Skip to content

General Contact Information


Phone: 646-660-6500

Fax: 646-660-6501




Mailing Address:

Office of the Provost & Senior Vice President for Academic Affairs

Baruch College/CUNY

One Bernard Baruch Way
Box D-701

New York, NY 10010-5585


Walk-In Address:

Administrative Center

135 East 22nd Street, 7th Floor

Office of the Provost and Senior Vice President for Academic Affairs

Message Archive

Monday, November 21, 2016


This email is being sent to all members of the Baruch College faculty.

For an archive of announcements sent from the Associate Provost beginning June 2011, click here.


From:  Prof. Rongning Wu, Paul H. Chook Department of Information Systems and Statistics


The Information Systems and Statistics Research Seminar Series

Presented by the Paul H. Chook Department of Information Systems and Statistics

“Survival Analysis Approach to Demand Forecasting in a Request-Based Service System”
Dr. Ta-Hsin Li, IBM T. J. Watson Research Center
Tuesday, November 29, 12:30 - 1:45pm, NVC 11-217

In some service businesses, service requests are initiated by the customer who specifies not only what type of service is needed but also when it is needed. Recorded in a service request management system, these requests are utilized to forecast the demand of different categories of service at different time horizons. Because the requests are subject to revision, the customer-specified time of service is not entirely reliable for demand forecasting. In this talk, we consider a resource-pool based software development service operation and discuss a survival analysis approach that explores the statistical characteristics of historical request data with the aim of providing more accurate demand forecasts. The survival models are constructed on the basis of a large hierarchy of requests, defined by the demand categories and the customers. A nonparametric approach is taken to handle the large scale of the hierarchy and the diversity of survival patterns. We also employ the regularized Cox's proportional hazards regression method and the Dirichlet-prior-based empirical Bayesian method to overcome the inevitable challenge of data sparsity in training the category- and customer-specific survival functions. Different techniques of estimating the hyperparameter are compared for their performance in demand forecasting.

Dr. Ta-Hsin Li is a Research Staff Member at the IBM T. J. Watson Research Center, Yorktown Heights, NY. He is also an Adjunct Professor at Columbia University. He received the Ph.D. degree in applied mathematics from the University of Maryland, College Park, in 1992. Before joining IBM in 1999, he was on the faculty of the Statistics Department at Texas A&M University, College Station (1992–1997) and the Statistics and Applied Probability Department at the University of California, Santa Barbara (1998–2000). His current research interests include statistical methods for business applications, time series analysis, and statistical signal processing. Dr. Li is a Fellow of the American Statistical Association (ASA) and a Senior Member of the Institute of Electrical and Electronic Engineers (IEEE).


Rongning Wu, Ph.D.
Associate Professor
Zicklin School of Business and Graduate Center
The City University of New York
One Bernard Baruch Way, Box B11-220
New York, NY 10010
Tel: 646-312-3404
Fax: 646-312-3351