Kanaad Parvate

About Me

Hiya! I'm Kanaad. I'm an engineer at Waymo on the Behavior Prediction team. I completed my undergrad and master’s at the University of California, Berkeley studying Electrical Engineering and Computer Science.

Previously, I interned at Tesla Autopilot, where I worked on data driven prediction models and at Lyft Level 5, where I developed novel LiDAR clustering techniques.

At Berkeley, I was advised by Prof. Alex Bayen investigating the applications of reinforcement learning to teams of autonomous vehicles, working on Flow. In May 2018, I was awarded the Arthur M. Hopkin Award.

I’m passionate about all sorts of transportation: planes, trains, buses, cars, bicycles, scooters, skateboards (you name it!). I spend my free time swimming, cycling, drinking coffee, and watching the NBA or college football.

Go bears! 🐻

Publications

• Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RL
  E. Vinitsky, N. Lichtle, K. Parvate, A. Bayen. arXiv preprint arXiv:2011.00120 (2020).

• Robust Reinforcement Learning using Adversarial Populations
  E. Vinitsky, Y. Du, K. Parvate, K. Jang, P. Abbeel, A. Bayen. arXiv preprint arXiv:2008.01825 (2020).

• Lagrangian Control through Deep-RL: Applications to Bottleneck Decongestion
  E. Vinitsky, K. Parvate, A. Kreidieh, C. Wu, Z. Hu, A. Bayen. IEEE Intelligent Transportation Systems Conference (ITSC), 2018. [Videos]

• Flow: Deep Reinforcement for Control in SUMO
  N. Kheterpal, K. Parvate, C. Wu, A. Kreidieh, E. Vinitsky, A. Bayen. SUMO User Conference. 2018.

• Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control
  C. Wu, A. Kreidieh, K. Parvate, E. Vinitsky, A. Bayen. IEEE Transactions on Robotics (T-RO). In review, 2017. [arXiv] [Videos] [github]

• Framework for Control and Deep Reinforcement Learning in Traffic
  C. Wu, K. Parvate, N. Kheterpal, L. Dickstein, A. Mehta, E. Vinitsky, A. Bayen. IEEE Intelligent Transportation Systems Conference (ITSC), 2017.