the SIGCSE 50th Anniversary Top Ten Symposium Papers of All Time Award, an ICER Best Paper award, and the Computer Science Canada Excellence in Teaching Award. <\/p>\n\n\n\n

Project 11:<\/strong> How Introductory Programming Students Use Generative AI While Coding
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Stephanie Moore (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of New Mexico <\/em><\/p>\n\n\n\n

Dr. Stephanie Moore is an Associate Professor in the Organization, Information, and Learning Sciences program and a Barbara Bush Foundation \/ Dollar General Foundation Fellow. Her research focuses on technology use in adult reading, digital literacies, online and blended learning design, and the ethics of technology in education and the workplace, including AI. Previously, Dr. Moore was an Assistant Professor at the University of Virginia, where she taught instructional design and ethics for learning technologies. She has received multiple awards including the AACTE Innovation of the Year Award and the Leadership in Education award, led and developed award-winning programs, and held leadership roles in AECT. She is Editor-in-Chief of the\u202fJournal of Computing in Higher Education<\/em>\u202fand consults globally through the U.S. Department of State\u2019s US Speakers Program, advising embassies on effective digital learning strategies. <\/p>\n\n\n\n

Project 12:<\/strong> Creating Inter-disciplinary Educational Pathways for AI Leadership
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> Less Focus on Coding <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Victor Law (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of New Mexico <\/em><\/p>\n\n\n\n

Dr. Victor Law is an Associate Professor and Program Director of the Organization, Information, and Learning Sciences (OILS) Program at the University of New Mexico. He has extensive expertise in educational psychology, instructional technology, and the application of technology in learning environments. Dr. Law holds a PhD in Educational Psychology with a concentration in Instructional Psychology & Technology from the University of Oklahoma. His research interests include artificial intelligence in education, ill-structured problem solving, computer-supported collaborative learning, self-regulation, game-based learning, and the adoption and use of technology in education. He has published in top journals and served on the editorial board of major journals such as Educational Technology Research and Development and Interdisciplinary Journal of Problem-Based Learning. <\/p>\n\n\n\n

Project 12:<\/strong> Creating Inter-disciplinary Educational Pathways for AI Leadership
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> Less Focus on Coding <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Fabian Stephany (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Oxford <\/em><\/p>\n\n\n\n

Dr. Fabian Stephany is a Departmental Research Lecturer in AI & Work at the Oxford Internet Institute, University of Oxford, and a Research Affiliate at the Humboldt Institute in Berlin. He leads the SkillScale Project, exploring emerging skills and sustainable occupations amid tech disruption. He co-created the Online Labour Observatory with the ILO. His work has been published in top journals and featured in major media like The New York Times and Nikkei Asia. Dr. Stephany holds a PhD and degrees from institutions including Universit\u00e0 Bocconi and the University of Cambridge and has worked with the UNDP, World Bank, and OECD. <\/p>\n\n\n\n

Project 13:<\/strong> Bridging the AI Skills Gap: Examining AI Literacy, Reskilling Pathways, and Micro-Credentials in the US and UK
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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Dr. Ole Teutloff (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Oxford <\/em><\/p>\n\n\n\n

Dr. Ole Teutloff is an incoming postdoctoral researcher at the Oxford Internet Institute and is affiliated with the Copenhagen Center for Social Data Science. His research uses computational social science methods to study the impact of technological innovations on society. Ole\u2019s work particularly focuses on the labor market implications of transformative AI and the effects of technological change on inequality. He holds a PhD in Social Data Science from the University of Copenhagen, an MSc in Social Data Science from the University of Oxford, and a Master of Public Policy from the Hertie School in Berlin. Previously, he has worked in various international contexts including the Centre for the Governance of AI, the OECD, and the World Bank. <\/p>\n\n\n\n

Project 13:<\/strong> Bridging the AI Skills Gap: Examining AI Literacy, Reskilling Pathways, and Micro-Credentials in the US and UK
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Jeffrey Nii Armah Aryee (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Kwame Nkrumah University of Science and Technology <\/em><\/p>\n\n\n\n

