Dr. Lam's research focuses on building computation tools to analyze decisions and to manage risk under stochastic environments. Methodologically, he uses a combination of Monte Carlo methods, simulation optimization and statistics. Regarding applications, he is broadly interested in engineering operations, service systems, and risk management.
Dr. Lam received his Ph.D. degree in Statistics at Harvard University in 2011, and was an Assistant Professor in the Department of Mathematics and Statistics at Boston University until December 2014.
Monte Carlo methods, risk analysis, model uncertainty and simulation output analysis, stochastic optimization
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.
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.