Alkis Gotovos

I am a postdoctoral fellow at MIT CSAIL supervised by Prof. Stefanie Jegelka. Before that, I received my PhD in the Learning & Adaptive Systems group at ETH Zurich under the supervision of Prof. Andreas Krause.

My research is focused around discrete optimization and probabilistic models for machine learning. I am interested in topics such as submodularity and its use in probabilistic modeling; sampling methods for approximate inference and scalable learning; and applications that make use of such models, for example, learning mutation interactions between cancer-related genes.