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AboutMy team and I develop methods to control real machines to the limits of performance by learning from data. Based in the high-tech hotspot Eindhoven, our key application domain involves the development of advanced motion control solutions for precision mechatronics. Driven by the challenges occurring in future precision mechatronics, our research focusses on fundamental issues arising in learning to control complex dynamical systems from data with robustness guarantees. As such, it is primarily positioned in the field of system identification and control, intersecting with machine learning, artificial intelligence, and mechatronics. Applications are broadly addressed through collaborations with many companies and institutions in mechatronics, ranging from semiconductor equipment and printing to space and astronomy. In addition, we enjoy many fruitful collaborations with domain experts in the health, energy, and mobility areas. More information: Inaugural booklet, “Learning in Machines” video, “Learning in Machines” magazine article, Advanced Motion Control research article, Fault detection/predictive maintenance movie, an impression of our post-academic course on motion control tuning. BioTom Oomen is a full professor in the Department of Mechanical Engineering at Eindhoven University of Technology, The Netherlands. He has also held academic positions at KTH Royal Institute of Technology (Sweden), The University of Newcastle (Australia), and Delft University of Technology. He is the recipient of several awards, including the 7th Grand Nagamori Award, the Corus Young Talent Graduation Award, and NWO Veni and Vidi personal grants. He currently serves as Senior Editor of IEEE Control Systems Letters (L-CSS) and Co-Editor-in-Chief of IFAC Mechatronics. His research spans all aspects from data to closed-loop control, and his application expertise includes precision mechatronics. For a more detailed CV see detailed CV or email me for an even more detailed one. ContactTel: +31 40 247 8332 Postal address: |