Accepting PhD Students

PhD projects

Meta-learning of sensorimotor skills of robots.

Deep reinforcement learning of dynamic locomotion of legged robots.

Data-efficient learning of autonomous robotic manipulation.

Multi-contact motion planning of multi-limbed robots.

Immersive tele-operation with multi-sensory interface.

Autonomous delivery robot for last-mile logistics.

Bio-inspired robotic gripper for handling soft objects.

Personal profile

Research Interests

My research is about producing intelligent behaviours of a wide variety of robotic systems to achieve human-comparable abilities in motor/movement skills. I am interested in the research of generating skilful, agile, athletic, and well-coordinated physical motions and interactions through control theories, optimization and machine learning; and I am particularly keen to translate robotics and AI technologies to healthcare for the better quality of life and public well being, and to tackle waste recycling/cleaning to protect environments and sustain a green planet.

Qualifications

Postdoctoral researcher, Italian Institute of Technology, 2012 - 2016.

PhD in Robotics, Italian Institute of Technology and University of Genova, 2012.

Biography

Dr Li is a Lecturer in the School of Informatics at the University of Edinburgh. Before joining the Institute of Perception, Action and Behaviour (IPAB), he had been with the Italian Institute of Technology (IIT) since 2009, where he obtained the joint PhD degree from IIT and University of Genova, worked as a post-doctoral researcher, and led the locomotion group inside the Humanoid and Human Centred Mechatronics Lab at the Department of Advanced Robotics, IIT.

His past work focused on the development of a variety of balancing and dynamic walking control of humanoid and other legged robots. His current research aims to control the dynamic behaviour of a wide variety of robotic systems and to achieve human-comparable ability to move, manipulate, and grasp. He is particularly interested in producing skilful, agile, athletic, and well-coordinated physical motions and interactions through control theories, optimization and machine learning.

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