Henry Lam

Department of Mathematics and Statistics

Boston University

111 Cummington Mall

Boston, MA 02215

Phone: 617-358-2394

Email: khlam (at) bu.edu


I am currently an Assistant Professor in the Department of Mathematics and Statistics in Boston University, and am moving to the Industrial & Operations Engineering Department in University of Michigan, Ann Arbor from January 2015.


My research focuses on building computation tools to analyze decisions and to manage risk under stochastic environment. The goal is to construct methodologies that can handle complex dynamics, are model-robust, and can effectively incorporate data. Methodologically, I use a combination of Monte Carlo methods, simulation optimization and statistics. Regarding applications, I am broadly interested in engineering operations, service systems, and risk management.


I received my Ph.D. degree in statistics at Harvard University in 2011, under the supervision of Professor Jose Blanchet. I am also affiliated with the Center for Information Systems and Engineering, and am a Croucher scholar in Hong Kong.

My recent work and CV.


·         MA570: Stochastic Methods in Operations Research: Spring 2014

·         MA569: Optimization Methods in Operations Research: Fall 2011 | Fall 2012 | Fall 2013

·         MA116: Statistical Methods II: Spring 2012 | Spring 2013 | Spring 2014

·         MA881: Graduate Seminar in Applied Probability: Fall 2011

Research Projects

Robust Measurement of Stochastic Model Uncertainty

·         Sensitivity to serial dependency of input processes: a robust approach, submitted.

·         Robust sensitivity analysis for stochastic systems, under minor revision in Mathematics of Operations Research. INFORMS Junior Faculty Interest Group (JFIG) Paper Competition 2012 Finalist.

·         Reconstructing input models via simulation optimization, with A. Goeva and B. Zhang, Proceedings of the Winter Simulation Conference (WSC) 2014.

·         Robust rare-event performance analysis with natural non-convex constraints, with J. Blanchet and C. Dolan, Proceedings of the Winter Simulation Conference (WSC) 2014.

·         Iterative methods for robust estimation under bivariate distributional uncertainty, with S. Ghosh, Proceedings of the Winter Simulation Conference (WSC) 2013.

·         Asymptotic approximations of input model errors in steady-state estimation, with X. Chen, preprint.

·         A stochastic optimization approach to assessing model uncertainty, with S. Ghosh, preprint.


Efficient Monte Carlo Methods for Systems and Risk Management

·         Rare-event simulation for many-server queues, with J. Blanchet, Mathematics of Operations Research, 39(4), 1142-1178, 2014. Honorable Mention Prize in INFORMS George Nicholson Paper Competition 2010.

·         Efficient rare-event simulation for perpetuities, with J. Blanchet and B. Zwart, Stochastic Processes and Their Applications, 122(10), 3361–3392, 2012.

·         State-dependent importance sampling for rare-event simulation: recent advances, with J. Blanchet, Surveys in Operations Research and Management Science, 17(1), 38-59, 2012. Shortened version appeared in Proceedings of the Winter Simulation Conference (WSC) 2011.

·         Efficient importance sampling under partial information, Proceedings of the Winter Simulation Conference (WSC) 2012.

·         Importance sampling for actuarial cost analysis under a heavy traffic model, with J. Blanchet, Proceedings of the Winter Simulation Conference (WSC) 2011.

·         Rare-event simulation for a slotted time M/G/s model, with J. Blanchet and P. Glynn, Queueing Systems: Theory and Applications, 63, 33-57, 2009.


Applied Probability and Risk Analysis

·         Uniform large deviations for heavy-tailed queues under heavy traffic, with J. Blanchet, submitted.

·         Exact asymptotics for infinite-server queues. Preliminary version appeared in Proceedings of the 6th International Conference on Queueing Theory and Network Applications 2011.

·         Two-parameter sample path large deviations for infinite server queues, with J. Blanchet and X. Chen, Stochastic Systems, 4(1), 206-249, 2014.

