Jun Liu received the B.Sc. and M.Sc. degrees in applied mathematics in
1993 and 1996, respectively, and the Ph.D. degree in Information
Engineering and Control in 1999 from the Southwest Jiaotong
University, Chengdu, China.
Dr Jun Liu is currently a Senior Lecturer in Computer Science, a full research member of Artificial Intelligence and Applications Research Group at Computer Science Research Institute. Before he joined Ulster University, he was a Postdoctoral Research Fellow at The University of Manchester, UK (Feb. 2002 - Dec. 2004), and a Postdoctoral Research Fellow at Belgian Nuclear Research Centre (SCK*CEN) (Mar. 2000 -Feb. 2002). He received the BSc. and MSc. degrees in Applied Mathematics, and PhD. degree in Information Engineering from Southwest Jiaotong University, Chengdu, China, in 1993, 1996, and 1999, respectively.
He has been working in the field of Artificial Intelligence for many years. His current research is focused on two themes: 1) Intelligent decision methodologies using techniques from systems theory, operational research and artificial intelligence, with applications in management, engineering, and industry field etc. (e.g., safety and risk analysis; policy decision making; security/disaster management; heath care and smart home; situation awareness and emergency systems, and scenario/activity recognition); 2) logic and automated reasoning methods for intelligent systems. In particular: resolution-based automated reasoning methods, algorithm and tools with applications (including software verification and automated theorem proving); lattice-valued logics with focus on handling incomparability, inconsistency and imprecision. He has published over 130 papers in peer-reviewed international journals and conferences.
Main Research Interests:
- non-classical logic and automated reasoning methods
- lattice-value logic and reasoning systems to treat incomparability
- applied computational intelligence for uncertainty analysis
- logic based Intelligent systems
- data mining and knowledge-based systems (knowledge and rule
acquisition, representation, and inference)
- information fusion and data combinations
- intelligent decision support systems and soft computing
applications to information management, with applications in management,
engineering, industry field etc (e.g., safety and risk analysis)
- situation awareness, information security, and emergency systems