Research Interests

My research interests are at the intersection of Artificial Intelligence and Machine Learning.

The overall theme is probabilistic reasoning and statistical inference with formal models and representation languages, especially those incorporating logic-based representations.

Within this broad area, my research covers a fairly wide spectrum ranging from philosophical and mathematical foundations, to concrete modeling frameworks, algorithms, and implementations.

Some specific topics of past, current and future interest are:

  • Foundations and principles of probabilistic reasoning and learning
  • Probabilistic logics
  • Combination of logical and relational representations with probabilistic graphical models (a.k.a. Statistical Relational Learning)
  • Learning from incomplete data
  • Latent variable models, especially for cluster analysis
  • Combining Machine Learning and formal verification techniques for system analysis