Research
I am largely interested in dynamical problems, e.g., designing (optimization) algorithms and control systems. In particular, I like to understand the interplay between the underlying problem structure and achievable qualitative behaviour.
Selected (pre)prints
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A Large Deviations Perspective on Policy Gradient Algorithms |
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Topological Obstructions to Stability and Stabilization: History, Recent Advances and Open Problems |
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On continuation and convex Lyapunov functions |
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Imaginary Zeroth-Order Optimization |
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Small Errors in Random Zeroth-Order Optimization are Imaginary |
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Topological Linear System Identification via Moderate Deviations Theory |
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Efficient Learning of a Linear Dynamical System with Stability Guarantees |
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On Topological Equivalence in Linear Quadratic Optimal Control |
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Robust Linear Quadratic Regulator: Exact Tractable Reformulation |
With special thanks to Daniel Kuhn, Mengmeng Li, Peyman Mohajerin Esfahani, Emmanuel Moulay, Roland Schwan, Tyler Summers, Tobias Sutter and Man-Chung Yue.
Selected talks (feel free to request slides or references, I aim to put everything online)
Towards Qualitative System Identification Through Optimization, June 2023, SIAM Conference on Optimization, Seattle.
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On continuation and convex Lyapunov functions, March 2023, KU Leuven, 17th International Young Researchers Workshop on Geometry, Mechanics, and Control.
Control theory with Heinz Hopf, February 2023, ETH Zürich, Institut für Automatik (IfA).
Imaginary Zeroth-Order Optimization, July 2022, International Conference on Continuous Optimization (ICCOPT), Lehigh.
Topological obstructions to stability and stabilization, March 2022, University of Warsaw, Department of Mathematical Methods in Physics, Theory of Duality seminar.
Small Errors in Zeroth Order Convex Optimization Are Imaginary, July 2021, SIAM Conference on Optimization, online.
On Topological Equivalence in Linear Quadratic Optimal Control, November 2020, Universiteit Utrecht, 15th International Young Researchers Workshop on Geometry, Mechanics, and Control.
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From Correlated Data to Guarantees in Stable Identification, October 2020, ETH Zürich, Institut für Automatik (IfA)
From Moderate Deviations Theory to Distributionally Robust Optimization: Learning from Correlated Data, September 2020, Robust Optimization Webinar (ROW).
Other
Stability via reverse I-projections, a symplectic perspective on the computation
Wouter Jongeneel
technical note, 2022
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From Moderate Deviations Theory to Distributionally Robust Optimization: Learning from Correlated Data
Tobias Sutter, Wouter Jongeneel and Daniel Kuhn
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Thesis
Controlling the Unknown: A Game Theoretic Perspective
Wouter Jongeneel
MSc. Thesis, Systems & Control, Delft University of Technology (TU Delft) 2019, adviser Peyman Mohajerin Esfahani.
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