Research interests

• Decision theory
• Reinforcement learning and Control
• Machine learning and Statistics
• Security and Privacy

Teaching

• Database design (Lille)
• Data mining (Lille)
• Web fundamentals (Lille)
• Decision making under uncertainty 
  (Chalmers, University of Tokyo)
• Algorithms, data structures and logic (Chalmers, 2014/2015 3)
• Artificial Intelligence (Chalmers, period 4, 2013/2014)
  

Upcoming events

• Special issue on Decision Making for Network Security and Privacy
• RL Competition (currently on hiatus - volunteers needed)

Recent events

• Workshop in Theory and Practice of Differential Privacy, at ICML 2016.
• At Harvard May-June 2016. 
• Swedish Research Council Grant on "Learning, Privacy and the limits of Computation"
• Chalmers ICT Areas of Advance Big Data Seed project on Automatic Experiment Design with Aikaterini Mitrokotsa and Rebecka Jornsten.
• INRIA-Lille and Univ-Lille from Oct 15 2015.
• Also visiting ETHZ periodically in 2016.
• AI-Sec 2015
• Harvard University, 14-26 September 2015.
• David Parkes (Harvard) and Christos Dimitrakakis (Chalmers), obtained a grant from the Future of Life Institute for a project on Mechanism design for AI architectures.
• Christos Dimitrakakis (Chalmers) and David Parkes (Harvard), obtained a grant for the project Market Mechanisms for Multiple Minds, covering a year-long visit of Dimitrakakis to Harvard.
• Visiting Professor, Tokyo Institute of Technology May-September 2015.
• Machine Learning School (14-16 April 2015).
• Our paper On selecting the nonce length in distance bounding protocols received the Computer Journal Wilkes Award for 2014.
• AISec 2014. [Proceedings]
• Reinforcement learning tutorial at the MPI summer school on Autonomous Learning.
• ICML 2014 Workshop on Learning, Security and Priavacy.
• AISec 2013.

Some recent papers

• On the Differential Privacy of Bayesian Inference, AAAI 2016.
• Algorithms for Differentially Private Multi-Armed Bandits, AAAI 2016.
• DIfferentially Private Multi-Agent Multi-Armed Bandits, EWRL 2015.
• Usable ABC Reinforcement Leanring. NIPS 2014, ABC in Montreal workshop.
• Generalised Entropy MDPs and Minimax Regret. NIPS 2014, From Bad Models to Good Policies Workshop.
• Expected loss bounds for authentication in constrained channels. Journal of Computer Security, 2014.
• On the Leakage of Information in Biometric Authentication, Indocrypt 2014.
• Robust and private Bayesian Inference. Algorithmic Learning Theory 2014.
• Distance bounding protocols: are you close enough? IEEE Security & Privacy Magazine.
• Cover tree Bayesian reinforcement learning. Journal of machine learning research.
• Monte-Carlo utility estimates for Bayesian reinforcement learning, IEEE CDC 2013.
  
• Personalized news recommendation with context trees, RecSys 2013.
• Probabilistic inverse reinforcement learning in unknown environments, UAI 2013.
• ABC reinforcement learning, ICML 2013.