Current Students

• Raphael Avalos - PhD Student on Multi-agent Deep Reinforcement Learning, Vrije Universiteit Brussel (VUB)
• Willem Röpke - PhD Student on Multi-Objective Multi-Agent Reinforcement Learning and Game Theory, Vrije Universiteit Brussel (VUB)


• Liam Mertens - Distributional Multi-objective Reinforcement Learning (MSc AI, VUB)
• Arno De Greef - Preference Learning for Accessible Route Planning (MSc AI, VUB)
• Robbe Thielemans - Multi-Objective Multi-Armed Bandits (MSc AI, VUB)
• Nicolas Rowies - TBA (MSc AI, VUB)

Former students:

• Dr Eugenio Bargiacchi - PhD Student on Multi-agent Reinforcement Learning, Vrije Universiteit Brussel (VUB)
• Dr Mathieu Reymond - PhD Student on Deep Multi-Objective Reinforcement Learning, Vrije Universiteit Brussel (VUB)
• Dr Conor F. Hayes - PhD Student on Multi-Objective Reinforcement Learning, National University of Ireland Galway (NUI Galway)
• Dr Roxana Rădulescu - Decision Making in Multi-Objective Multi-Agent Systems: A Utility-Based Perspective, Vrije Universiteit Brussel (VUB) [PhD thesis]
• Dr Denis Steckelmacher - Model-Free Reinforcement Learningfor Real-World Robots, Vrije Universiteit Brussel (VUB) [PhD thesis]


• Dr Luisa M. Zintgraf - Temporary Post-Master Researcher on User Preferences and Multi-Objective Decision Making, Vrije Universiteit Brussel (VUB)


