Prof. Lenk develops Bayesian models that disaggregate data to address individuals. He also studies Bayesian nonparametric methods and currently consider shape constraints. Prof. Lenk teaches and uses data mining methods such as recursive partition and neural networks.
Jun Li, PhD, is Assistant Professor in the department of Technology and Operations in the Ross School of Business at the University of Michigan, Ann Arbor.
Jun Li’s main research interests are empirical operations management and business analytics, with special emphases on revenue management, pricing, consumer behavior, economic and social networks. She has worked extensively with large-scale data, including transactions, pricing, inventory and capacity, consumer online search and click stream data, supply chain relationships and disruptions, clinical and healthcare claims. She is the Winner of INFORMS Revenue Management and Pricing Practice Award for her close collaboration with retailing practitioners in implementing best response pricing algorithms. Her paper on airline pricing and consumer behavior is the finalist for Best Management Science Papers in Operations Management 2012 to 2014. She is also the principal investigator of a National Science Foundation funded project: “Gaining Visibility Into Supply Network Risks Using Large-Scale Textual Analysis”. Her work has enjoyed coverage by The Economist, New York Times and Forbes.