Jingjing Li is a member of TYDE’s Post-doctoral Research Committee.
As a professor of UVa’s McIntire School of Commerce, Li’s research interests are in artificial intelligence and big data analytics, with applications spanning search engines, healthcare, marketing, platforms, and public policy. Her work has been published in prestigious journals, including MIS Quarterly; Information Systems Research; Journal of Marketing; Strategic Management Journal; Review of Economics and Statistics; Journal of Management Information Systems; and ACM Transactions on Information Systems (TOIS). She has received several accolades for her research, such as the INFORMS Design Science Award, CIST Best Paper Award, INFORMS Data Science Workshop Best Paper Award, WITS Best Paper Award, and WITS Best Prototype Award. Her research was also a finalist for the Shelby D. Hunt/Harold H. Maynard Award. Her projects have received funding from notable institutions and companies, including NSF, Amazon, Google, Microsoft, the Jefferson Trust, and the UVA Data Analytics Center (Analytics Resource Award). Currently, she serves as an associate editor for MIS Quarterly.
Professor Li teaches courses on big data and business analytics at undergraduate, graduate, and executive master levels. She has been recognized for her excellence in teaching, receiving an award for her Business Intelligence course at the Leeds School of Business at the University of Colorado Boulder, and was named Poets&Quants Best Undergraduate Professor in 2023. Prior to her tenure at the McIntire School, she worked as a Scientist at Microsoft, where she developed several large-scale machine learning solutions for various Microsoft products and services. She is a member of the Association for Information Systems (AIS) and the Institute for Operations Research and the Management Sciences (INFORMS).
Read Jingjing's Spotlight