Peter Bosman

Full Name
Prof.dr. P.A.N. Bosman
Group leader, Scientific Staff Member
+31 20 592 4265
Life Sciences and Health


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 5 received best paper awards and 10 more were nominated for a best paper award. According to Google Scholar, his h-index is 35 with a total of 4077 citations to his works (as measured on June 24, 2021). Various other awards include a silver Humies award 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.


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, the associated projects fund(ed) various scientific research positions (including 24 Ph.D. student positions and various postdoc, radiation therapy technologist, and scientific programmer positions), and various high-performance computing hardware.


Current projects with external funding

  • Fast, accurate, and insightful brachytherapy treatment planning for cervical cancer through artificial intelligence (Brachytherapy treatment)
  • Distributed and Automated Evolutionary Deep Architecture Learning with Unprecedented Scalability (DAEDALUS)
  • Evolutionary eXplainable Artificial Medical INtelligence Engine (EXAMINE)
  • Fusible Evolutionary Deep Neural Network Mixture Learning from Distributed Data for Robust Medical Image Analysis (FEDMix)
  • Multi-Objective Deformable Image Registration (MODIR) – An Innovative Synergy of Multi-Objective Optimization, Machine Learning, and Biomechanical Modeling for the Registration of Medical Images with (MODIR)
  • Uitlegbare kunstmatige intelligentie (None)
  • Transparent, Reliable and Unbiased Smart Tool for AI (TRUST-AI)

Professional activities

  • Committee member: Genetic and Evolutionary Computation Conference - [GECCO]
  • Committee member: International Conference on Parallel Problem Solving from Nature - [PPSN]
  • Committee member: European Workshop on Evolutionary Computation in Transportation and Logistics -[EvoTRANSLOG miv 2010 EvoApplications]
  • Committee member: European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments - [EvoSTOC miv 2010 EvoApplications]
  • Committee member: The IEEE Congress on Evolutionary Computation
  • Committee member: Benelux Conference on Artificial Intelligence - [BNAIC]
  • Committee member: Member review committee - Research Grants Council, Hong Kong
  • Committee member: Member program committee,
  • Editor: Journal: Journal of Applied Metaheuristic Computing - [IJAMC]
  • Lecturer: Technische Universiteit Delft - [TUD]
  • Organizer: Tutorial organizer - Genetic and Evolutionary Computation Conference - [GECCO] - Model-Based Evolutionary Algorithms
  • Side Position: Treasurer - Koninklijk Wiskundig Genootschap - [KWG]


  • ᅠNVIDIA GPU Grant Programme,ᅠ"Support for the GPU-based Acceleration of Gene-pool Optimal Mixing Evolutionary Algorithms" (2017)
  • STW-KWF Partnership Programme,ᅠᅠ"Improving Childhood Cancer Care when Parents Cannot be There - Reducing Medical Traumatic Stress in Childhood Cancer Patients by Bonding with a Robot Companion" (2016)
  • NWO Innovatieve PPS in ICT (IPPSI) - Technology Area (TA) programme,ᅠᅠ"ICT-based Innovations in the Battle against Cancer - Next-Generation Patient-Tailored Brachytherapy Cancer Treatment Planning",ᅠᅠ2015. (2015)


  • Humies Silver Award (2019)
  • Best paper award: Genetic and Evolutionary Computation Conference 2015, Madrid, Spain (2015)
  • Best paper award: Genetic and Evolutionary Computation Conference 2013, Amsterdam, The Netherlands (2013)
  • Best paper - Genetic and Evolutionary Computation Conference , Portland, Oregon, USA (2010)
  • Best paper: BNAIC (Benelux Conference on Artificial Intelligence) - Eindhoven, The Netherlands (2009)