The Machine Intelligence Lab (MIL) focuses on theory and practice of novel machine learning technologies that are applicable to a broad range of domains. In particular, we investigate biologically-inspired deep machine learning architectures that are combined with reinforcement learning algorithms to yield high-performance decision making systems.

Our studies emphasize qualitative and quantitative evaluation of system performance, robustness and scalability. To achieve the latter, we introduce hybrid hardware/software designs that are realizable using customized massively-parallel computation platforms.