Assistant Professor Yang focuses her research in the field of data mining, including Web mining, market segmentation, predictive modeling, Internet marketing and formal modeling in e-commerce. She is interested in developing a way to better integrate data mining and Internet marketing to analyze consumer behavior, giving companies tools to make better choices for committing revenue streams to personalized and targeted advertising and marketing. Her research papers include “A Knowledge Driven Approach to the Evaluation of Online Personalization Systems,” “A Pattern-Based Approach to Segmenting Customer Transactions,” and “Free-Shipping Promotions and Internet Shopping.”

Most recently, Yang and her co-author Assistant Professor Balaji Padmanabhan of The Wharton School of the University of Pennsylvania have developed a method for identifying users based on their online browsing behavior. In their study titled "Clickprints on the Web: Are There Signatures in Web Browsing Data?" the authors develop formal methods to determine the optimal amount of user data that must be aggregated before unique clickprints can be deemed to exist. Their main objective with this method is to deter online fraud, which costs the Internet economy billions of dollars annually. But the same information could also be valuable for Web marketers.

Yang earned her Ph.D. in operations and information management from the Wharton School at the University of Pennsylvania in 2004. Before earning her doctorate, she earned a M.A. in managerial science and applied economics from the Wharton School. She received her B.E. in management of information systems from the School of Economics and Management at Tsinghua University in China, where she was named as the outstanding student four consecutive years from 1995 to 1998.