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Holger H. Hoos is a Professor of Computer Science and a Faculty Associate at the Peter Wall Institute for Advanced Studies at the University of British Columbia (Canada). His main research interests span empirical algorithmics, artificial intelligence, bioinformatics and computer music. He is known for his work on the automated design of high-performance algorithms - notably, the Programming by Optimization (PbO) paradigm - and on stochastic local search methods. Holger is a co-author of the book "Stochastic Local Search: Foundations and Applications", and his research has been published in numerous book chapters, journals, and at major conferences in artificial intelligence, operations research, molecular biology and computer music. His publications have received several awards, including two IJCAI-JAIR Best Paper Prizes. He is an Associate Editor of the Journal of Artificial Intelligence Research (JAIR) and past president of the Canadian Artificial Intelligence Association / Association pour l'intelligence artificielle au Canada (CAIAC). His group has helped UBC to produce better exam timetables, Actenum Inc. to increase production efficiency in the oil and gas industry, and IBM to improve their CPLEX optimisation software, which is used by 50% of the world's largest companies and thousands of universities.
For further information, see Holger's web page at http://www.cs.ubc.ca/~hoos