- Adaptive Control
- Bandits and adaptive experiment design
- Bayesian analysis and approximate Bayesian computation
- Decision theory
- Differential Privacy
- Distributed problems
- Game theory
- Recommendation systems
- Reinforcement learning
- Aristide C. Y. Tossou, Secure and private learning and decision making.
- Elena Pangin, Authentication protocols. (With Aikaterini Mitrokotsa).
- Jarboui Firas, Multi-agent learning
- Nikolaos Tziortziotis, Bayesian reinforcement learning (with Kostantinos Blekas), University of Ioannina.
- Christian Savu-Krohn (with Peter Auer), University of Leoben.
Image categorisation through Boosting using cost-minimising strategies for data labelling
- Florent Garcin (with Boi Faltings), EPFL.
Aggregating information from the crowd: ratings, recommendations and predictions
- Brammert Ottens (with Boi Faltings), EPFL.
Coordination and Sampling in Distributed Constraint Optimization
- Wen Xu, approximate hierarchical reinforcement learning.
- Michel Edkranz, The statistics of exploit publication and deployment.
- Hannes Eriksson, Adaptive experiment design.
- Fredrik Ek and Robert Stigsson, Recommendation system evaluation.
- Asbjorn Hagalin Petursson and Runar Kristinsson, Identity Bridging.
- Joacim Westelius, Optimisation of Wi-Fi Services
- Peng-Kun Liu, Planning with biased evaluations
- Mattias Warnquist, Making recommendations using contextual bandits.
- Emmanouil Androulakis, Chalmers Decision Making Under Uncertainty: A robust optimization
- Daniel Langiklde, Chalmers Large-scale content extraction from heterogeneous sources
- John Karlsson, Chalmers Learning to Play Games from Multiple Imperfect Teachers
- Samy Bengio, Google
- Boi Faltings, EPFL
- Devdatt Dubhashi, Chalmers
- Benjamin Rubinstein, Melbourne
- Michail Lagoudakis, TU Crete
- Aikaterini Mitrokotsa, Chalmers
- Blaine Nelson, Google
- Ronald Ortner, Leoben
- David Parkes, Harvard