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Philippe De Wilde

Philippe De Wilde

Professor, AI, University of Kent
Prof. Philippe de Wilde is a Professor of Artificial Intelligence in the Division of Natural Sciences at the University of Kent, United Kingdom. He promotes the use of artificial intelligence and machine learning in Biosciences, Pharmacy, Sports and Exercise Sciences, Physics, Chemistry, Forensics, and the Medical School. Between 2014 and 2020 Prof. De Wilde was Deputy Vice-Chancellor (US: Vice-President) for Research & Innovation at the University of Kent. He had responsibility for strategy and policy development, and line-managed Research Services, Kent Innovation & Enterprise, and the Graduate School. Between 2007 and 2014 Prof. De Wilde was Head (US: Dean) of the School of Mathematical and Computer Sciences and a member of the University Executive, Heriot-Watt University, with campuses in Edinburgh, Dubai, and Malaysia. Prof. De Wilde obtained the PhD degree in mathematical physics and the MSc degree in computer science in 1985 from Ghent University, Belgium. He was Lecturer and Senior Lecturer in the Department of Electrical Engineering, Imperial College London, between 1989 and 2005. Before 1989 he worked in Belgium at KU Leuven in applied mathematics and IMEC, also in Leuven, on microelectronics. Laureate, Royal Academy of Sciences, Letters and Fine Arts of Belgium, 1988. Research Fellow, British Telecom, 1994. Vloeberghs Chair, Free University Brussels, 2010. He has published 60 journal papers and 56 conference papers. He has published four books, including "Neural Network Models'', Springer, 1997, and "Convergence and Knowledge-processing in Multi-agent Systems'', Springer, 2009. He started contributing to multi-layer feedforward neural networks in 1987. His work with British Telecom from 1994 to 1999 has contributed to scalable mobile apps. Prof. De Wilde is a Fellow of the British Computer Society, a Fellow of the Institute of Mathematics and its Applications, and a Senior Member of IEEE. His current research is in computational neuroscience, biomedical signal processing, statistical learning, remote sensing, crowd behaviour, AI in health, and human-compatible AI.

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