Research Team

Current Team

I am currently (co-)supervising the following post-doctoral researchers and Ph.D. students: 

• Lucian Cristian Iacob: LPV Modeling Using the Koopman Operator 

• Sarvin Moradi: Learning Constitutive Laws in a Multi-Physics System (joint supervision with N.O. Jaensson)

• Máté Kiss:  Data-Driven Model Completion: from Experimental Design to Interpretable Models

• Jan Hoekstra: An LFR-based approach for Data-Driven Model Completion

• Apoorva Singh: Artificial Intelligence for Quantitative Crowd Dynamics Modeling (joint supervision with A. Corbetta and R.M. Castro)

• Lars Sickert Karam: Statistics and AI for Quantitative Crowd Dynamics Modeling (joint supervision with A. Corbetta and R.M. Castro)

• Gé van Otterdijk:  Port-Hamiltonian Identification of Interconnected Systems

• Samarth Toolhally:  Hybrid Modelling for Thermo-Mechanical Processes in Lithography 

Furthermore, I am currently (co-)supervising the following MSc students during their final graduation project:

• Kirill Gugunishvili: Machine Learning-Based Crack Opening Prediction During Fatigue Loading  (in collaboration with D. Leonetti, Built Environment, TU/e)

• André Sniekers: Nonlinear state-space neural network for wafer stage feedforward   (in collaboration with H. Butler, ASML)

• 2023-2025 - Dylan Öztürk Şener:  Data-Driven Modelling of Smooth Muscle Cell Dynamics

• 2023-2025 - Yuhan Liu: Regularized Data-Driven Model Completion

• 2024-2025 - Gerben I. Beintema: Data-driven Learning of Nonlinear Dynamic Systems: A Deep Neural State–Space Approach

• 2026 - Stefano De Carli, University of Bergamo, Italy: Model augmentation with guaranteed stability

• 2025 - Mahsan Ghasemi, University of Calgary, Canada: Port-Hamiltonian identification for interconnected systems

• 2023 - Francesco Gismondi, the University of Rome Tor Vergata, Italy: Deep Learning for Nonlinear System Identification

• 2020 - Soumaya Marzougui, Gabes University, Tunesia: Nonlinear System Identification of Fractional-Order Systems

• 2019 - Thiago Burghi, Cambridge University, UK: System Identification of Biophysical Neuronal Models

• 2019 - Prof. Jin-Song Pei, University of Oklahoma, USA: Data-Driven Hysteresis Modelling for Control

1. 2025 - Roel Drenth: Efficient Gradient-Based Learning of LPVModels with Linear Fractional Representation (Journal Publication in Preparation)

2. 2025 - Sven Passier: A SUBNET Based Approach For Crack Opening Estimation During Fatigue Loading (in collaboration with D. Leonetti, Built Environment, TU/e)

3. 2025 - Tobin Bauer: Real-Time Tomographic Inversion and Control for MAst-U  (in collaboration with M. van Berkel, DIFFER)

4. 2025 - Abdel Rahman El Tonbary: Enhancing Wafer Alignment Marker Selection by Machine Learning Techniques (in collaboration with ASML)

5. 2025 - Noortje Hagelaars: Learning Port-Hamiltonian DAE Dynamics (Conference Publication in Preparation)

6. 2025 - Yidan Zhu: Deep Learning for Continuous Time Irregularly Sampled Systems (Conference Publication in Preparation)

7. 2024 - Joost Mellink: Sparse Interpretable State-Space Models for Dynamical Systems

8. 2024 - Jacky Li: Frequency-Domain Linear-Parameter Varying Identification and Control of Wirebonder Systesm (in collaboration with ASMPT)

9. 2024 - José Noronha: Identification and Control using Koopman Models

10. 2024 - Gé van Otterdijk: Learning Port-Hamiltonian Neural Network Models for Nonlinear Dynamical Systems (Conference Publication)

11. 2024 - Robin van der Meulen: System Identification for Compensating Pressure-Induced Disturbances in Cooled Motion Systems (in collaboration with H. Butler, ASML)

12. 2024 - Rutger Elfrink: Advanced input signals and transient processing methods for rheology (co-supervised by N.O. Jaensson, P&P, ME, TU/e)

13. 2024 - Gregorius Rafael Widojoko: Linear Time-invariant State-space System Identification by Variational Inference (co-supervised by W.M. Kouw, SPS, EE, TU/e)

14. 2023 - Serban Popescu: Nonlinear MPC using Deep Prediction Networks (Conference Publication)

15. 2023 - Adem Bavarsi: MIMO System Identification and Feedback Control Design For Wire Bonders (in collaboration with ASMPT)

16. 2023 - Gustavo Cardenas: Initializing the Subspace Encoder Approach for Nonlinear System Identification using the Best Linear Approximation

17. 2023 - Luc Tissingh: Intelligent wafer stage long-stroke commutation using AI (in collaboration with H. Butler, ASML)

18. 2023 - Jan Hoekstra: Nonlinear MPC automatic using linear parameter varying embedding on neural networks (Conference Publication)

19. 2023 - Collin Bouwens: Learning an Artificial Neural Network Slip/Friction Dynamics (in collaboration with ASML)

20. 2022 - Loek van Leeuwen: Deep Learning-based tomographic reconstruction for fusion control (co-supervised by J. Citrin, Differ, journal contribution in preparation)

21. 2022 - Lars Peeters: Behavior-Based Regularization for Nonlinear System Identification (co-supervised by K. Tiels, CST, ME, TU/e, Conference Publication)

22. 2022 - Rishi Ramkannan: Improved Subspace Encoder-Based Nonlinear System Identification (Conference Publication)

23. 2022 - Matei Popescu: System Identification and Control Design for Compensation of Machine Frame Dynamics (in collaboration with ASMPT)

24. 2022 - David van de Sanden: Reinforcement Learning for Urgency-Aware Optimal Routing through Artificial Currencies  (co-supervised by M. Salazar, CST, ME, TU/e, Conference Publication)

25. 2021 - Claudia Wevers: Determining the Motion of a Thrown Deformable Object using Motion Capture Data (main supervisor A. Saccon, D&C, ME, TU/e)

26. 2021 - Kumaran B.K. Viswanathan: Encoder-based Nonlinear Identification for PDEs

27. 2021 - Mengqi Wang: Reinforcement Learning for Medical Eye Surgery Pumps (in collaboration with Demcon)

28. 2021 - Tarun B. Sriram: Machine Learning-Based Vision-In-The-Loop System For Automated Buzz Wire Demonstrator (in collaboration with Demcon)

29. 2021 - Mukhlish Ghany Al Fatah: Graph Neural Network for grid topology reconstruction (in collaboration with B.J. Claessens, EES, Electrical Engineering, TU/e)

30. 2021 - Joost C.P. Hakvoort: Data-driven methods for fixed-structure controller tuning (in collaboration with ASMPT)

31. 2020 - Konstantinos Krikelis: Piezo-Hysteresis Modelling using Artificial Intelligence (in collaboration with ASML, Conference Publication)

32. 2020 - Naveen Venugopalan: Settling Performance Improvement Using Machine Learning-Based Motion Control (in collaboration with ASMPT)

33. 2019 - Congyi Wu: Modelling Aerospace Structures using Data-Driven Nonlinear State-Space Identification

34. 2019 - Pascal Den Boef: Frequency Domain LPV System Identification Using Local Data (Conference Publication)

35. 2015 - Jules Hammenecker: Design and realization of a compensation for non-linear amplifiers (Journal Publication)