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PROFILE

Assistant Professor

Dr. Harris Papadopoulos

Short CV

Harris Papadopoulos is an Assistant Professor at the Department of Electrical Engineering, Computer Engineering and Informatics of Frederick University, where he is also heading the Computational Intelligence (COIN) Laboratory. He is also a Visiting Fellow of the Computer Learning Research Centre of Royal Holloway, University of London, UK. He obtained a B.Sc. (first Class Hons) degree in Computer Science and a Ph.D. degree in Machine Learning from Royal Holloway, University of London in 1999 and 2004, respectively. His main research interests focus on the development of novel machine learning techniques that accompany their predictions with probabilistically valid measures of confidence and on the application of such techniques to a variety of problems and scientific fields. He has published more than 50 research papers in prestigious international refereed journals and conferences in the field of Machine Learning. He was also co-editor of the book “Measures of Complexity: Festschrift in Honor of Alexey Chervonenkis” published by Springer in 2015, which was dedicated to one of the most significant figures in the area of Machine Learning. He has been involved in several funded research projects with a total budget of more than 2.5 million euro. He has also recently secured an industrial grant (of more than 40,000 euro per annum) for the application of Machine Learning techniques to large volumes of data, from one of the biggest international consulting companies for complicated assets. He served as an Associate Editor of the Evolving Systems Journal (Springer) from 2015 to 2018 and as guest editor and reviewer for numerous esteemed scientific journals. He served as one of the main organizers of several international conferences and workshops (General Chair of AIAI 2013, Organizing Chair of AIAI 2010, PC Chair of eight conferences and Chair of nine workshops). Finally, he participated in the Program Committee of many prestigious international conferences, including IJCNN, INNS Conference on Big Data and ICANN.