Patrick Hart is a research scientist at fortiss and a Ph.D. student at the Technical University of Munich and fortiss. His main research interest is how agents can learn complex behaviors in uncertain environments using reinforcement learning. He obtained his Master's degree from the Karlsruhe Institute of Technology and wrote his master thesis at the FZI Karlsruhe about search-based motion planning for autonomous vehicles in 2016. In 2017, he then joined the autonomous systems group at fortiss and began to pursue his Ph.D.. At fortiss, he gained valuable insights in the field of autonomous driving working on autonomous valet parking, on autonomous vehicles, and on simulation. He is the initiator of BARK machine learning (BARK-ML) and one of the initiators and main developers of BARK.

For more information have a look at my personal website .