I am teaching courses and conducting research studies under the supervision of Professor Alex Bayen. We designed a new course entitled "Deep Multi-Agent Reinforcement Learning with Applications to Autonomous Traffic." In this class, students learn the fundamental techniques of machine learning (ML) / reinforcement learning (RL) required to train multi-agent systems to accomplish autonomous tasks in complex environments. Foundations include reinforcement learning, dynamical systems, control, neural networks, state estimation, and partially observed Markov decision processes (POMDPs). My research is focused on modeling and simulating traffic as well as applying artificial intelligence techniques to relieve traffic congestion. I am also working on developing an interface between Aimsun microsimulation software and Flow (a deep reinforcement learning framework for mixed autonomy traffic).