Raffaello Camoriano

Raffaello Camoriano is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Polytechnic University of Turin. He is also an Affiliated Researcher at the Istituto Italiano di Tecnologia. His academic work spans multiple roles including serving as an Editorial Board Member for MACHINE LEARNING journal (since 2024) and Associate Editor for IEEE ROBOTICS AND AUTOMATION LETTERS (since 2022). He is an active member of IEEE Robotics and Automation Society (since 2024) and ELLIS - European Laboratory for Learning and Intelligent Systems (since 2022).

Dr. Camoriano's research focuses on the intersection of artificial intelligence, machine learning, and robotics. His work particularly emphasizes robot learning, incremental/lifelong learning, structured learning, and kernel methods. His research has significant applications in medical robotics, particularly in laser-based skincare procedures and prosthetic control systems. He has developed innovative approaches for federated learning, point cloud processing for robotics, and trajectory generation for humanoid robots. His work bridges theoretical machine learning with practical robotics applications, addressing challenges in resource efficiency, adaptation to changing environments, and human-robot interaction.

His recent publications demonstrate a strong trajectory in advancing federated learning techniques, with particular emphasis on resource-efficient personalization and handling heterogeneous data. He has made significant contributions to robotics applications including upper-limb prosthetics using high-density sEMG, autonomous navigation using point clouds, and medical robotics for laser procedures. His work consistently combines theoretical machine learning advances with concrete robotics applications, showing expertise in both domains.

• Best PhD Thesis Award of the Computational Intelligence Society Italy Chapter 2017

Dr. Camoriano actively supervises PhD students in the Intelligenza Artificiale program, including Stephany Ortuno Chanelo, Andrea Protopapa, and Leonardo Iurada. He has led research projects including the ECML-PKDD 2023 International Workshop 'Adapting to Change: Reliable Learning Across Domains' and the International Workshop 'Learning Meets Model-based Methods for Manipulation and Grasping' (2023). His teaching portfolio includes Fundamentals of Artificial Intelligence, Machine and Deep Learning, and Algorithms and Programming across multiple engineering programs at Polytechnic University of Turin.