Ph.D. in Management (Finance), Rutgers Business School, Rutgers University, NJ, 2013
Thesis: “Housing Bubbles: Testing, Estimation, and Fundamental Analysis”
M.S. in Quantitative Finance, Rutgers Business School, Rutgers University, NJ, 2009
M.A. in Computer Science, The City University of New York – Queens College, NJ, 2008
B.S. in Computer Science, Wuhan University of Technology, China, 2006
Business Analytics, Big Data, Asset Pricing, Bubbles and Crises
Office: Harriman Hall 346
- JOURNAL ARTICLES
Xiao, K., Liu, Q., Liu, C., & Xiong, H. Price Shock Detection with an Influence-Based Model of Social Attention. ACM Transactions on Management Information Systems (TMIS), forthcoming.
Fabozzi, F. J., & Xiao, K. Explosive Rents: The Real Estate Market Dynamics in Exuberance. The Quarterly Review of Economics and Finance, forthcoming.
Liu, C., Xiong, H., Papadimitriou, S., Ge, Y., & Xiao, K. (2017). A Proactive Workflow Model for Healthcare Operation and Management. IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(3), 586-598.
Chen, H., Xiao, K., Sun, J., & Wu, S. (2017). A Double-Layer Neural Network Framework for High-Frequency Forecasting. ACM Transactions on Management Information Systems (TMIS), 7(4), 11.
Chen, J., & Xiao, K. (2010). BISC: A Bitmap Itemset Support Counting Approach for Efficient Frequent Itemset Mining. ACM Transactions on Knowledge Discovery from Data (TKDD), 4(3), 12.
- REFEREED CONFERENCE PROCEEDINGS
Zhang, L., Xiao, K., Liu, Q., Tao, Y., & Deng, Y. (2015). Modeling Social Attention for Stock Analysis: An Influence Propagation Perspective. The Proceedings of the 2015 IEEE International Conference on Data Mining (ICDM’15). pp 609-618. IEEE
Liu, C., Ge, Y., Xiong, H., Xiao, K., Geng, W., & Perkins, M. (2014). Proactive Workflow Modeling by Stochastic Processes with Application to Healthcare Operation and Management. The Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’14). pp. 1593-1602. ACM.
Ge, Y., Xiong, H., Tuzhilin, A., Xiao, K., Gruteser, M., & Pazzani, M. (2010). An Energy-Efficient Mobile Recommender System. The Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’10). PP. 899-908. ACM.
“Applying Simulated Annealing and Parallel Computing to the Mobile Sequential Recommendation” (with Zeyang Ye, Yong Ge, and Yuefan Deng). submitted to IEEE Transactions on Knowledge and Data Engineering (under the 2nd round review).
“The Timeline Estimation of Bubbles: The Case of Real Estate” (with Frank J. Fabozzi), submitted to Real Estate Economics (under the 4th round review).
“Exploring Information Value in Price Shock Prediction: A Machine Learning Framework” (with Jinwen Sun, Chuanren Liu, Wenjun Zhou, and Hui Xiong).