Wen Wang Directory Page

Wen Wang is an Assistant Professor in the Department of Decision, Operations, and Information Technologies at the Robert H. Smith School of Business, University of Maryland, College Park. She earned her Ph.D. in Information Systems from the Heinz College of Carnegie Mellon University. 

Her research develops interpretable, actionable, and governable deep learning and generative AI methods to improve business decision-making and social welfare. Her work spans three closely related areas: (1) interpretable AI for market decisions and customer analytics, (2) human-centered AI for societal outcomes and well-being, and (3) responsible AI for privacy, data governance, and the broader welfare implications of generative AI.

Her research has appeared in premier academic journals, including Information Systems Research and Management Science. She has received several prestigious recognitions, including the Gerard J. Tellis Award for Excellence in Research at the AIM Conference; Best Paper Award Nominee at WISE; Kauffman Best Student Paper Award Nominee at ICIS; and the Best Paper Award in the Digital Innovation Track at ICIS.

Publications

• Wen Wang, Beibei Li, Xueming Luo, Xiaoyi Wang (2022) Deep Reinforcement Learning for Sequential Targeting. Management Science 69(9):5439-5460.
• Wen Wang, Beibei Li (2024) Learning Personalized Privacy Preference from Public Data. Information Systems Research 36(2):761-780.
• Wen Wang, Mi Zhou, Beibei Li, Honglei Zhuang (2025) Predicting Instructor Performance in Online Education: An Interpretable Hierarchical Transformer with Contextual Attention. Information Systems Research 36(4):2327-2343.
• Wen Wang, Siqi Pei, Tianshu Sun (2025). Unraveling Generative AI from A Human Intelligence Perspective: A Battery of Experiments. Information Systems Research, forthcoming.