Actual Course Info
In the 2019-20 study year I teach AI: Principles and Techniques (former Search, Planning, and Machine Learning); Neuromorphic Computing, and Theoretical Foundations for Cognitive Agents. I will also give several guest lectures, e.g. in Academic and Professional Skills, both in the bachelor and the master programme.

I normally have walk-in office hours every Tuesday 16.00-17.00; contact me by email if you cannot make it during these office hours.
Master thesis or Internship
Look here if you are interested in doing a BSc of MSc project supervised by me. I'm also available to co-supervise external or affiliated projects as long as my task load can accomodate it. You're welcome (preferably at the office hours) to discuss possibilities with me.
Teaching experience - Lecturing
2019-now MSc. AI Neuromorphic Computing
2016-now MSc. AI Theoretical Foundations for Cognitive Agents
2014-now BSc. AI, 2nd year AI: Principles and Techniques
2016-2019 BSc. AI, 3rd year Representation and Interaction
2010-2011 and 2018-2019 BSc. AI, 1st year Introduction to AI
2017-2018 MSc. AI Social Robotics
2014-2015 BSc. AI, 3rd year Knowledge Representation and Reasoning
2013-2015 BSc. AI, 2nd year Robotics 2
2012 BSc. CS, 1st year Algorithms (LIACS course)
2012 BSc. CS, 2nd year Complexity (LIACS course)
Guest Lectures
2018 MSc. AI Advanced Academic and Professional Skills Introduced formal and experimental algorithm analysis.
2018 BSc. AI Academic and Professional Skills Introduced research at the B(I)C group.
2017 BSc. AI Computational and Formal Modeling Discussed models for Similarity Judgement and Coherence.
2017 BSc. AI Academic and Professional Skills Introduced Search algorithms and runtime complexity.
2017 MSc. AI Trends in Artificial Intelligence Introduced Predictive Processing, some foundations and formalisation in terms of causal Bayesian networks.
2016 MSc. AI Trends in Artificial Intelligence Introduced Predictive Processing, some foundations and formalisation in terms of causal Bayesian networks.
2016 MSc. AI Cognition and Complexity Introduced randomized parameterized complexity classes and parameterized tractability results for approximate MAP in Bayesian networks.
2016 MSc. AI Cognition and Complexity Replacing teacher; taught parameterized complexity analysis, parameterized reductions, FPT and W-hierarchy.
2015 MSc. AI Human Robot Interaction Preview and teaser for the Theoretical Foundations for Cognitive Agents course.
2015 MSc. AI Cognition and Complexity Introduced randomized parameterized complexity classes and parameterized tractability results for approximate MAP in Bayesian networks.
2015 MSc. AI Artificial and Natural Music Cognition Introduction of Predictive Processing and discussion of its possible applicability in music cognition.
2014 MSc. AI Trends in AI Introduction of Predictive Processing and its formalization with Bayesian networks, research overview.
2014 MSc. AI Cognition and Complexity Introduction of Predictive Processing and its formalization with Bayesian networks, treewidth as a complexity measure, and parameterized complexity results.
2013 MSc./PhD. Cognition and Complexity Mini-course (8 hours) at the IK2013 spring school. Topics: Computational models of cognition; Marr's hierarchy of theories; why is a complexity analysis relevant. Short introduction in computational complexity theory: classes P and NP; hands-on: easy NP-hardness proofs; introduction in parameterized complexity theory and Bayesian networks, as applied to cognitive models. Case studies and discussion session.
2013 BSc. AI Robotics 2 Replacing ill teacher; taught auctions and bargaining in multi-agent systems.
2013 MSc. AI Cognition and Complexity Introduction of Predictive Coding and how one may formalize concepts from the cognitive neuroscience literature into computational models and analyse their parameterized complexity.
2011 MSc. AI Cognition and Complexity Introduced treewidth as a parameter of graph based problems, both informally using Constraint Satisfaction and with a formal definition using tree-decompositions. I discussed my Most Simple Explanations model as an application of cognitive modelling.
2010 MSc. CS Bayesian and Decision Models in AI Introduced MPE and Partial MAP, explained a NP-hardness proof, and discussed problem constraints and the application in cognitive science and philosophy.
2010 MSc. AI Cognition and Complexity Introduced Constraint Satisfaction and Bayesian Abduction as applications where treewidth plays an important role. I proved NP-hardness, introduced treewidth and let students construct a non-trivial treedecomposition of the adjacency graph of the Netherlands' provinces.
2010 MSc. Math. Complexity Theory Introduced probabilistic Turing machines, PP, BPP, the error reduction theorem and the Sipser-Lautermann theorem (including proofs), and probabilistic networks as an application.
2008 PhD level IPA fall days Introduced probabilistic Turing Machines, the class PP, oracles and the counting hierarchy, and discussed completeness proofs for Probabilistic Inference and Network Tuning.
2008 BSc. CS Algorithms Introduced complexity theory as a means to analyse algorithms, informally introduced the classes P, EXP, NP and co-NP, discussed NP-completeness and introduced a number of standard proofs for well known problems as Knapsack and Hamiltonian Circuit.
2008 MSc. CS Algorithms and Networks Introduced Turing Machines to define complexity classes, discussed topics as encoding, membership, and non-determinism, showed the equivalence between the 'certificate' and 'nondeterminism' approach of NP, sketched Cook's generic proof of NP-hardness of satisfiability and discussed proof techniques for NP-hardness.
Individual Supervision
Current PhD advisor for:
Nils Donselaar (DCC, RU)
Danaja Rutar (DCC, RU, with Sabine Hunnius)

