Murtaza Dalal

Hi! I am a Robotics PhD Student in the Robotics Institute at Carnegie Mellon University. I am advised by Professor Ruslan Salakhutdinov and I also work closely with Professor Deepak Pathak. My research work is supported by the National Science Foundation Graduate Research Fellowship. During my PhD, I spent a fantastic summer at NVIDIA research, where I worked in Professor Dieter Fox's lab, advised by Ankur Handa, Ajay Mandlekar and Caelan Garrett.

Previously, I was an undergraduate student at UC Berkeley where I received my BS in Electrical Engineering and Computer Science. I was an undergraduate researcher in Berkeley Artificial Intelligence and Research, working with Professor Sergey Levine, Vitchyr Pong and Ashvin Nair on deep reinforcement learning and robotics research. I also interned at (Google) X Robotics where I worked with Daniel Kappler.

Feel free to contact me via email! You can reach me at mdalal -at- andrew dot cmu dot edu

Research

I am interested in developing intelligent, efficient, adaptable robotics systems by leveraging techniques from deep reinforcement learning, machine learning, optimization, control and computer vision.

Publication Areas:

All Hierarchical Learning Self-supervised Learning Goal-conditioned Learning Demo-accelerated Learning

(* indicate equal contribution)

	Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks Murtaza Dalal, Tarun Chiruvolu, Devendra Chaplot, Ruslan Salakhutdinov International Conference on Learning Representations (ICLR),* 2024 [paper] [site] [code]
	Imitating Task and Motion Planning with Visuomotor Transformers Murtaza Dalal, Ajay Mandlekar, Caelan Garrett, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox Conference on Robot Learning (CoRL), 2023 [arXiv] [site] [code]
	Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives Murtaza Dalal, Deepak Pathak, Ruslan Salakhutdinov Neural Information Processing Systems (NeurIPS),* 2021 [arXiv] [site] [code]
	SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency Devendra Chaplot* Murtaza Dalal, Saurabh Gupta, Jitendra Malik, