Yun Li

Professor

Personal Statement

Professor Yun Li is currently with Faculty of Engineering at the University of Strathclyde. He received his BSc from Sichuan University, China, MEng from University of Electronic Science and Technology of China (UESTC), PhD from University of Strathclyde, and CBA from Adam Smith Business School of University of Glasgow. Following a period with UK National Engineering Laboratory as consultant engineer in 1989 and with Industrial Systems and Control Ltd as postdoctoral research engineer in 1990, he joined University of Glasgow as Lecturer in 1991, where later he served as Professor and Founding Director of University of Glasgow Singapore and Founding Director of University of Glasgow’s Joint Education Programme with UESTC. In March 2018, he moved to University of Strathclyde to deepen research into artificial intelligence (AI) for Industry 4.0 in the Department of Design, Manufacture and Engineering Management, and work as overseas Distinguished Professor at Dongguan University of Technology located in China’s manufacturing hub.

 

Research Interests

Prof Li’s research has mainly been concerned with transforming the simulation-based passive Computer-Aided Design (CAD) to the AI-enabled pro-active Computer-Automated Design (CAutoD), machine learning and “machine inventing”, especially for the dawning "Industry 4.0".  With data-driven prospects of computation akin to the human being, CAutoD offers intelligent search, learning and automation functionalities as services for optimal design, virtual prototyping and cyber-physical integration, applicable to electronic, electrical, mechanical, control, manufacturing, and biomedical engineering, operations management, financial and economic system modelling and optimisation. He developed one of the world’s first 30 evolutionary and neural computing courses in 1995 and its online interactive genetic algorithm (GA) courseware GA_demo, demonstrating also the working mechanism of CAutoD. He served on the Management Board of the European Network of Excellence in Evolutionary Computation (EvoNet), and established both the EvoNet Workgroup on Systems, Control, and Drives for Industry and the IEEE Computer-Aided Control System Design Evolutionary Computation Working Group.

 

Prof Li was General Chair of the EPSRC funded Industrial Systems in the Digital Age conference, “Looking Beyond Industry 4.0”, held in Glasgow in 2017. He has over 260 publications, among which one is noted the most popular in IEEE Transactions on Control Systems Technology every month and another most cited in IEEE Transactions on Systems, Man, and Cybernetics – Part B. Prof Li is a Chartered Engineer, an Associated Editor of IEEE Trans Evolutionary Computation and of IEEE Trans Emerging Topics in Computational Intelligence, and a Guest Editor of Smart Design, Smart Manufacture and Industry 4.0 Special Issue for Energies.

 

More publications of his may be downloaded from:
https://scholar.google.co.uk/citations?user=1NT1jFMAAAAJ
or http://eprints.gla.ac.uk/view/author/293.html

 

Industrial Relevance

R&D in artificial intelligence, evolutionary computation, optimisation, modelling and control for design, manufacture, engineering management and service, and Industry 4.0

 

Expertise & Capabilities

Artificial Intelligence; Evolutionary Computation; Optimisation, modelling and control for intelligent design, manufacture, engineering management and service; Industry 4.0.

 

Transnational Education, High Education management

 

Teaching Interests

In 1995, Yun Li developed one of the world's first 30 evolutionary and neural computing courses and, in 1997, the online interactive courseware GA_demo for this course and computer-automated design (CAutoD). 

Ha has an interest in teaching in artificial intelligence, evolutionary computation, optimisation, modelling, and control for intelligent design, smart manufacture, engineering management and services, and for Industry 4.0.

 

Academic / Professional qualifications

BSc, MEng, PhD, CBA, CEng

 

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    Research areas

  • Artificial Intelligence, Industry 4.0, Evolutionary Computation, Design and Manufacture, Optimization, Modelling and Control
Yun Li

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