Former PhD advisor for:
Dr Maria Otworowska (DCC, RU, with Iris van Rooij; graduated October 4th, 2018)

PhD manuscript committee / opposition member for:
Marco Benjumeda (Dpt of AI, Technical University of Madrid, supervisors Concha Bielza and Pedro Larañaga, graduated July 10th, 2019)
Dr Ridho Rahmadi (ICIS, RU, supervisors Tom Heskes and Perry Groot; graduated March 14th, 2019)

Current master students that I (co-)supervise:
Erwin de Wolff (MSc AI)
Berend Ottervanger (MSc AI)
Wieke Kanters (MSc AI)
Abdullahi Ali (MSc CNS, with Serge Thill and Marcel van Gerven)
Sophie Willemsen (MSc AI, affiliated supervisor Pieter Medendorp)
Luke Peters (MSc AI, Blizzard Entertainment internship)
Denise Klep (MSc AI, TNO internship, affiliated supervisor Niels Taatgen)
Thomas Rost (MSc AI, affiliated supervisor Maurits Kaptein)

Graduated master students I (co-)supervised:
Alessandro Ardu (MSc AI, Philips internship)
Arianne Meijer-van de Griend (MSc AI, affiliated supervisor Aleks Kissinger)
Rik van Lierop (MSc AI, Volksbank internship)
Lisa Goerke (MSc AI, affiliated supervisor Elena Machiori)
Linde Kuijpers (MSc AI, Volksbank internship, affiliated supervisor Tom Heskes)
Bellamie Persad (MSc AI, Bol.com internship, affiliated supervisor Martha Larson)
Abdullahi Ali (MSc AI)
Dennis Doerrich (MSc AI, OCADO internship in Barcelona)
Wouter van der Weel (MSc AI, ReSnap internship, affiliated supervisor Tom Heskes)
Tim Bergman (MSc AI)
Wouter Eijlander (MSc AI)
Patrick Ebel (MSc AI, affiliated supervisor Elena Machiori)
Natali Alfonso Burgos (MSc AI, affiliated supervisor Tom Heskes)
Luc Wijnen (MSc AI, affiliated supervisor Beata Grzyb)
Danny Merkx (MSc AI, affiliated supervisor Odette Scharenborg)
Tessa Beinema (MSc AI, with Louis Vuurpijl; external supervisor Reinout Versteeg)
Sarit Hashkes-Pink (MSc CNS, with Luc Selen)
Alex Bijsterveld (MSc AI, with Iris van Rooij)

Current bachelor students that I (co-)supervise:
(new cohort will start in 2019-2020 study year!)

