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

On topological properties of compact attractors on Hausdorff spaces Wouter Jongeneel submitted 2023. |pdf| |arXiv| |bibtex|

A Large Deviations Perspective on Policy Gradient Algorithms Mengmeng Li, Wouter Jongeneel and Daniel Kuhn 2023. |arXiv|

Topological Obstructions to Stability and Stabilization: History, Recent Advances and Open Problems Wouter Jongeneel and Emmanuel Moulay SpringerBriefs in Control, Automation and Robotics (Open Access), pp. X, 132, 2023. |pdf| |link (Springer)| |Supported by the SNSF|

On continuation and convex Lyapunov functions Wouter Jongeneel and Roland Schwan submitted 2023. |pdf| |arXiv| |bibtex|

Imaginary Zeroth-Order Optimization Wouter Jongeneel submitted 2022. As presented at the International Conference on Continuous Optimization 2022 |pdf| |arXiv| |bibtex| |PDE GIF|

Small Errors in Random Zeroth-Order Optimization are Imaginary Wouter Jongeneel, Man-Chung Yue and Daniel Kuhn submitted 2022. As presented at the SIAM Conference on Optimization 2021 *Winner of the 2023 INFORMS Optimization Society Student Paper Prize |slides| |pdf| |arXiv| |bibtex| |Lorenz GIF|

Topological Linear System Identification via Moderate Deviations Theory Wouter Jongeneel, Tobias Sutter and Daniel Kuhn IEEE Control Systems Letters, vol. 6, pp. 307-312, 2022. Presented at the 2021 CDC |arXiv| |link (IEEE)| |bibtex|

Efficient Learning of a Linear Dynamical System with Stability Guarantees Wouter Jongeneel, Tobias Sutter and Daniel Kuhn IEEE Transactions on Automatic Control (TAC), vol. 68, no. 5, pp. 2790 - 2804, 2023. |arXiv| |link (IEEE)| |bibtex| As presented at the SIAM Conference on Optimization 2023 |slides| *Runner up IEEE CSS Swiss Chapter Young Author Best Journal Paper Award 2023

On Topological Equivalence in Linear Quadratic Optimal Control Wouter Jongeneel and Daniel Kuhn European Control Conference (ECC), pp. 2002 - 2007, 2021. |preprint pdf| |link (IEEE)| |bibtex|

Robust Linear Quadratic Regulator: Exact Tractable Reformulation Wouter Jongeneel, Tyler Summers and Peyman Mohajerin Esfahani IEEE Conference on Decision and Control (CDC), pp. 6742 - 6747, 2019. |pdf| |link (IEEE)| |bibtex|

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. |slides|

• 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. |video|

• 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
|pdf|

From Moderate Deviations Theory to Distributionally Robust Optimization: Learning from Correlated Data
Tobias Sutter, Wouter Jongeneel and Daniel Kuhn
|video at SPS|

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.
|pdf| |link| |bibtex|