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Haiying Wang

Haiying Wang

Lecturer
Computer Science Research Institute
School of Computing and Mathematics
University of Ulster

UK Tel: 44 28 90368908

Biography

Haiying Wang(BEng, MSc, PhD, PgCHET) is a Lecturer in Computer Science within the School of Computing and Mathematics, Faculty of Computing and Engineering, University of Ulster. He is a member of the Artificial Intelligence and Applications Research Group in the Computer Science Research Institute, University of Ulster.Wang received the BEng and MSc in Optical Engineering from Zhejiang University, China, in 1987 and 1989 respectively. Before he joined the University of Ulster in 2000 as a research student funded by the University VCRS Award in 2000, he was a senior engineer in Fujian Electronic Technology Institute, China. He received his PhD degree on artificial intelligence in biomedicine in 2004. After two years post doctoctoral research, he took the current post as a lecturer in Computer Science in 2006.Wang is an active researcher in bioinformatics and medical informatics. His current research focuses on the areas at the intersection of computer science and biomedical sciences with an emphasis on the development of network-based approaches to predicting protein interaction networks and drug target associations. It comprises machine and statistical learning methods to support predictive data analysis, complex network analysis, community detection, data integration, pattern discovery and visualisation in medical informatics and bioinformatics. Since 2004, he has published more than 80 peer-reviewed papers in journals, books and conference proceedings.

Research

Network-based approaches to the prediction of drug target interactions,pattern discovery and visualisation with self-adaptive and self-organizing neural networks,complex networks and their dynamics,large scale data visulisation and representation,systems biology appraoches to the prediction of protein interaction networks and biomarker discovery and Statistical and machine learning approaches in gait monitoring and analysis.