Graduated bachelor students I (co-)supervised:
Jet van Dijk (AI, with Danaja Rutar)
Julius Mannes (AI, with Danaja Rutar)
Martijn Arnoldussen (AI, with Danaja Rutar)
Koen Naarding (AI, with Danaja Rutar)
Pepijn van Teeffelen (AI, with Danaja Rutar)
Casper van Aarle (AI, with Danaja Rutar)
Borislav Sabev (AI, with Danaja Rutar)
Bea Waelbers (AI, with Danaja Rutar)
Wout Hermens (AI)
Djamari Oetringer (AI)
Dennis Verheijden (AI)
Sjors Aalbers (AI)
Maaike ter Borg (AI, with Maria Otworowska)
Koen Dercksen (AI, affiliated supervisor Arjen de Vries)
Erwin de Wolff (AI)
Sven van Herden (AI, with Maria Otworowska)
Ward Bannink (AI, with Maria Otworowska)
Jesse Fenneman (AI, with Maria Otworowska)
Dennis Merkus (AI, with Lorijn Zaadnoordijk, Maria Otworowska, and Iris van Rooij)
Rob Klein Hofmeijer (AI, with Iris van Rooij)
Jelte Van Waterschoot (AI, with Iris van Rooij)
Jorn Bunk (AI, with Iris van Rooij and Mark Blokpoel)
Stefan Schrama (CS (LIACS), with Jetty Kleijn)

External reader for:
Pieter Wolfert (MSc AI, supervisors Pim Haselager and Mirjam de Haas)
Marjolein Troost (MSc CNS, supervisor Marcel van Gerven)
Stefano Gentili (MSc CNS, supervisors Iris van Rooij and Mark Blokpoel)
Koen Smit (BSc AI, supervisor Pim Haselager)
Jan Van Acken (MSc AI, supervisor Pim Haselager)
Anouk Maris (MSc AI, supervisors Beata Grzyb and Hagen Lehmann)
Loes Habermehl (BSc AI, supervisor Luc Selen)
Pieter Wolfert (BSc AI, supervisor Luc Selen)
Anco Peeters (MSc AI, supervisor Pim Haselager)
Thomas Planting (MSc AI, supervisor Pim Haselager)
Bas Bootsma (MSc AI, supervisor Pim Haselager)
Jasper van Dalen (BSc AI, supervisor Pim Haselager)
Arne Wijnia (MSc AI, supervisors Todd Wareham and Iris van Rooij)
Tijl Grootswagers (MSc AI, supervisors Todd Wareham and Iris van Rooij)

Capita Selecta projects:
Matthijs de Jong and Johan van den Heuvel (BSc AI): Algorithmic Information Theory
Laurens Hagendoorn (MSc AI): Tuning of NV-centre resonance
Sarit Hashkes-Pink (MSc CNS): A Predictive Processing Account of the Effects of 5-Hydroxytryptamine 2A (5-HT2A) Agonists On Perception
Erwin de Wolff (BSc AI): Neural Network Replacing Utility Functions in Q-Learning
Dennis Merkus (BSc AI): Software Engineering of a Predictive Coding Toolbox

Visiting students
Dibyanshee Mishra
Samuele Faggiano
Sebastijan Veselič

Research assistant supervision
Hugo Chateau-Laurent (DCC)
Abdullahi Ali (DCC)
Athena Iakovidi (DCC)
Joris van Vugt (DCC)
Jordi Riemens (DCC)
Marvin Uhlmann (DCC)
Didactical skills
I have acquired my Basiskwalificatie Onderwijs (University Teaching Qualification) in 2012 and Uitgebreide Kwalificatie Onderwijs (Senior University Teaching Qualification) in 2016.