Best SICON Paper Prize (2015) For one of two most outstanding papers in SIAM J. on Control and Optimization during 2013-2015.
Plenary Speaker, SIAM Conference on Optimization (2021)
Plenary Speaker, Colombian Conference on Applied and Industrial Mathematics (2022)
Princeton University's Howard B. Wentz, Jr. Junior Faculty Award (2016) for excellence in research and teaching.
Distinguished Teaching Award of the Princeton School of Engineering and Applied Sciences (2023)
Excellence in Teaching of Operations Research Award of the Institute for Industrial and Systems Engineers (2017)
Teaching Award of the Princeton Engineering Council (four-time recipient, Fall 2014, Fall 2018, Fall 2019, Fall 2023) For ORF 363/COS323, "Computing and Optimization"
AFOSR YIP (2014-2017) Office of Scientific Research Young Investigator Program Award (AF career award)
INFORMS Computing Society Prize (2012) For best series of papers at the interface of Operations Research and Computer Science
IBM Watson Herman Goldstine Fellowship in Mathematical Sciences (2012,2013) Awarded annually to at most two candidates in all areas of mathematical and computer sciences. Only one fellowship awarded in 2012.
Best Paper Award (2013) 30th IEEE International Conference on Robotics and Automation (ICRA)
NSF Junior Oberwolfach Fellowship (2015)
NSF Junior Oberwolfach Fellowship (2014)
AMS-Simons Travel Award (2012-2014)
Best Student-Paper Award Finalist, 47th IEEE Conference on Decision and Control (2008)
Young Engineer Prize, 1st Place Award, Washington Society of Engineers (2006)
Best undergraduate technical paper, 1st Prize, District of Columbia Council of Eng. (2006)
Current Research Interests
Optimization: Algebraic methods in optimization, semidefinite programming, polynomial optimization.
Computational aspects of dynamics and control: Optimization-based Lyapunov theory for verification of dynamical systems.
Control-oriented learning: Learning dynamical systems from trajectory observations subject to side information.
Algorithms and complexity: Computational complexity in numerical optimization, convex relaxations in combinatorial optimization.
I am also interested in applications of these tools to semialgebraic problems in systems theory, machine learning, portfolio management, robotics, and mathematical economics.
A popular-science description of some research papers