·         A heavy traffic approach to modeling large life insurance portfolio, with J. Blanchet, Insurance Mathematics and Economics, 53(1), 237-251, 2013.

·         Information dissemination via random walks in d-dimensional space, with Z. Liu, M. Mitzenmacher, X. Sun and Y. Wang, Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA) 2012. Full version.

·         Chernoff-Hoeffding bounds for Markov chains: generalized and simplified, with K. M. Chung, Z. Liu and M. Mitzenmacher, Proceedings of the Symposium on Theoretical Aspects of Computer Science (STACS) 2012. Full version.

·         Corrections to the Central Limit Theorem for heavy-tailed probability densities, with J. Blanchet, M. Z. Bazant and D. Burch, Journal of Theoretical Probability, 24(4), 895-927, 2011.


Data Analysis and Statistical Learning

·         Learning about social learning in MOOCs: from statistical analysis to generative model, with C. Brinton, M. Chiang, S. Jain, Z. Liu and F. Wong, IEEE Transactions on Learning Technology, 2014.

·         From Black-Scholes to online learning: dynamic hedging under adversarial environments, with Z. Liu, submitted.

·         A Bayesian framework for online classifier ensemble, with Q. Bai and S. Sclaroff, International Conference on Machine Learning (ICML), 2014.

·         Why Steiner-tree algorithms work for community detection, with M. Chiang, Z. Liu and V. Poor, Journal of Machine Learning Research W & CP (AISTATS), 2013. Supplementary materials.

·        Statistical platform to discern spatial and temporal coordination of endothelial sprouting, with W. Yuen, N. Du, D. Shvartsman, P. Arany, and D. Mooney, Integrated Biology, 4(3), 292-300. 2012.

·         Adaptive variance reduction algorithms for bid optimization, with G. Zervas, preprint.


·         National Security Agency (NSA) Young Investigator Grant. Title: “Design of Robust Methodologies for Efficient Simulation and Sensitivity Analysis for Stochastic Systems”. Amount: $39,983. Duration: September 2013-September 2015. Role: P.I.

·         National Science Foundation (NSF) CMMI-OR. Title: “A Sensitivity Approach to Assessing Model Uncertainty for Stochastic Systems”. Amount: $224,947. Duration: July 2014-June 2017. Role: P.I.

·         National Science Foundation (NSF) CMMI-SES. Title: “Collaborative Research: Modeling and Analyzing Extreme Risks in Insurance and Finance”. Amount: $89,750. Duration: September 2014-August 2017. Role: co-PI (PI: Jose Blanchet, co-PI: Qihe Tang).


Current Ph.D. Students

·         Alexandrina Goeva

·         Clementine Mottet

·         Jerry Bai (Computer Science; co-advise with Stan Sclaroff)


On Thesis Defense Committee

·         Dan Ren

·         Wes Viles

·         Chong Liu

·         Wuyang Dai (Electrical & Computer Engineering)

·         Jing Qian (Electrical & Computer Engineering)

·         Yixi Shi (Operations Research, Columbia University)

·         John Zhang (Operations Research, Columbia University)


Undergraduate Students

·         Nicolas Kim (Honors Thesis)

·         Guy Aridor (UROP, joint with Rafik B. Hariri Institute for Computing Summer Research Award)


Other Teaching Experience

Teaching Fellow in Harvard University, Cambridge, MA:

·         STAT104: Introduction to Quantitative Methods, Fall 2006

·         STAT171: Stochastic Processes, Spring 2007

·         STAT139/239: Linear Models, Fall 2007


Industry Experience

·         Citigroup Global Markets and Banking, Equity Derivatives Trading, Hong Kong, Summer 2009

·         Lehman Brothers, Investment-Linked Insurance Structuring, Hong Kong, Summer 2008

·         Hewitt Associate LLC, Pension and Compensation Statistical Analyst, Hong Kong, Summer 2005

·         Standard Chartered Bank, Corporate Banking, Hong Kong, Summer 2001-2003


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