Dr. Hsieh is currently an Assistant Professor of Management Sciences in the Department of Information Systems and Supply Chain Management. She received her Ph.D. degree in Statistics from the Stern School of Business, NYU in 2006. She has over eight years of applied research experience at diverse private organizations, including IBM Research, Morgan Stanley, Credit Suisse, and Activision. Her current research interests are applied statistics in supply chain management and predictive analytics.
Time Series Analysis, Financial Econometrics, Predictive Analytics
Statistics, Regression Model and Data Analysis, Forecasting Time Series Data
- Hsieh, M., Hurvich, C., & Deo, R. (2010). Long Memory in Intertrade Durations, Counts and Realized Volatility of NYSE Stocks. Journal of Statistical Planning and Inference, 140 (12), 3715-3733.
- Deo, R., Hsieh, M., Hurvich, C., & Soulier, P. (2006). Long Memory in Nonlinear Processes. Dependence in Probability and Statistics, Lecture Notes in Statistics, Vol. 187. Springer [B].
Presentation of Refereed Papers
- Hsieh, M., Giloni, A., Hurvich, C., & Simonoff, J. (2016, November). Statistical Learning and Optimal Decisions. INFORMS, Nashville, Tennessee.
- Hsieh, M., Giloni, A., & Hurvich, C. (2016, May). Impact of Exponential Smoothing on Inventory Costs in Supply Chains. POMS Annual Meeting, Orlando, Florida.
Papers Under Review
Hsieh, M., Giloni, A., & Hurvich, C. (2016). "Impact of Exponential Smoothing on Inventory Cost in Supply Chains," Revision under 2nd review to Production and Operations Management.
- Hsieh, M., Giloni, A., Simonoff, J., & Hurvich, C. (2017). "Statistical Learning and Optimal Decisions."
- Hsieh, M., Hurvich, C., & Soulier, P. (2017). "Modeling Leverage and Long Memory Volatility in a Pure Jump Process."
- 2011 - Method and Apparatus for Workforce Demand Forecasting. (# 8015043)
- 2008 - Method and Structure for Generic Architecture for Integrated End-to-End Workforce Management. (# 0167929 A1)
- 2008 - Method and Structure for End-to-End Workforce Management. (# 0167930 A1