Peter A.N. Bosman
Scholar

Peter A.N. Bosman

Google Scholar ID: YED2pAoAAAAJ
Centrum Wiskunde & Informatica (CWI)
Evolutionary ComputationOptimizationMachine LearningArtificial IntelligenceComputer Science
Citations & Impact
All-time
Citations
3,266
 
H-index
24
 
i10-index
73
 
Publications
20
 
Co-authors
25
list available
Resume (English only)
Academic Achievements
  • Has (co-)authored over 250 peer-reviewed publications, with 9 receiving best paper awards and 11 more nominated for best paper awards. Has received two silver Humies awards for obtaining real-world human-competitive results with EAs in the medical domain. Currently chairs SIGEVO, the ACM special interest group on Genetic and Evolutionary Computation, and has been an officer, executive board member, and business committee member of SIGEVO. He is a program committee member of all major conferences and various journals in the EA field and related fields. He has served as general chair, track chair, and local chair, as well as organized various workshops and tutorials at the main conference in the field of EAs - the Genetic and Evolutionary Computation Conference (GECCO).
Research Experience
  • Currently the group leader of the Evolutionary Intelligence research group at Centrum Wiskunde & Informatica (CWI) in Amsterdam, Netherlands. He is also a part-time full professor at Delft University of Technology in the Algorithmics group. His research focus is on the use of (model-based) EAs to solve real-world problems that require optimization and/or machine learning, with a key application area being the medical domain, such as the automated optimization of brachytherapy treatment plans for prostate cancer at Amsterdam UMC.
Education
  • Obtained M.Sc. and Ph.D. degrees in Computer Science from Utrecht University.
Background
  • Research interests include the design and application of modern model-based Evolutionary Algorithms (EAs) for single- and multi-objective optimization, and Machine Learning (ML). Particularly interested in using model-based EAs to achieve eXplainable AI (XAI). On the optimization side, he focuses on complex problems that typically require black-box optimization (BBO) or at least grey-box optimization (GBO).
Miscellany
  • Additional application areas include (smart) energy systems, revenue management, and logistics.