Peter Bosman

Full Name
Prof.dr. P.A.N. Bosman
Email
Phone
+31 20 592 4265
Room
M276
Department(s)
Function(s)
Scientific Staff Member, Group leader
Peter Bosman

Research

Prof.dr. Peter A.N. Bosman is the group leader of the Evolutionary Intelligence 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. A key application area is the medical domain, where research outcomes have successfully been translated into clinical practice (in particular the automated optimization of brachytherapy treatment plans for prostate cancer, at Amsterdam UMC). Additional application areas include (smart) energy systems, revenue management, and logistics.

Prof.dr. Bosman has (co-)authored over 200 peer-reviewed publications, out of which 9 received best paper awards and 10 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 currently chair of SIGEVO, the ACM special interest group on Genetic and Evolutionary Computation and was formerly an officer, executive board, and business committee member of SIGEVO. He is furthermore program committee member of all major conferences and various journals in the EA field and related fields. Prof.dr. Bosman has been general chair, track chair, and local chair as well as organizer of various workshops and tutorials at the main conference in the field of EAs - the Genetic and Evolutionary Computation Conference (GECCO). According to Google Scholar, his h-index is 41 with over 5800 citations to his works.

Finally, the (co-)acquired research grant funding by Prof.dr. Bosman totals over €10M, 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.

Publications

All publications

Awards

  • Best Paper Award at EMO 2023 for "Multi-objective Learning Using HV Maximization" (2023)
  • Best Paper Award in track: Neuroevolution, of GECCO 2022 (2022)
  • Best Paper Award in track: Genetic Programming, GECCO 2022 (2022)
  • Best Paper award at EMO 2021 (2021)
  • Best Paper Award in track: Genetic Algorithms, GECCO 2021 (2021)
  • Silver "HUMIES" Award for Human-Competitive Results Produced by Genetic and Evolutionary Computation (2021)
  • Brachytherapy Award at ESTRO 2019 (2019)
  • Silver "HUMIES" Award for Human-Competitive Results Produced by Genetic and Evolutionary Computation (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)

Professional activities

  • Committee member: Genetic and Evolutionary Computation Conference - [GECCO]
  • Committee member: International Conference on Parallel Problem Solving from Nature - [PPSN]
  • Speaker: Invited Lecture at the Optimization by Building and Using Probabilistic Models - OBUPM workshop at the Genetic and Evolutionary Computation Conference - GECCO
  • Organizer: (Local Chair) The International Conference on Computational Management Science - CMS.
  • Committee member: The IEEE Congress on Evolutionary Computation
  • Speaker: Invited Lecture at the Optimization by Building and Using Probabilistic Models - OBUPM workshop at the Genetic and Evolutionary Computation Conference - GECCO
  • Speaker: Invited Lecture at the seminar of the Department of Logistics, University of Mannheim
  • Nominated: Best Paper Nomination in track: EMO, GECCO 2006
  • Speaker: Invited Lecture at the IPA Herfstdagen on "Beyond Turing"
  • 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]
  • Lecturer: Technische Universiteit Delft - [TUD]
  • Speaker: Invited Lecture at the seminar on Operations Research of CentER (business & economics research insitute of Tilburg University)
  • Speaker: Invited Lecture at the Dagstuhl Seminar Sampling-based Optimization in the Presence of Uncertainty
  • Speaker: Invited Lecture at the Optimization by Building and Using Probabilistic Models - OBUPM workshop at the Genetic and Evolutionary Computation Conference
  • Speaker: Invited Lecture at the ORMS seminar of Warwick Business School
  • Speaker: Invited Lecture at the minisymposium Issues of Modeling & Uncertainty in Simulation-Based Applications of Optimization at the SIAM Conference on Optimization
  • Speaker: Invited Lecture at the Bridging the Gap (BTG) Workshop 7 on Dynamic Optimisation in an Uncertain World: Challenges and State-of-the-Art
  • Nominated: Best Paper Nomination in track: GA, GECCO 2007
  • Nominated: Best Paper Nomination, PPSN XII
  • Committee member: Benelux Conference on Artificial Intelligence - [BNAIC]
  • Organizer: (Tutorial organizer) Genetic and Evolutionary Computation Conference - [GECCO] - Model-Based Evolutionary Algorithms
  • Speaker: Invited Lecture at the physics seminar of the department of Radiation Oncology at the Amsterdam Medical Center (AMC)
  • Nominated: Best Paper Nomination, SSCI 2013
  • Nominated: Best Paper Nomination, PPSN XII
  • Speaker: Invited Lecture at the IPA Herfstdagen on "Algorithms and Models for Real-Life Systems"
  • Side Position: Treasurer - Koninklijk Wiskundig Genootschap - [KWG]
  • Nominated: Best Paper Nomination in track GA, GECCO 2016
  • Speaker: Invited Lecture at the bi-annual RKF (Radiotherapeutische Klinische Fysica) Scientific Project Day
  • Speaker: Invited Lecture at the Model-Based Evolutionary Algorithms - MBEA workshop at the Genetic and Evolutionary Computation Conference - GECCO
  • Speaker: Invited Lecture at the seminar of the ALICE research group at the University of Groningen
  • Nominated: Best Paper Nomination in track: ENUM, GECCO 2017
  • Speaker: Invited Lecture at the Victoria University of Wellington, New Zealand
  • Speaker: Invited Lecture at Queensland University, Australia
  • Speaker: Invited Lecture at Royal Melbourne Institute of Technology, Australia
  • Speaker: Invited Lecture at University of New South Wales, Australia
  • Speaker: Invited Lecture at University of Adelaide, Australia
  • Speaker: Invited Lecture at TAU and RANDOPT research groups of INRIA Saclay, Paris
  • Speaker: Invited Lecture at Health Track (plenary talk) in the Conference for ICT-Research in the Netherlands (ICT.OPEN)
  • Speaker: Invited Lecture at AMC Radiation Oncology reference meeting
  • Speaker: Invited lecture at department research meeting of the Medical Informatics department at the Academic Medical Center (AMC)
  • Speaker: Invited Lecture at the seminar of the AI section of the Department of Computer Sciences of the Vrije Universiteit Amsterdam
  • Nominated: Best Paper Nomination in track: Genetic Algorithms, GECCO 2018
  • Speaker: Invited Lecture at Delft AI Meetup.
  • Speaker: Invited Lecture at Amsterdam Medical Data Science / Amsterdam Data Science meetup
  • Board Member: ACM SIGEVO executive board.
  • Executive: ACM SIGEVO Officer.
  • Speaker: Invited Lecture at the symposium on "Inverse planning in brachytherapy - A one click solution?" at the European Society for Radiotherapy and Oncology (ESTRO)
  • Executive Board Member: ACM SIGEVO Business Committee.
  • Nominated: Best Paper Nomination in track: ENUM, GECCO 2020
  • Board Member: Scientific Advisory Board of the Hanarth Fund.
  • Speaker: Invited Lecture at 75th anniversary celebration of CWI.
  • Speaker: Invited Lecture at the symposium on ``Machine learning, artificial intelligence and big data for precision medicine'' at the World Congress of Brachytherapy. 2021
  • Speaker: Invited lecture at Booking
  • Speaker: Invited Lecture at University Fund Delft Masterclass series.
  • Speaker: Invited lecture at Philips
  • Speaker: Invited Lecture at the “AI in Oncology” seminar at TU Delft.
  • Speaker: Keynote at the International Symposium on Late Complications After Childhood Cancer (ISLCCC)
  • Nominated: Best Paper Nomination in track: RWA, GECCO 2022

