Kejia Hu Short Bio
Kejia Hu is a scholar in operations management, currently a Brownlee O. Currey Jr. Dean's Faculty Fellow and Assistant Professor at Vanderbilt University's Owen Graduate School of Management. She focuses on unlocking business value from data. Hu's domain expertise lies in service operations, artificial intelligence, and business analytics. She has worked with industrial partners, including L'Oreal, Marriott International, Dell, Alibaba, and Vanderbilt University Medical Center, with research published in journals that include Manufacturing & Service Operations Management, Production and Operations Management, Applied Energy, and Energy Policy. With a Ph.D. from Kellogg School of Management at Northwestern University, an M.S. in Statistics from the University of California - Davis, and a B.S. in Statistics from Fudan University, Hu specializes in causal inference, statistical forecasting, and stochastic modeling. Hu frequently serves as session chairs and track chairs of service operations, sustainability operations, and emerging business models at INFORMS and POMS annual conferences. Her research has been recognized with several Best Paper Awards at INFORMS, POMS, and MSOM. Hu's case Jointown Pharmaceutical Group is named one of the Top 100 MBA Case Studies in China. Hu also serves at the Cornell Institute for Healthy Futures, on the Member Engagement Committee at POMS College of Service Operations, and on Vanderbilt Provost's WAVE Council. Previously, she worked at Lawrence Berkeley National Lab, Morgan Stanley, and the Yiwu Government -- the world's largest wholesale market.
Kejia Hu's Philosophy: Unlock Business Insights from Data
My 4-step “DEFI” approach
Collect Data ==> Launch Exploration ==> Discover Finding ==> Deliver Insights
Unlocking business insights from data requires a combination of domain knowledge and methodology expertise. A successful unlocking requires mindful searches, deliberate pauses to digest the intermediate findings, and constant connections with strategy-level business perspectives and operational-level business practices. Such unlocking is rarely a one-time event, but a progression that continuously pushes the business frontier and develops data assets.
📖 Domain Expertise
🔭 Methodology Expertise
Structural Modeling and Causal Inference Statistical Forecasting and Machine Learning