Henry
Lam
Department of Mathematics and Statistics
Boston University
111 Cummington Street
Boston, MA 02215
Phone: 617-358-2394
Email: khlam (at) bu.edu

My research
focuses on computational and analytical approximation in stochastic systems,
including Monte Carlo methods, large deviations and diffusion approximation,
and stochastic optimization. The goal is to aid decision-making in risk and
operations management via sound mathematical analysis. I received my Ph.D.
degree in statistics at Harvard
University in 2011, under the supervision of Professor Jose Blanchet.
Papers
Working papers
Iterative
methods for robust estimation with bivariate model inputs, with S. Ghosh, submitted.
Rare-event simulation for
many-server queues, with J. Blanchet, recommended
for acceptance to Mathematics of Operations Research. Honorable Mention Prize in INFORMS George Nicholson Paper
Competition 2010.
Why Steiner-tree
algorithms work for community detection, with M. Chiang, Z. Liu and V. Poor, to appear in Journal of Machine Learning Research W & CP (AISTATS).
Exact asymptotics for infinite-server queues, preliminary version
appeared in Proceedings of the 6th
International Conference on Queueing Theory and
Network Applications 2011.
Uniform large deviations for heavy-tailed single-server queues under
heavy traffic, with J. Blanchet. Earlier version appeared in Chapter 2 of my Ph.D. thesis 2011.
Published papers and proceedings
Efficient
rare-event simulation for perpetuities, with J.
Blanchet and B. Zwart, Stochastic Processes and Their Applications, 122(10),
3361–3392, 2012.
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.
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 available at http://arxiv.org/pdf/1104.5268v2.pdf.
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 available at http://arxiv.org/pdf/1201.0559v1.pdf.
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.
Experience
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
Course
Instructor in Boston University, MA:
·
MATH569:
Optimization Methods in Operations Research, Fall
2011, 2012
·
MATH881:
Graduate Seminar in Applied Probability, Fall 2011
·
MATH116:
Statistical Methods II, Spring 2012, 2013
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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