Biography

Dr. Bikramjit Das received his Ph.D. from the School of OR&IE at Cornell University under the supervision of Prof. Sidney Resnick. He was a post-doctoral researcher under Prof. Paul Embrechts at the RiskLab at ETH Zurich before joining SUTD as an Assistant Professor.
Dr. Das’s research is in the investigation and analysis of rare and extreme events using tools from applied probability, statistics and optimization. The application domain for his research spans insurance, finance, telecommunication and more recently social and economic networks.
He teaches undergraduate level classes in Probability, Statistics, Stochastic Simulation and a graduate class in Stochastic Modelling.

Education

  • PhD in Operations Research, Cornell University, USA (2009)
  • B. Stat, Indian Statistical Institute, India (2002)

Selected Recent Publications

  • Heavy-tailed random walks, buffered queues and hidden large deviations (with H. Bernhard), Bernoulli (forthcoming),2018.
  • Risk contagion under regular variation and asymptotic tail independence (with V. Fasen-Hartmann), Journal of Multivariate Analysis, 165, 194-215, 2018.
  • Generation and detection of multivariate regular variation and hidden regular variation (with S. Resnick). Stochastic Systems, 5(2), 195-238 (electronic), 2015.
  • Living on the multidimensional edge: seeking hidden risks using regular variation (with A. Mitra and S. Resnick), Advances in Applied Probability, 45(1), 139-163, 2013.
  • Weak limits of exploratory plots in extreme value analysis (with S. Ghosh), Bernoulli, 19(1), 308-343, 2013.
  • Four theorems and a financial crisis (with P. Embrechts and V. Fasen), International Journal of Approximate Reasoning, 54(6), 701-716, 2013.
  • On robust tail index estimation for linear long-memory processes (with J. Beran and D. Schell), Journal of Time Series Analysis, 33(3), 406-423, 2012.
  • QQ plots, random sets and data from a heavy tailed distribution (with S. Resnick), Stochastic Models, 24 (1), 103-132,2008.

Recent presentations

  • Heavy tails in a robust newsvendor model, June, 2018. Video
  • Multivariate regular variation: full dependence and strong dependence, May, 2016. Video