Dr Chunxu Li received his PhD degree from Swansea University in 2019, and was appointed as a lecturer at the School of Engineering, Computing and Mathematics, University of Plymouth in January 2020. He has published 34 academic papers, 32 of which are SCI/EI indexed, and won the Best Student Paper Award and was shortlisted for the Best Paper Award in IEEE international conferences. He has expertise in ROS, JAVA, C++, Python and MATLAB with over 6 years working experience on multiple robot platforms, e.g., KUKA iiwa, Baxter, NAO, Universal, etc. He successfully integrated motion/colour tracking technology with robot control and machine learning algorithms into the development of advanced robot teaching systems and force-feedback based teleoperation systems. 

Dr Li is an Associate Fellow of the Higher Education Academy and a member of IEEE (Institute of Electrical and Electronics Engineers). As the main co-investigator, he successfully completed a number of EU projects. He contributed to the execution of several manufacturing projects in ASTUTE as the leading robotic expert. He was also involved in several international consultancy projects. Since the first paper was published in 2016, it has been cited 301 times in total, with h index of 12 and h10 index of 13. He has set up a strong collaborative framework with the University of Manchester, Swansea University, Leeds University, and University of Bristol.

• He is a member of Institute of Electrical and Electronics Engineers (IEEE).
• He is an associate fellow of the Higher Education Academy (HEA).

I am a reviewer for below listed journals:

• Sensors 
• Connection Science
• IEEE Access
• Applied Sciences
• International Journal of Intelligent Robotics and Applications

Module Leader of AINT308 Computer Vision and Behavioral Computing

Providing an advanced knowledge of artificial vision systems for interactive systems guidance and control, this module is underpinned by current theoretical understanding of animal vision systems.

Module Leader of AINT515Z Artificial Vision and Deep Learning

This module will provide an advanced knowledge of artificial vision systems and deep learning neural networks. It will be underpinned by current theoretical understanding of vision algorithms and deep learning neural network models. This module will also introduce the use of deep learning models and vision systems.

Co-teaching of AINT516Z Topics in Advanced Intelligent Robotics

This module introduces the research activities of the Centre for Robotics and Neural Systems (CRNS). It is taught by CRNS members who lead thematic workshops on their own areas of expertise, such as swarm robotics, cognitive robotics, Human-Robot Interaction, and bio-inspired cognitive architectures. The module also covers scientific research methods and data analysis.

PhD Supervision as DoS

Shuo Zhu