Speakers 

Donatello Materassi is a researcher in control and dynamical systems, with expertise in nonlinear system identification, graphical and causal models, and interpretable machine learning. He received his Ph.D. from the University of Florence in 2007 and subsequently held postdoctoral research positions at the University of Minnesota and MIT. He has served as a lecturer at Harvard University and as an Assistant Professor at the University of Tennessee. He is the recipient of an NSF CAREER Award (2015) and is currently an Associate Professor at the University of Minnesota. His research lies at the intersection of system identification, causality, and explainable AI (XAI), with applications ranging from molecular force spectroscopy and bioinformatics to broader data-driven modeling problems.

Michael Muehlebach studied mechanical engineering at ETH Zürich and specialized in robotics, systems, and control during his Master’s degree. He received the B.Sc. and the M.Sc. in 2010 and 2013, respectively, before joining the Institute for Dynamic Systems and Control for his Ph.D. He graduated under the supervision of Prof. R. D’Andrea in 2018 and joined the group of Prof. Michael I. Jordan at the University of California, Berkeley as a postdoctoral researcher. In 2021 he started as an independent group leader at the Max Planck Institute for Intelligent Systems in Tuebingen, where he leads the group “learning and dynamical systems”. He is interested in a variety of subjects, including machine learning, dynamical systems, and optimization. During his Ph.D. he developed approximations to the constrained linear quadratic regulator problem, a central problem in control theory, and applied these to model predictive control. He also designed control and estimation algorithms for balancing robots and flying machines. His more recent work straddles the boundary between machine learning and optimization, and includes the analysis of momentum-based and constrained optimization algorithms from a dynamical systems point of view. He received the Outstanding D-MAVT Bachelor Award for his Bachelor’s degree and the Willi-Studer prize for the best Master’s degree. His Ph.D. thesis was awarded with the ETH Medal and the HILTI prize for innovative research. He was also awarded a Branco Weiss Fellowship, Emmy Noether Fellowship, and an Amazon research grant, which funds his research group.

Luca Furieri is an Associate Professor in the Department of Engineering Science at the University of Oxford since June 2025. His research focuses on optimal control and optimisation for distributed decision-making and large-scale cyber-physical systems. He received the Swiss National Science Foundation (SNSF) Ambizione career grant in 2022, the IEEE Transactions on Control of Network Systems Best Paper Award in 2022, and the American Control Conference O. Hugo Schuck Best Paper Award in 2018.

Lorenzo Zino is an Assistant Professor with the Department of Electronics and Telecommunications, Politecnico di Torino, Italy, since 2022. He received BS (2012), MS (2014), and PhD (2018) in Applied Mathematics from Politecnico di Torino, and held research fellowships with the New York University (US) and University of Groningen (The Netherlands). His research interests include modelling, analysis, and control of dynamical processes on networks, graph theory, applied probability, optimization, and game theory. He produced more than 90 international scientific publications, including more than 50 papers in scientific journals, and gave more than 50 presentations and seminars at national and international conferences, universities, and research centers. He is Senior Member of the IEEE and the recipient of the 2024 IEEE CSS Italy Best Young Author Journal Paper Award. He is Member of the Editorial Board of the International Journal of Control, Scientific Reports, and the IEEE Control Systems Letters; Member of the CEB for the IEEE CSS and the EUCA, and of the Program Committee of several national and international conferences.

Chung-Han Hsieh is an Associate Professor of Quantitative Finance at National Tsing Hua University, Taiwan. He received his Ph.D. in Electrical Engineering from the University of Wisconsin–Madison in 2019, specializing in control systems with a minor in mathematics. His research focuses on control-theoretic foundations for decision-making under uncertainty, with applications to quantitative finance, including stochastic and robust control, distributionally robust optimization, and feedback-based trading and portfolio policies. He has authored or co-authored papers in journals including Automatica, IEEE Transactions on Automatic Control, European Journal of Operational Research, and the Journal of Economic Dynamics and Control. He is a recipient of the 2025 Ta-You Wu Memorial Award from the National Science and Technology Council (NSTC) in Taiwan and the 2025 Young Automatic Control Engineer Award from the Chinese Automatic Control Society (CACS).