Samuele Tosatto

Samuele Tosatto is an Assistant Professor in the Computer Science Department at the University of Innsbruck and affiliated with the Digital Science Center. His research focuses on enabling robots to learn in real-world environments through reinforcement learning and abstraction techniques, addressing challenges in scalability and efficiency.

• Ph.D. in Computer Science from Technical University of Darmstadt (2020)
• M.Sc. and B.Sc. in Software Engineering from Polytechnic University of Milan

His work emphasizes theoretical aspects of reinforcement learning, particularly policy gradient estimation and temporal-difference methods. Recent publications highlight innovations in data-driven teleoperation, movement primitives, and off-policy optimization, aligning with his goal of bridging simulation-to-reality gaps.

He teaches courses including Introduction to Robotics, Optimization and Numerical Computation, Machine Learning, and Data Analysis II. His research is disseminated via platforms like Google Scholar and samueletosatto.com.