Prof.dr. Peter A.N. Bosman
Senior Researcher at Centrum Wiskunde & Informatica (CWI)
(Dutch National Research Institute for Mathematics and Computer Science)
Life Sciences and Health Research Group

Professor of Evolutionary Algorithms at Delft University of Technology
Algorithmics Section of the Department of Software Technology
Faculty of Electrical Engineering, Mathematics and Computer Science

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Prof.dr. Peter A.N. Bosman is a senior researcher heading the Medical Informatics (MI) subgroup of the Life Sciences and Health (LSH) research group at the Centrum Wiskunde & Informatica (CWI) (Center for Mathematics and Computer Science) located in Amsterdam, the Netherlands. He further has a part-time professor (in Dutch: deeltijdhoogleraar) position at Delft University of Technology in the Algorithmics group of the Department of Software Technology in the Faculty of Electrical Engineering, Mathematics, and Computer Science. Prof.dr. Bosman was formerly affiliated with Utrecht University, where he also obtained his M.Sc. and Ph.D. degrees in Computer Science.

Prof.dr. Bosman's fundamental research focus is on the design and application of Evolutionary Algorithms (EAs) for single- and multi-objective optimization, and Machine Learning (ML). The optimization problems considered are typically complex to an extent where a black-box optimization (BBO), or at least a grey-box optimization (GBO), perspective is required, i.e., virtually no information (BBO) or limited information (GBO) is available (or properly understood) about the problem at hand. The designed EAs are moreover mostly model-based, meaning that a model is used to capture and exploit problem-specific features to guide the search for high-quality solutions more effectively and efficiently. Such models may be derived by hand or, if this is not possible (as in e.g., the BBO case), be learned online, i.e., during optimization, using techniques from fields such as ML. For problems where efficient (problem-specific) heuristics (i.e., local search (LS) techniques) are available, model-based EAs are furthermore a very solid basis for hybridization to obtain the best of both worlds in terms of efficiency and effectiveness, resulting in state-of-the-art optimization algorithms for specific problems.

Prof.dr. Bosman's applied research focus is on the use of (model-based) EAs to solve real-world problems that require optimization and/or machine learning, which are often multi-objective in nature, together with industry- and societal partners. The primary domain of attention is the Life Sciences and Health (LSH) domain with a specific focus is on radiation oncology, including automated treatment planning, deformable image registration and 3D dose reconstruction. Other application areas include(d) smart energy systems, revenue management, transportation logistics, and patient-flow logistics.

Prof.dr. Bosman has (co-)authored over 150 peer-reviewed publications, out of which 6 received best paper awards and 9 more were nominated for a best paper award. Various other awards include 2 silver Humies awards (in 2021 and in 2019) for obtaining real-world human-competitive awards with EAs (in the medical domain). He is an officer, executive board, and business committee member of SIGEVO, the ACM special interest group on Genetic and Evolutionary Computation, as well as program committee member of various major conferences and journals in the EA field and related fields. In 2017, Prof.dr. Bosman was the General Chair of the main conference in the field of EAs - the Genetic and Evolutionary Computation Conference (GECCO). He has furthermore organized various workshops and tutorials on various EA related topics and has been (co-)track chair and (co-)local chair at GECCO. According to Google Scholar, his h-index is 36 with a total of 4321 citations to his works (as measured on January 18, 2022).

Finally, the (co-)acquired research grant funding by Prof.dr. Bosman totals over €8M, which includes funding from the Dutch research council, the Dutch cancer society, the Dutch children cancer-free foundation, and the European Innovation Council. Together, these grants support(ed) various scientific research positions (including 28 Ph.D. student positions as well as various postdoc, radiation therapy technologist, and scientific programmer positions), and various high-performance computing hardware.