The Trustworthy Autonomy for Smart Adaptive Systems (TASAS) group, part of the Institute for Systems Theory and Automatic Control (IST), conducts fundamental research in the modelling, analysis, and control of uncertain linear and nonlinear dynamical systems. Our work spans both model-based and data-driven approaches, as we believe that combining these paradigms is essential for developing safe, efficient, and optimal solutions for complex systems.
Our research lies at the intersection of control theory, optimization, and learning. We pursue both fundamental and applied research, with a focus on:
- Data-Driven Control Theory
- System Identification
- Uncertainty Quantification
- Optimization
- Robust Control
- Dynamical Systems Theory
Our overarching goal is to foster trustworthy autonomy by advancing the design of intelligent systems, with a particular emphasis on applications in sustainable energy systems, smart transportation, and Industry 4.0.
Our team comprises passionate researchers working on cutting-edge problems in control, optimization, and learning.
- Prof. Dr. Andrea Iannelli
Research Interests:
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M.Sc. Nicolas Chatzikiriakos
Title: PhD Candidate
Research Interests: Learning-based control, Statistical Learning Theory, System Identification
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M.Sc. Fabian Jakob
Title: PhD Candidate
Research Interests: Optimization Algorithms, Robust Control, Robotics
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M.Sc. Massimiliano Manenti
Title: PhD Candidate
Research Interests: Optimal Control, Reinforcement Learning, Learning-based Control, and Mobile Robotics
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M.Sc. Bowen Song
Title: PhD Candidate
Research Interests: Data-driven Control, Policy Optimization
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