Grants

  • (co-applicant) Stichting Gieskes-Strijbis Fonds, "Uitlegbare Kunstmatige Intelligentie" (2021)
  • NWO-TTW Open Technology Programme, "DAEDALUS – Decentralized and Automated Evolutionary Deep Architecture Learning with Unprecedented Scalability" (2020)
  • (co-applicant) Horizon 2020 FET Proactive, "TRUST-AI – Transparent, Reliable and Unbiased Smart Tool for AI" (2020)
  • NWO Open Competition Domain Science – KLEIN-2 programme, "EXAMINE – Evolutionary eXplainable Artificial Medical INtelligence Engine" (2019)
  • (co-applicant) Dutch Cancer Society (KWF), "Fast, accurate, and insightful brachytherapy treatment planning for cervical cancer through artificial intelligence" (2019)
  • NWO-ENW Joint eScience and Data Science across the Topsectors Programme, "FEDMix: Fusible Evolutionary Deep Neural Network Mixture Learning from Distributed Data for Robust Medical Image Analysis" (2017)
  • ᅠNVIDIA GPU Grant Programme,ᅠ"Support for the GPU-based Acceleration of Gene-pool Optimal Mixing Evolutionary Algorithms" (2017)
  • (co-applicant) NWO-TTW Open Technology Programme, "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 Content Mismatch and Large Deformations" (2017)
  • (co-applicant) Nijbakker-Morra Stichting, "High Performance Computing System for Research into Mapping Out more Accurately than Ever Before the Irradiation-Induced Long-Term Effects after Surviving Childhood Cancer." (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)
  • (co-applicant) Maurits en Anna de Kock Stichting, "High Performance Computing System for the Accurate Reconstruction of the 3D Dose Distribution for Children with Cancer who have been Treated in the Past." (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)
  • (co-applicant) KiKa multiannual research projects, "3D dose reconstruction for children with long-term follow-up - Toward improved decision making in radiation treatment for children with cancer." (2014)
  • EIT ICT Labs, "Market-driven Simulation Software for Smart Energy Systems" (2013)
  • EIT ICT Labs, "Market-driven Simulation Software for Smart Energy Systems" (2012)
  • (co-applicant) NWO free competition programme, "Estimation of Distribution Algorithms for Mixed Continuous-Discrete Problems." (2011)
  • EIT ICT Labs, "Market and organisational mechanisms and intelligent planning methods for smart energy systems." (2011)
  • (co-applicant) NWO Smart Energy Systems programme, "Computational Capacity Planning in Electricity Networks" (2010)

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)
  • Uitlegbare kunstmatige intelligentie (None)
  • Transparent, Reliable and Unbiased Smart Tool for AI (TRUST-AI)

Courses