I am serving as an Assistant Professor in the Engineering Systems & Design pillar of SUTD since 2018. My research interests lie broadly in applied probability and data-driven optimization under uncertainty. The research focus has been to

  1. understand the tradeoffs between efficiency and competing considerations such as robustness, risk and fairness in large-scale decision problems affected by uncertainty, and

  2. subsequently build models and method for designing robust and reliable operations in uncertain environments.

We employ relevant tools from probability theory and optimization, such as large deviations, optimal transport, etc., to effectively tackle these challenges. My CV is available here: (link)

Note to prospective PhD students and postdoctoral researcers: I am actively looking for prospective PhD students and post-doctoral researchers who are interested in working broadly in data and decision analytics. An ideal candidate for a postdoctoral position will have training in one (or) more of the following areas: stochastic modeling, optimization, simulation modeling and analysis, statistics and machine learning.

Brief bio: Before joining SUTD, I had the good fortune of pursuing PhD under the supervision of Professor Sandeep Juneja at Tata Institute of Fundamental Research and having the mentorship of Professor Jose Blanchet during my stint as a postdoctoral researcher at the Department of Industrial Engineering and Operations Research, Columbia University. My PhD dissertation on "Rare events in heavy-tailed stochastic systems: Algorithms and Analysis" was awarded with the TIFR-SASKEN Best Thesis Award for the year 2015. While pursuing PhD, I was a recipient of IBM International Fellowship for the year 2013-14. I have served as a visiting researcher in ICERM, Brown University (Sep - Nov, 2012), Department of IEOR, Columbia University (Sep - Dec, 2012) and Management Science & Engineering, Stanford University (Jul - Nov, 2017).

Research publications

We gratefully acknowledge support from the Singapore Ministry of Education Academic Research Funding, Civil Aviation Authority of Singapore, Aviation Studies Institute and the Startup reseach funding support from SUTD

Publications in refereed journals*

J. Blanchet, F. He, K. Murthy, “On distributionally robust extreme value analysis”, Extremes, 2020, 23(2), 317- 347

D. Padmanabhan, K. Natarajan, K. Murthy, “Exploiting partial correlations in distributionally robust optimization”, Mathematical Programming, 2019

J. Blanchet, Y. Kang, K. Murthy, “Robust Wasserstein profile inference and applications to machine learning”, Journal of Applied Probability, 2019, 56(3), 830-857

J. Blanchet, K. Murthy, “Quantifying distributional model risk via optimal transport”, Mathematics of Operations Research, 2019, 44:2, 565-600

J. Blanchet, K. Murthy, “Exact simulation of multi-dimensional Reflected Brownian Motion”, Journal of Applied Probability, 2018, 55(1), 137-156

J. Blanchet, K. Murthy, “Tail asymptotics for delay in a half-loaded GI/GI/2 queue with heavy-tailed job sizes”, Queueing Systems, 2015, 81:301

S. Dey, S. Juneja, K. Murthy, “Incorporating views on marginal distributions in the calibration of risk models”, Operations Research Letters, 2015, 43(1), 46-51

K. Murthy, S. Juneja, J. Blanchet, “State-independent importance sampling for random walks with regularly varying increments”, Stochastic Systems, 2015, 4(2), 321-374


“Self-structuring importance samplers for scalable and efficient tail risk estimation” [with A. Deo]

Confidence regions in Wasserstein distributionally robust optimization” [with J. Blanchet, N. Si]

Optimal transport based distributionally robust optimization: Structural properties and iterative Schemes [with J. Blanchet, F. Zhang]

Exact and efficient simulation of tail probabilities of heavy-tailed infinite series” [with H. Hult, S. Juneja]

Publications in refereed conference proceedings

A. Deo, K. Murthy “Optimizing tail risks using an importance sampling based extrapolation for heavy-tailed objectives,” 2020 59th IEEE Conference on Decision and Control (CDC), 2020

J. Blanchet, Y. Kang, K. Murthy, F. Zhang, “Data-Driven Optimal Transport Cost Selection For Distributionally Robust Optimization,” 2019 Winter Simulation Conference (WSC), National Harbor, Maryland, 2019, pp. 3740-37514 [Winner of the Best Theoretical Paper award]

K. Murthy, S. Juneja, J. Blanchet, “Optimal rare event Monte Carlo for Markov modulated regularly varying random walks,” 2013 Winter Simulation Conference (WSC), Washington, DC, 2013, pp. 564-576

K. Murthy, S. Juneja, “State-independent importance sampling for estimating large deviation probabilities in heavy-tailed random walks,” 6th International ICST Conference on Performance Evaluation Methodologies and Tools, Cargese, 2012, pp. 127-135


Default author ordering in the listing of publications is alphabetical

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Currently teaching in SUTD

40.015 Simulation modeling and analysis (Term 3, 2020)

Past Courses

IEOR E4101 / 4100 Probability models for Management Science & Engineering (Fall 2016, Columbia University)

40.305 Advanced topics in stochastic modeling (Term 1 of years 2018, 2019, 2020)

40.520 Stochastic modeling (Term 1 of years 2018, 2019, 2020)

10.007 Modeling the systems world (Term 1 of 2020)