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Biography
Ender Özcan is a Professor of Computer Science and Operational Research with the Computational Optimisation and learning (COL) Lab in the School of Computer Science at the University of Nottingham, UK (UoN). He received his PhD from the Department of Computer and Information Science at Syracuse University, NY, USA in 1998. He worked as a lecturer in the Department of Computer Engineering at Yeditepe University, Istanbul, Turkey from 1998-2007. He established and led the Artificial Intelligence research group from 2002. He served as the Deputy Head of the Department from 2004-2007. Prof Özcan was appointed as a senior research fellow in 2008 to the EPSRC funded LANCS initiative, which was one of the largest Science and Innovation Rewards given by EPSRC (Engineering and Physical Sciences Research Council, UK). He became a lecturer in 2009. He served as an executive committee member for the LANCS initiative. Prof Özcan was the Deputy Director of the EPSRC's National Taught Course Centre in Operational Research (NATCOR). He was on the advisory board of the first Cross-domain Heuristic Search Challenge (CHeSC 2011) and co-organised the second challenge (CHeSC 2014). He chaired the PATAT 2014 conference. His research interests and activities lie at the interface of Computer Science, Artificial Intelligence and Operational Research, with a focus on intelligent decision support systems combining data science techniques, heuristics, hyper-heuristics, and metaheuristics applied to real-world optimisation and decision support problems. Prof Özcan has over 140 refereed publications at reputable venues. He is a Senior Member of IEEE and elected member of the EPSRC college. Prof Özcan has been awarded grants as principal investigator and co-investigator/named researchers from various funding bodies, including the European Commission, The Royal Society, TSB, The Scientific and Technological Research Council of Turkey, T.R. Prime Ministry State Planning Organisation and CONACyT. Prof Özcan is a co-founder and co-chair of the EURO Working Group on Data Science Meets Optimisation. He was Associate Editor of the IEEE Transactions on Emerging Topics in Computational Intelligence. He is Associate Editor of the Journal of Scheduling and International Journal of Applied Metaheuristic Computing. He is Steering Committee member and Executive Officer of the International Conference Series on the Practice and Theory of Automated Timetabling (PATAT).
Expertise Summary
My expertise lies at the interface of Computer Science, Artificial Intelligence (AI) and Operational Research, with a focus on intelligent decision support systems embedding data science, mainly machine learning and heuristic,hyper-heuristic and metaheuristic optimisation techniques applied to real-world optimisation and decision support problems.
Keywords: artificial intelligence, optimisation, intelligent decision support, heuristic, metaheuristic, hyper-heuristic, evolutionary algorithm, adaptive approaches, timetabling, cutting and packing
Teaching Summary
I have been teaching informed by my research and scholarly activities exploiting my industrial links, and leading teaching innovation through the development and delivery of the undergraduate… read more
Research Summary
My research interests and activities lie at the interface of artificial intelligence, computer science, and operational research: Intelligent decision support systems, search and optimisation,… read more
Current Research
My research interests and activities lie at the interface of artificial intelligence, computer science, and operational research: Intelligent decision support systems, search and optimisation, including combinatorial optimisation, constraint optimisation, multi-modal optimisation and multi-objective optimisation using heuristics, local search, hyper-heuristics, metaheuristics, in particular memetic algorithms, particle swarm optimisation, hybrid approaches embedding data science techniques and their theoretical foundations.
Modelling of and applications to the complex real-world problems, including scheduling, timetabling, cutting&packing, SAT, knapsack problems, TSP, VRP and more, that are at the boundary of artificial intelligence, computer science and operational research, including grouping problems, such as, data clustering, graph colouring and bin packing.