Dr. Jeffrey Nii Armah Aryee is a Lecturer in the Department of Meteorology and Climate Science at Kwame Nkrumah University of Science and Technology (KNUST) in Kumasi, Ghana. He holds a PhD in Meteorology and Climate Science from KNUST, completed under the European Union\u2019s 7th Framework Programme funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud-Interactions in West Africa) Project. Dr. Aryee\u2019s research interests include climate data reconstruction, boundary-layer meteorology, climate variability and change, ML\/AI applications in climate science and climate impact studies. He is the Lead for the JNAA research group (JNAA Lab) and served as the satellite data scientist for the KNUST cohort of the GCRF African SWIFT (Science for Weather Information and Forecasting Techniques) Project. Dr. Aryee is the PI for the ANDeL (Advancing Nowcasting with Deep Learning techniques), Ghana AQ Data Hub and TechAir projects. He also collaborates with an extensive scientific community on other projects such as the EW4ENERGY (Early Warning for Energy) project. He is also the group lead for PY4CA, a scientific computing solutions team involved in building science-related problem-based solutions and applications. <\/p>\n\n\n\n

Project 14:<\/strong> Revolutionizing Tertiary Education for Africa\u2019s Thriving AI Economy and Workforce (RetAIn) Project: Expanding Access to AI Education, Fluency, and Workforce Training
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n\n\n

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Advising Fellows, guiding scholarship with issue-area expertise<\/h3>\n\n\n\n

The AI Economy Institute\u2019s Advising Fellows are a distinguished group of global thought researchers who have expertise in the areas of the AI economy. Their participation in AIEI helps to ensure scholarly rigor and reach across our cohorts. These experts play a pivotal role in shaping AIEI\u2019s intellectual agenda\u2014bringing deep expertise in economics, technology, and workforce transformation to guide research and amplify impact.<\/p>\n\n\n\n

Advising Fellows contribute far beyond proposal review. They participate in virtual and in-person convenings, contribute editorial insights, and help position AIEI as a trusted source of evidence-based guidance on the future of education and work in an AI-driven economy. By affiliating with AIEI, they accelerate the dissemination of research and ideas that inform policy, industry, and academia worldwide.<\/p>\n\n\n\n\n\n

Elizabeth J. Altman (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Massachusetts\u2013Lowell <\/em><\/p>\n\n\n\n

Elizabeth J. Altman is Associate Professor of Management at the University of Massachusetts\u2013Lowell\u2019s Manning School of Business. She is a Research Affiliate with the MIT Initiative on the Digital Economy and a Nonresident Fellow at Brookings, and has held visiting appointments at Harvard Business School. Altman is lead author of Workforce Ecosystems<\/em> (MIT Press, 2023), and her research explores organizational strategy and workforce transformation in the digital economy. <\/p>\n\n\n\n

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G\u00e1bor B\u00e9k\u00e9s (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Central European University <\/em><\/p>\n\n\n\n

G\u00e1bor B\u00e9k\u00e9s is Associate Professor at Central European University in the Department of Economics and Business. He is a Research Affiliate at CEPR and Senior Research Fellow at the KRTK Institute of Economics in Hungary. B\u00e9k\u00e9s co-authored Data Analysis for Business, Economics, and Policy<\/em> (Cambridge University Press, 2021), and his work focuses on applied data analysis and business economics. <\/p>\n\n\n\n

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Daniel Bj\u00f6rkegren (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University <\/em><\/p>\n\n\n\n

Daniel Bj\u00f6rkegren is Assistant Professor of International and Public Affairs at Columbia University\u2019s School of International and Public Affairs. He leads the AI & Development initiative at Columbia\u2019s Center for Development Economics and Policy and is affiliated with BREAD, J-PAL, and the Data Science Institute. Bj\u00f6rkegren\u2019s research examines the intersection of AI and development, including policy-relevant fieldwork in Africa. <\/p>\n\n\n\n

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Anders Humlum (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Chicago Booth School of Business <\/em><\/p>\n\n\n\n

Anders Humlum is Assistant Professor of Economics and Fujimori\/Mou Faculty Scholar at the University of Chicago Booth School of Business. He is a Research Affiliate at IZA and previously held a postdoctoral fellowship at the Becker Friedman Institute. Humlum\u2019s research focuses on the labor market impacts of automation and artificial intelligence. <\/p>\n\n\n\n

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Frank Nagle (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

