Speakers

Thomas Beckers

Thomas Beckers is an incoming Professor of Autonomous Systems at Ulm University and currently an Assistant Professor of Computer Science and the Institute for Software Integrated Systems at Vanderbilt University. Before joining Vanderbilt, he was a postdoctoral researcher at the Department of Electrical and Systems Engineering, University of Pennsylvania, where he was member of the GRASP Lab, PRECISE Center and ASSET Center. In 2020, he earned his doctorate in Electrical Engineering at the Technical University of Munich (TUM), Germany. He received the B.Sc. and M.Sc. degree in Electrical Engineering in 2010 and 2013, respectively, from the Technical University of Braunschweig, Germany. In 2018, he was a visiting researcher at the University of California, Berkeley.

He is a DAAD AInet fellow and was awarded with the Rhode & Schwarz Outstanding Dissertation prize. His research interests include physics-enhanced learning, nonparametric models, and safe learning-based control. [Website]

Alberto Bemporad

Alberto Bemporad received his M.S. degree cum laude in Electrical Engineering (1993) and his Ph.D. in Control Engineering (1997) from the University of Florence, Italy. He held research positions at Washington University in St. Louis (1996–1997) and ETH Zurich (1997–2002). He served at the University of Siena (1999–2009) and at the University of Trento (2010–2011). Since 2011, he has been Full Professor at the IMT School for Advanced Studies Lucca, where he was Director from 2012 to 2015. He co-founded ODYS S.r.l. in 2011, a company specialized in industrial model predictive control systems, and has held visiting appointments at Stanford University, the University of Michigan, and Zhejiang University. He has authored over 400 publications and 21 patents in model predictive control, hybrid systems, numerical optimization, nonlinear system identification, and automotive control, and co-developed the Model Predictive Control Toolbox (MathWorks) for MATLAB.

He was an Associate Editor of the IEEE Transactions on Automatic Control during 2001-2004 and Chair of the IEEE CSS Technical Committee on Hybrid Systems during 2002-2010. He is an IEEE Fellow (since 2010) and IFAC Fellow (since 2025). His awards include the IFAC High-Impact Paper Award (2011–14), IEEE CSS Transition to Practice Award (2019), SAE Environmental Excellence in Transportation Award (2021), the Beale–Orchard-Hays Prize (2024), and an ERC Advanced Grant (2024). [Website]

Ján Drgoňa

Jan is an associate professor in the Department of Civil and Systems Engineering and the Ralph S. O’Connor Sustainable Energy Institute (ROSEI) at Johns Hopkins University (JHU). Before joining JHU, Jan was a senior data scientist in the Physics and Computational Sciences Division at Pacific Northwest National Laboratory and a postdoc at the mechanical engineering department at KU Leuven in Belgium. Jan has a PhD in Control Engineering from the Slovak University of Technology in Bratislava, Slovakia. His current research is focused on scientific machine learning with applications in sustainable energy systems. [Website]

Rolf Findeisen

Rolf Findeisen studied engineering cybernetics at the University of Stuttgart and chemical engineering at the University of Wisconsin – Madison. He began his doctoral studies at ETH Zurich's, which he completed in 2004 following his doctoral father to the University of Stuttgart. 2007, Rolf was appointed professor at the Institute of Automatic Control at Otto-von-Guericke University Magdeburg. Since August 2021, he heads the Control and Cyber-physical Systems Laboratory at the Technical University of Darmstadt.

Rolf is engaged in method development in the area of systems theory and control engineering, focusing on optimization-based and predictive control; fusing machine learning approaches such as Gaussian processes and neural networks with model based control providing guarantees; and control of complex, distributed systems via communication networks. [Website]

Cosimo Della Santina

Cosimo Della was born in Pontedera, Italy, on the 6th of October 1989. He holds a B.Sc. in Computer Engineering and a M.Sc. in Robotics and Control Theory from the University of Pisa. He was a Ph.D. student at the University of Pisa and IIT, a visiting researcher and postdoc at MIT-CSAIL, and a senior postdoc and later a lecturer at TUM. He is now Associate Professor at TU Delft (CoR, Mechanical Engineering), and a researcher at the German Aerospace Center (DLR).

Cosimo Della has been awarded the 2020 Georges Giralt Ph.D. Award, the 2023 IEEE RAS Early Career Award, and an ERC Starting Grant in 2024. I am co-director of the Delft AI lab SELF, and a VENI laureate. [Website]

Sergio Lucia

Sergio Lucia received the M.Sc. degree in Electrical Engineering from the University of Zaragoza, Spain, in 2010 and the Dr.-Ing. degree in Optimization and Automatic Control from the TU Dortmund University, Germany, in 2014. He then joined the Otto-von-Guericke University Magdeburg and visited the Massachusetts Institute of Technology as a Postdoctoral Fellow. From 2017 to 2020, he served as an Assistant Professor at TU Berlin before returning to TU Dortmund University as an Associate Professor in 2020. Since 2023, he has been a Full Professor and Head of the Chair of Process Automation Systems at TU Dortmund University. His research focuses on decision making under uncertainty and the integration of machine learning with control theory. Additionally, he serves as an Associate Editor for the Journal of Process Control, and starting after IFAC WC 2026, he will serve as Chair of the IFAC TC on Optimal Control. [Website]

Dirk Reinhardt

Dirk Reinhardt is a postdoctoral researcher in the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU) and the Center for AI for Decisions (aiD), where he works in the group of Sébastien Gros on combining model predictive control and reinforcement learning (RL). Alongside this research, his current focus is on algorithm development and efficient software implementation. As a core developer of "leap-c", an open-source Python framework that embeds differentiable MPC solvers as physics-informed structural priors into RL policies and value functions, he works to enable applications of these methods across a wide range of domains, including energy systems, robotics, and autonomous vehicles. He holds a PhD in Engineering Cybernetics from NTNU (2022), where he designed nonlinear autopilots for fixed-wing UAVs and flew the full autonomy stack in real flight experiments.[Website]

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