About
Mochen Yang’s main research revolves around the topic of algorithmic decision making and consists of three connected streams. The first stream of work explores the problem of designing theoretically robust and computationally efficient algorithms and strategies to support decision making in information-intensive marketplaces. The second stream of work examines the antecedents of algorithmic decision making as well as its impact on decision quality, fairness, and privacy. The third stream of work focuses on the design of novel approaches to draw robust statistical inferences with variables generated by machine learning algorithms.
Before joining Carlson, Yang was an Assistant Professor in the Department of Operations and Decision Technologies at the Indiana University Kelley School of Business. He received his PhD from the Department of Information and Decision Sciences at the University of Minnesota Carlson School of Management. Yang’s dissertation studies user-generated content and associated user engagement behavior on company-managed social media pages. He obtained his bachelor’s degree in Information Systems Management from the School of Economics and Management at Tsinghua University.