Siddarth Venkatraman

I am a PhD student at Mila, Quebec AI Institute affiliated with Université de Montréal. I have the pleasure of being advised by Dr. Glen Berseth and part of the Robotics and Embodied AI Lab (REAL).

I obtained my Masters in Robotics from Carnegie Mellon University where I was a part of the Auton Lab and the Argo AI Center for Autonomous Vehicles Research advised by Dr. Jeff Schneider. Before this I obtained by bachelors in Computer Science at Manipal Institute of Technology. I worked as an ML research intern at NASA Jet Propulsion Laboratory (JPL) where I worked on learning heuristics for more efficient Mars Rover motion planning. I recently interned at Lawrence Livermore National Laboratory (LLNL) where I worked on scaling GFlowNets for scientific applications.

I am generally interested in topics related to probabilistic inference, generative models and reinforcement learning. I am looking for collaborators on research projects related to these topics. If you are interested in working together, please reach out by email!

Email / CV / Google Scholar / Github / LinkedIn

Research

Here is a collection of my previous research work.

	Amortizing intractable inference in diffusion models for vision, language and control Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin NeurIPS 2024*
	Reasoning with Latent Diffusion in Offline Reinforcement Learning Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John Dolan, Jeff Schneider, Glen Berseth International Conference on Learning Representations (ICLR 2024)*
	Learning Temporally Abstract World Models without Online Experimentation Benjamin Freed, Siddarth Venkatraman, Guillaume Adrien Sartoretti, Jeff Schneider, Howie Choset Proceedings of the 40th International Conference on Machine Learning, PMLR 202:10338-10356, 2023. (ICML 2023)
	Multi-Alpha Soft Actor-Critic: Overcoming Stochastic Biases in Maximum Entropy Reinforcement Learning Conor Igoe, Swapnil Pande, Siddarth Venkatraman, Jeff Schneider 2023 IEEE International Conference on Robotics and Automation (ICRA 2023)
	MLNav: Learning to Safely Navigate on Martian Terrains Shreyansh Daftry , Neil Abcouwer, Tyler Del Sesto, Siddarth Venkatraman, Jialin Song, Lucas Igel, Amos Byon, Ugo Rosolia, Yisong Yue, Masahiro Ono IEEE Robotics and Automation Letters ( Volume: 7, Issue: 2, April 2022) (RAL+ICRA 2022)
	Machine Learning Based Path Planning for Improved Rover Navigation Neil Abcouwer, Shreyansh Daftry, Tyler Del Sesto, Olivier Toupet, Masahiro Ono, Siddarth Venkatraman, Ravi Lanka, Jialin Song, Yisong Yue 2021 IEEE Aerospace Conference (50100)
	Deep Residual Neural Networks for Image in Audio Steganography (Workshop Paper) Shivam Agarwal, Siddarth Venkatraman 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM)