Workshop on AI & Analytics for Social Good
April 24, 2026
This workshop brings together academics, thought leaders and stakeholders to discuss how analytics can support nonprofit organizations, government entities and social impact organizations in improving their reach and impact through innovative use of data and models. The overarching theme is analytics for doing good.
Speakers

Keynote Speaker: Georgia Perakis
Georgia Perakis is a Professor of Operations Management, Operations Research & Statistics at the MIT Sloan School of Management. She has been on the faculty at MIT Sloan since July 1998.
Perakis teaches courses and performs research in analytics/AI, in particular in the intersection of optimization and machine learning with applications in pricing, revenue management, supply chain, and healthcare among others. At MIT over the years, she has taught in a variety of programs such as undergraduate, MSc, PhD, MBA, and EMBA programs across MIT. For her teaching, Perakis won the Graduate Student Council Teaching Award in 2002 as well as the Jamieson Prize in 2014 for excellence in teaching, and the Teacher of the Year award (among all faculty at the MIT Sloan School) in 2017.

Keynote Speaker: Cynthia Rudin
Cynthia Rudin is the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science at Duke University. She directs the Interpretable Machine Learning Lab, and her goal is to design predictive models that people can understand. Her lab applies machine learning in many areas, such as healthcare, criminal justice, and energy reliability. She holds degrees from the University at Buffalo and Princeton. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (the “Nobel Prize of AI”), as well as the INFORMS Society of Data Mining Prize in 2024. She received a 2022 Guggenheim fellowship, and is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Association for the Advancement of Artificial Intelligence.
Invited Speakers
Gordon Burtch
Gordon Burtch is the Allen and Kelli Questrom Professor of Information Systems and a fellow of the Digital Business Institute at Boston University’s Questrom School of Business. His research focuses on the economic evaluation of information systems, using econometrics and field experiments to examine participation in online social contexts, and has appeared in leading journals including Management Science, MIS Quarterly and Information Systems Research. Burtch is the recipient of multiple early career and best paper awards, has secured more than $2 million in research funding from public and private sponsors, and regularly serves in editorial and leadership roles for top journals and conferences. Before academia, he worked as an information systems auditor, hardware design engineer and technology consultant, and he teaches graduate courses in data analytics and IT management.
Yanchong (Karen) Zheng
Yanchong (Karen) Zheng is the George M. Bunker Professor and an associate professor of operations management at the MIT Sloan School of Management. Her research focuses on operations and supply chain management, with an emphasis on data-driven decision-making. Zheng earned her Ph.D. from Stanford University and holds bachelor’s and master’s degrees from Tsinghua University in China.
Organizing Committee
- Hamsa Bastani, Wharton University, hamsab@wharton.
upenn.edu - Margret Vilborg Bjarnadottir (Co-Chair), mbjarnad@umd.edu
- Jui Ramaprasad (Co-Chair), jramapra@umd.edu
- Jessica Clark, jmclark@umd.edu
- John Silberholz, josilber@umd.edu
Important Dates
- Abstract deadline: February 14, 2026
- Notification of Acceptance: March 1, 2026
- Conference Date: April 24, 2026
Recommended Hotel
Submission Instructions
We invite scholars at universities and other research institutions working on analytics (broadly defined) for good as well as policymakers who frame their policies using business analytics. We are agnostic about the topic of research provided it fits into the workshop theme. We particularly encourage young scholars, junior faculty and PhD students to submit papers.
Submission Requirements: Please submit a 3-page extended abstract (page limit excludes references). In the submission, please include the title of the paper and the names and email addresses of all of the authors, and highlight the research questions/goals, novelty, methodological approach, main results, and impact or potential for impact.
Abstracts should be submitted by email to socialimpactanalytics@umd.edu.
Decisions will be released on March 1, 2026.