Professor Yaxin Bi

Overview

Yaxin Bi is a Professor in the School of Computing at Ulster University and a core member of the Artificial Intelligence Research Centre within the School. He has over thirty years of research experience in Artificial Intelligence and its applications. He has a BSc (Hons) in Computing Science, an MSc by research in Computing Application, and a PhD in the area of Text Categorization with ensemble learning approaches. He is a Senior Fellow of the Higher Education Academy, UK.

Yaxin’s research interests include machine learning and ensemble learning in conjunction with the Dempster-Shafer theory of evidence. He has pioneered ensemble approaches for combining multiple classifiers using Dempster’s rule of combination, as well as measuring the diversity impact of evidential classifiers with varying metrics. He has secured more than £5 million in research funding from the funding bodies of the European Space Agency, the EU Frameworks and Horizon 2020 programs, Knowledge Transfer Partnership (KTP), Invest NI, and the Royal Society, UK, etc.

His research extends to the development of data analytics and decision-making methods under uncertainty to tackle real-world challenges in a wide range of applications. These include anomaly/change detection in satellite data and manufacturing process, energy consumption and generation analysis, crop classification and disease detection, generative simulation and digital twin, sentiment analysis, and sensor fusion for activity/event recognition. Yaxin has published over 200 peer-reviewed papers across international journals, edited books, book chapters and conference proceedings.

Yaxin held key roles for various international conferences and workshops as a general co-chair and program co-chair. He served as an associate editor for the International Journal of Artificial Intelligence Review (2015-2020). Currently, he serves as an associate editor for the International Journal of Intelligent Systems and an editorial board member of Real-World Data Science (Royal Statistical Society, UK), as well as a steering committee member for both the International Conference on Knowledge Science, Engineering, and Management (KSEM) and the Science and Information (SAI) Conference.