dr. P. Mohajerin Esfahani (Peyman)
My research interests revolve around theoretical and practical aspects of decision-making problems in uncertain and dynamic environments, with applications in control and security of large scale and distributed engineering systems. In my research, I use tools from Control Theory, Optimization, Machine Learning, and Information Theory.
July 2017: I have been invited as a keynote speaker at the Dutch Institute of Systems and Control (DISC) summer school.
February 2017: Our cohesion proposal “Distributed Actuation for Mechatronic: Fabrication of Multilayer IPMC ” with Hassan HosseinNia and Luigi Sasso from the department of Precision and Microsystems Engineering (PME) got awarded.
December 2016: Our paper Performance Bounds for the Scenario Approach and an Extension to a Class of Non-convex Programsreceived the George S. Axelby Outstanding Paper Award from the IEEE Control Systems Society, an award that recognizes the best paper published in the past two years in the IEEE Transactions on Automatic Control.
August 2016: I have been selected as one of the three finalists for the Young Researcher Prize in Continuous Optimization of the Mathematical Optimization Society, in recognition of our paper Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations.
March 2018: Invited seminar at “Distributionally Robust Optimization ”
Banff International Research Station for Mathematical, Innovation and Discovery (BIRD), Alberta, Canada
May 2017: Invited seminar at “Optimal Transport meets Probability, Statistics and Machine Learning ”
Banff International Research Station for Mathematical, Innovation and Discovery (BIRD), Oaxaca, Mexico
April 2017: New paper on a class of distributionally robust programs as an optimal decision-making mechanism
From Data to Decisions: Distributionally Robust Optimization is Optimal, [arXiv]
March 2017: New paper on linear programming approach to optimal control problems under weaker required assumptions
On Infinite Linear Programming Approach to Deterministic Infinite Horizon Discounted Optimal Control Problems, [arXiv]
February 2017: New paper on finite approximation of infinite dimensional linear programs
From Infinite to Finite Programs: Explicit Error Bounds with an Application to Approximate Dynamic Programming, [arXiv]