MIT Initiative on the Digital Economy <\/em><\/p>\n\n\n\n

Frank Nagle is a Research Scientist at the MIT Initiative on the Digital Economy and advises the Linux Foundation as Chief Economist. He previously served as Assistant Professor of Strategy at Harvard Business School. Nagle\u2019s work includes widely cited research estimating the multi-trillion-dollar economic value created by open-source software. <\/p>\n\n\n\n

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Gal Oestreicher-Singer (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Tel Aviv University <\/em><\/p>\n\n\n\n

Gal Oestreicher-Singer is Mexico Professor of Information Systems and Associate Dean for Research at the Coller School of Management, Tel Aviv University. She is an Adjunct Professor at NYU Stern and has held senior editorial roles in MIS journals. Oestreicher-Singer\u2019s research examines digital platforms, social networks, and e-commerce, and she is a recent recipient of the Kadar Family Award. <\/p>\n\n\n\n

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Daniel Rock (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

The Wharton School at the University of Pennsylvania <\/em><\/p>\n\n\n\n

Daniel Rock is Assistant Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania. He is a Digital Fellow at the MIT Initiative on the Digital Economy and affiliated with NBER and Stanford\u2019s Digital Economy Lab. Rock co-authored the Science article \u201cGPTs are GPTs\u201d (2024) and the AEJ: Macroeconomics paper on the \u201cProductivity J Curve.\u201d <\/p>\n\n\n\n

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Wesley Rosslyn Smith (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Pretoria <\/em><\/p>\n\n\n\n

Wesley Rosslyn Smith is Associate Professor in the Department of Business Management at the University of Pretoria and Director of the Centre for the Future of Work. He also lectures at the Gordon Institute of Business Science. Rosslyn Smith\u2019s research and teaching focus on corporate strategy, turnaround management, business analytics, and the future of work. <\/p>\n\n\n\n

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Fabian Stephany (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Oxford <\/em><\/p>\n\n\n\n

Fabian Stephany is Departmental Research Lecturer in AI and Work at the Oxford Internet Institute, University of Oxford. He is a Senior Research Fellow at the Oxford Martin School and a Fellow at Bruegel, and co-created the Online Labour Observatory with the ILO. Stephany serves on the World Economic Forum\u2019s Global Future Council on Human Capital Development. <\/p>\n\n\n\n

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Prasanna (Sonny) Tambe (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

The Wharton School at University of Pennsylvania <\/em><\/p>\n\n\n\n

Prasanna Tambe is Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania, where he co-directs AI at Wharton. He is a Digital Fellow at the MIT Initiative on the Digital Economy and affiliated with NBER. Tambe\u2019s research explores the economics of technology and labor, including widely cited work on AI in human resource management. <\/p>\n\n\n\n

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Mary Gray (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Microsoft Research<\/em><\/em><\/p>\n\n\n\n

Mary L. Gray is a Senior Principal Researcher at Microsoft Research and Principal Investigator of Project Resolve, an initiative focused on helping community-based organizations govern and secure their AI futures. An anthropologist and media scholar, she studies the impact of technology on work, society, and digital economies.<\/p>\n\n\n\n\n\n

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Interested in becoming an advisor, share research question ideas or have general questions – contact us (opens in new tab)<\/span><\/a>!<\/p>\n\n\n\n

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AI Economy Institute Cohort 3 Open Call<\/h2>\n\n\n\n
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About AI Economy Institute<\/h3>\n\n\n\n

Launched in 2025, Microsoft\u2019s AI Economy Institute (AIEI) supports independent, policy-relevant research on how artificial intelligence is reshaping productivity, labor markets, education systems, and economic opportunity, worldwide. AIEI advances rigorous scholarship that informs policymakers, educators, employers, and workers as societies adapt to the rapid diffusion of generative AI.  The institute emphasizes scholarship that is immediately translatable top policy, decision-making, and investment.<\/p>\n\n\n\n

All research supported by AIEI is conducted independently. Findings, interpretations, and conclusions are those of the authors and do not represent the views of Microsoft.<\/em><\/p>\n\n\n\n

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AIEI research to date<\/h3>\n\n\n\n

Since its launch, the AI Economy Institute has convened two research cohorts through open and targeted Calls for Proposals, supporting independent scholarship across a range of topics related to AI\u2019s economic and societal impacts.<\/p>\n\n\n\n

Previous cohorts have focused on studying:<\/p>\n\n\n\n