Sheldon Jacobson

Sheldon H. Jacobson is a Founder Professor in the Department of Computer Science at the University of Illinois Urbana-Champaign.  His research focuses on data-driven risk-based decision-making applied to problems in homeland security, public health, public policy, and sports.  Hi research on risk-based airport security contributed to the design of TSA PreCheck.  He has received numerous awards for his research, including a John Simon Guggenheim Memorial Foundation Fellowship, the INFORMS Saul Gass Expository Writing award, and the INFORMS Presidents Award.  He is an elected Fellow of INFORMS and the American Association for the Advancement of Science (AAAS).

David Jurgens

David Jurgens is an Associate Professor jointly in the School of Information and department of Computer Science and Engineering at the University of Michigan. He obtained his PhD in Computer Science from the University of California, Los Angeles. His research centers on language technologies for social understanding and on behavioral analysis through language. His work has been recognized by the Cozzarelli Prize from the National Academy of Science, Cialdini Prize from the Society for Personality and Social Psychology, multiple best paper awards and nominations (e.g,. ACL, ICWSM), and an NSF CAREER award. 

Louise Keely

Louise is a leader in Bain’s Advanced Analytics practice. She has 25+ years' professional experience in advanced analytics and customer strategy, with a focus on retail and other consumer-facing industries.

She has advised clients on customer-led strategic transformations that incorporated significant use of data science and analytics to inform recommendations. She has guided clients on the strategy and design of data and analytics functions, including the demonstration of the use of analytics to solve critical business questions, the design of the organizational structure, the roles of the new function, and its commercial goals and KPIs. She has also worked with clients on their Engine 2 strategies, to build new businesses to serve their customers and were adjacent to core capabilities.  Most recently, Louise has advised clients on their Generative AI strategy, use case development, and implementation.

Before Bain, Louise was a principal and held leadership roles at other major consulting firms and in industry. Louise also spent several years as an economics professor and researcher. Louise started her career at Bain as an associate consultant.   

Louise has a B.Sc. in international economics from Georgetown University, a M.Sc. in econometrics and mathematical economics and a Ph.D. in Economics from the London School of Economics. 

Louise is a noted writer and speaker on the topic of global consumer demand shifts and their implications for business strategy and investment priorities, as well as on trends in consumer data and analytics strategy and business models to capture value for enterprises.

Anjana Susarla

Anjana Susarla holds the Omura-Saxena Professorship in Responsible AI at the Broad College of Business of Michigan State University. She earned an undergraduate degree in Mechanical Engineering from the Indian Institute of Technology, a graduate degree in Business Administration from the Indian Institute of Management and a Ph.D. in Information Systems from the University of Texas at Austin. Her research interests include the economics of information systems and artificial intelligence. Her work has appeared in several academic journals and peer-reviewed conferences such as such as Conference on International Conference in Learning Representations, Information Systems Research, Knowledge Discovery and Data Mining, Journal of Management Information Systems, Management Science, MIS Quarterly and Neurips. She is on the editorial boards of leading journals and serves on program committees of major international IS conferences and workshops. She has been a recipient of several best paper awards at international conferences and peer-reviewed publications. She has worked in consulting and led experiential projects with several companies. Her work has also been quoted in several media outlets such as the Associated Press, BBC News, Bloomberg, Newsweek, NPR, PBS, The Conversation, and Pew Research. 

Moontae Lee

Moontae Lee is an assistant professor of Information and Decision Sciences at the University of Illinois Chicago. Concurrently, he leads the Advanced Machine Learning Laboratory at LG AI Research as a research fellow. His journey to Large Language Models started when he was invited to Microsoft Research Redmond as a visiting scholar on 2019. Then, he continued to work multiple years as a consulting professor of the Deep Learning Group for the ambitious Universal Language Modeling projects. Moontae received his Ph.D. in Computer Science from Cornell University, where he worked on machine learning and natural language understanding. He received his MS in Computer Science from Stanford University, where he specialized in Artificial Intelligence. He holds a BS in Computer Science, BS in Mathematics, and BA in Psychology from Sogang University. Moontae has served as an area chair/senior program committee of NeurIPS, ICML, ICLR, ACL, NAACL, EMNLP, AAAI, AISTATS, and CVPR. Beyond the machine learning communities, his work was recognized by the Operations Research and Management Information Systems community by winning the Best Paper award at INFORMS 2017. His research in computational social science won a research award from Amazon.

Lajanugan Logeswaran

Lajanugen Logeswaran is a Senior Research Scientist at LG AI Research. He received his PhD from the University of Michigan, where he made fundamental contributions to text representation learning. His recent work aims to leverage knowledge available in the form of language for building agents that learn to perform useful tasks in real and virtual environments. His research has been published in top Machine Learning and Natural Language Processing venues such as ICML, Neurips, ICLR, AAAI, NAACL, ACL and EMNLP. His work on zero-shot entity linking received a best paper nomination at ACL 2019. During his PhD, he has spent time at Google Brain and Facebook AI as a research intern.

Sebastien Martin

Sebastien Martin is an Assistant Professor of Operations at Kellogg. He received his Ph.D. in operations research from MIT and an M.Sc. in applied mathematics at Ecole Polytechnique. Before joining Kellogg, he was a postdoctoral research fellow at the ridesharing company Lyft. He is a twice Edelman Award Laureate (2019 and 2023) and has received the George Dantzig and TLS Society dissertation awards. 

His research examines the interface between humans and algorithms in public sector operations and online platforms, focusing on prescriptive analytics and motivated by real-world impact. He designed Lyft's dispatch algorithm, increasing drivers' yearly revenue by tens of millions. He also optimized the school transportation systems of Boston and San Francisco, enabling millions of dollars to be reinvested every year in children's education while increasing fairness. 

Brad Sturt

Brad Sturt is an assistant professor of business analytics at the University of Illinois Chicago, which he joined in Fall 2020. He completed his PhD in Operations Research from MIT in Spring 2020. Prior to that, Brad graduated with highest honors from the University of Illinois at Urbana-Champaign with a BS in Computer Engineering and a minor in Technology and Management.

His research interest is optimization under uncertainty with a focus on applications in operations, revenue management, and the public sector. Brad is also broadly interested in using robust optimization to design tractable approaches for dynamic optimization problems. His work has received several recognitions, including second place in the INFORMS Junior Faculty Interest Group (JFIG) Paper Competition and second place in the INFORMS George Nicholson Student Paper Competition.

At UIC, Brad teaches MBA and undergraduate classes on operations management and business analytics. As a graduate student, he received the MIT Sloan Outstanding Teaching Assistant Award (selected once per year by MBA students) and co-organized a student-run class on software tools for statistics and optimization.