Author: Petar Kormushev
Petar Kormushev is a Lecturer at Imperial College London doing research in robotics and machine learning. In 2009 he graduated with a PhD degree in Computational Intelligence from Tokyo Institute of Technology. His research interests include various forms of robot learning and machine learning algorithms, especially reinforcement learning for intelligent robot behavior. He holds a MSc degree in Artificial Intelligence, a MSc degree in Bio- and Medical Informatics, and a BSc degree in Computer Science from Sofia University. He has participated in many scientific projects, including European INFRAWEBS project for designing the future Semantic Web, and Japanese NEDO project for developing a common basis for next-generation robots. Since 2012 he is a technical coordinator of two FP7 projects (PANDORA and STIFF-FLOP) at IIT, and a co-chair of the IEEE RAS Technical Committee on Robot Learning. He has won a number of prestigious awards, including a “John Atanasoff” scholarship, a “St. Kliment Ohridski” award, and a 4-year Monbukagakusho/MEXT Japanese research fellowship.
Surgical robotic tools face dynamic environments, changing kinematics, and complex tasks. Machine learning can help us overcome these challenges.