Team

I (co-)supervise the following researchers. If you are interested in working with us, please visit the application website, where all vacancies are advertised. I may not be able to respond to email applications.

Researchers

• Pooya Saffarieh (postdoctoral researcher)

Ph.D. Candidates

• Laura Barendsz (with Electromagnetics, EE, TUE)

• Lotfi Chaouach (with DCSC, TUD)

• Rogier Dinkla (with DCSC, TUD)

• Enrico Dozzi

• Raphaël Goetz (with D&C, ME, TUE)

• Timo de Groot

• Abdullah Habboush (with D&C, ME, TUE)

• Maarten van der Hulst

• Tjeerd Ickenroth

• Gijs Van Meerbeeck

• Arturo Morales Bugueño (with TNO)

• Mauricio Sotelo (with Airbus)

• Eke Suichies (with RBT, ME, TUE)

• Teun Wijfjes

Former Researchers

• Kentaro Tsurumoto (visiting PhD candidate from The University of Tokyo), 2025-2026

• Taejune Kong (visiting PhD candidate from DGIST, Korea), 2025

• Koen Classens (postdoctoral researcher), 2024

• Guilia Sonzogni (visiting PhD candidate from University of Bergamo), 2024-2025

• Paul Tacx (postdoctoral researcher), 2024

• Deokjin Lee (visiting PhD candidate from DGIST, Korea)

• Zhihe Zhuang (Jiangnan University)

• Hanul Jung (visiting PhD candidate from DGIST, Korea)

• Edoardo Catenaro (visiting PhD candidate from Politecnico of Milan)

• Kentaro Tsurumoto (visiting PhD candidate from The University of Tokyo)

• Masahiro Mae (visiting PhD candidate from The University of Tokyo)

• Jean-Philippe Noël (postdoctoral researcher, 2019-2020)

• Enzo Evers

• Wataru Ohnishi (visiting professor, University of Tokyo, 2020)

• Mirko Mazzoleni (visiting professor, University of Bergamo, Q1 2020)

• Isaac Spiegel (visiting PhD candidate from The University of Michigan)

• Robbert Voorhoeve, 2018-2019

• Dieter Verbeke, Visiting Ph.D. candidate from Vrije Universiteit Brussel, Q4, 2016

Former Ph.D. Candidates

• Lotfi Chaouach, Thesis “Exploiting structure in distributionally robust optimization”, defense date June 29, 2026

• Mathyn van Dael, Thesis: “Data-driven control of Gravitational Wave detectors”, defense date January 23, 2026

• Lars van de Kamp, Thesis: “Closing the loop with AI in respiratory systems: From AI-based diagnostics to decision-making”, defense date December 2, 2025

• Max van Meer, Thesis: “Data-driven calibration and control using cost-effective actuators and sensors”, defense date September 9, 2025

• Max van Haren, Thesis: “Multirate identification and motion control”, defense date September 3, 2025

• Johan Kon, Thesis: “Neural networks in feedforward control: Applied to high precision motion systems”, defense date June 18, 2025

• Koen Classens, Thesis: “Fault diagnosis for uncertain systems in closed loop: Applied to semiconductor equipment”, defense date October 4, 2024

• Paul Tacx, Thesis: “Identification and control of overactuated mechatronic systems”, defense date September 18, 2024

• Maurice Poot, Thesis: “Gaussian processes for learning in motion control: Applied to semiconductor back-end machines”, defense date July 3, 2024

• Leontine Aarnoudse, Thesis: “Data-driven randomized and nonlinear learning for control”, defense date June 19, 2024

• Nic Dirkx (ASML), Thesis: Wafer stage motion control: From experiment design to robust performance, Defense date October 6, 2023

• Tom Bloemers (EE-CS, TUE), Data-driven linear parameter-varying control: A frequency-domain approach, Defense date March 3, 2023

• Noud Mooren, Thesis: “Intelligent mechatronics through learning: From Gaussian processes to repetitive control and adaptive feedforward”, defense date May 12, 2022, supported by I-mech

• Nard Strijbosch, Thesis: “Learning and feedforward control for unconventional sampling and actuation”, defense date March 18, 2022, supported by NWO Vidi

• Joey Reinders, Thesis: “Smart mechanical ventilators: Learning for monitoring and control”, defense date February 2, 2022, supported by Macawi/Demcon

• Enzo Evers, Thesis: Identification and active thermomechanical control in precision mechatronics, Defense date January 7, 2021

• Robin de Rozario, Thesis: Data-driven learning control for complex multivariable and linear parameter-varying systems, Defense date April 28, 2020

• Lennart Blanken, Thesis: Learning and repetitive control for complex systems - With application to large-format printers, Defense date May 21, 2019

• Jurgen van Zundert, Thesis: Resource-aware motion control: Feedforward, learning, and feedback, Defense date November 28, 2018

• Robbert Voorhoeve, Thesis: Identification for advanced motion control - Numerically reliable algorithms for complex systems, Defense date October 22, 2018, propositions available here

• Frank Boeren, Thesis: System identification for feedforward and feedback control: With application to semiconductor manufacturing, Defense date October 3, 2016, supported by Philips Innovation Services

• Egon Geerardyn, Thesis: Development of user-friendly system identification techniques, private defense date June 16, 2016, public defense date August 26, 2016, Vrije Universiteit Brussel, Belgium

• Joost Bolder, Thesis: Flexibility and robustness in iterative learning control: With applications to industrial printers, defense date September 2, 2015, supported by Océ

• Robbert van Herpen, Thesis: “Identification for control of complex motion systems: Optimal numerical conditioning using data-dependent polynomial bases”, defense date January 27, 2014, supported by ASML Research, now at LIME

Former Eng.D. Students

• Quinten van den Elsen (2025)