My main research revolves around the topic of algorithmic decision-making and consists of three connected streams. In the first stream of work, I study the problem of designing theoretically robust and computationally efficient algorithms and strategies to support decision-making in information-intensive marketplaces. In the second stream of work, I examine the antecedents of algorithmic decision-making as well as its impact on decision quality, fairness, and privacy. In the third stream of work, I design novel approaches to draw robust statistical inference with variables generated by machine learning algorithms.
Before joining Carlson, I was an Assistant Professor in the Department of Operations and Decision Technologies at Kelley School of Business, Indiana University. I received my Ph.D. from the Department of Information and Decision Sciences at Carlson School of Management, University of Minnesota. My advisors are Yuqing Ren and Gediminas Adomavicius. My dissertation studies the user-generated content and associated user engagement behavior on company-managed social media pages. I obtained my bachelor’s degree in Information Systems and Information Management from the School of Economics and Management at Tsinghua University.