• David Meertens - Research Intern on Data Science for Risk Assessment (MSc, UvA - Data Science, City of Amsterdam)
• Andrea Lombardo - Research Intern on Computer Vision for Sidewalk Issue Labelling (MSc, UvA - Artificial Intelligence, City of Amsterdam) [blog post]
• Kasper Verhavert - BSc Thesis Project on Classification of Sidewalk Issues (BSc, VUB - Computer Science, City of Amsterdam) [blog post]
• Alisa Todorova - BSc Thesis project on multi-objective path planning for accessibility (BSc, Maastricht University) [BSc thesis]
• Aditi Mishra - BSc Thesis project on preference ellicitation for accessible route planning (BSc, Maastricht University) [BSc thesis]
• Jeff v/d Kamer - Research Intern on Classification of Events in Timeseries Data on Low-Performance Hardware via Neural Networks (BSc, HU - Microsystems Technology) [BNAIC 2022 demonstration]
• Maaike Hovenkamp - Research Intern on Sensors and Data Analysis for Medical Devices (BSc, HU - Microsystems Technology) [BNAIC 2022 demonstration]
• Willem Röpke - MSc Thesis Project on Multi-objective Normal Form Games (with communication) (MSc, VUB) [ALA paper] [ALA video] [MODeM paper] [MODeM video]
• Ramon Petri - Research Project on Heuristics for Joint Action Selection in Multi-Agent Reinforcement Learning (BSc, HU) [BNAIC/BENELEARN paper]
• Sebastiaan Saarloos - Research Project on Multi-Objective Heuristic Search for Object Placing on Robots (BSc, HU)
• Niels Post - Research Intern on Physical Models for Simulation Validation (BSc HU / VUB) [Robot Featured on the Arduino Website!] [instructable]
• Yijie Zhang - Summer Project on Multi-Objective Multi-Agent Reinforcement Learning (MSc AI, VUA / VUB) [AAMAS ext. abstract] [ALA paper]
• Mathilde Theelen - Adaptive E-tutoring for Teaching Vocabulary (MSc AI, VU Amsterdam)
• Mark de Blaauw - Single-shot Learning for Logo Recognition (MSc BA, VU Amsterdam) [BNAIC extended abstract]
• Bertan Konuralp - Deep RL for Playing Snake (BSc CS, VU Amsterdam)
• Chris Dejevij - Many-Objective Queued Pareto Local Search (BSc CS, VU Amsterdam)
• Oktay Kavi - Interactive Top-Two Thompson Sampling for Multi-Objective Multi-Armed Bandits (BSc AI, VU Amsterdam)
• Kevin Waller - Per-option Discounting in Option-MCTS (BSc CS, VU Amsterdam)
• Ward van Rooij - Deep learning for radiology (MSc AI, VU Amsterdam)
• Ilse Goedhart - Personal data recognition (MSc BA, VU Amsterdam)
• Carmine Paolino - Music genre recognition (MSc AI, VU Amsterdam)
• Axel Abels - Multi-objective deep reinforcement learning with dynamic weights, Université Libre de Bruxelles (ULB, MSc)[ICML 2019 paper] [BNAIC extended abstract] [☆ Best student thesis abstract award at BNAIC 2018!]
• Kenzo Clauw - MSc thesis project on multi-objective planning in MOMDPs, Vrije Universiteit Brussel (VUB)
• Tanya Pedersen - AMSI Vacation Research Scholar (VRS) on guarantees for reinforcement learning in multi-objective multi-armed bandits, BSc Federation University (Australia)
• Manon Legrand - MSc thesis project on multi-agent deep reinforcement learning with autonomous cars, Université Libre de Bruxelles (ULB) [BNAIC extended abstract] [BNAIC demonstration]
• Hossam Mossalam (MSc. thesis - Multi-Objective Deep Learning, University of Oxford) [DeepRL (NIPS workshop) paper] [BNAIC extended abstract] [☆ Best student thesis abstract award at BNAIC 2016!]
• Maarten de Waard (MSc. thesis - Monte Carlo Tree Search with Options for General Video Game Playing, University of Amsterdam) [CIG paper]
• Joost van Doorn (Free project - Balancing Relevance Criteria in Information Retrieval via Multi-Objective Optimisation, University of Amsterdam) [SIGIR paper]
• Elise van der Pol and Carla Groenland (Project AI - Lorenz-optimal Optimistic Linear Support, University of Amsterdam)
• Auke Wiggers (MSc. thesis - zero-sum partially observable stochastic games, University of Amsterdam) [MSDM paper][Thesis]
• Maarten de Waard, Maarten Inja, Chiel Kooijman (Free project - Pareto Local Policy Search for MOMDPs, University of Amsterdam) [ESANN paper] [BNAIC extended abstract]
• Luisa Zintgraf, Phillip Beau, and Timon Kanters (Free project - Quality assessment of MORL algorithms, University of Amsterdam) [BENELEARN paper]
• Lieuwe Rekker (MSc thesis - Parameter estimation in competence models, University of Amsterdam) [thesis]
• Eugenio Bargiacchi (Free project - multi-agent reinforcement learning for RTS games, University of Amsterdam)
• Maarten de Waard, Maarten Inja, Chiel Kooijman (Free project - Queued Pareto Local Search, University of Amsterdam) [PPSN paper] [BNAIC ext.abstr.]
• Sander Latour (MSc thesis - Evolutionary Methods for Curriculum Sequencing, University of Amsterdam) [thesis]
• Chiel Kooijman (Bachelor thesis - multi-objective planning for broadcasting channels, University of Amsterdam)
• Eugenio Bargiacchi, Camiel Verschoor, Anna Keune, Steven Laan (Project AI - multi-agent reinforcement learning for RTS games, University of Amsterdam) [BNAIC demo]
• Evert Rozendaal (Bachelor thesis - Document output bij Nedasco, Utrecht University of Applied Sciences [Hogeschool Utrecht])

Courses taught

2019-2022 at HU University of Applied Science Utrecht:

• Advanced Technical Programming, 3rd year Technical Computer Science, HU
• Research and Advice, 2nd year Technical Computer Science, HU
• Computer Vision, 2nd year Technical Computer Science, HU
• Algorithms and Data Structures, 2nd year Technical Computer Science, HU
• C++ Programming and Software Engineering, 2nd year Technical Computer Science, HU
• Programming, 1st year HBO-ICT, HU

Before 2020 at various academic institutions

• Master course on Reinforcement Learning, 2018-2019, Vrije Universiteit Amsterdam
• Master course on Reinforcement Learning, 2017-2018, Vrije Universiteit Brussel (VUB)
• CS4010 Algorithms for Planning and Scheduling 2016-2017 and 2017-2018 (TU Delft) as guest-lecturer and project supervisor (2016-2017)
• Autonomous Agents 2014-2015 (UvA) as lecturer [datanose]
• Autonomous Agents 2013-2014 (UvA) as co-lecturer
• Autonomous Agents 2012-2013 (UvA) as TA
• Advanced bachelor courses (HU), amongst others:
  • Computer Vision,
  • ERP,
  • Business Intelligence Technology 1,
  • HTML5 and CSS3,
  • Seminar Collective Intelligence,
  • Databases 4 (Data mining)
• Elementary bachelor courses (HU) like programming, databases and project management.