- Decision theory
- Reinforcement learning and Control
- Machine learning and Statistics
- Security and Privacy
New positions will open in 2016.
Contact me for possible collaborations or projects.
- 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.
- 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.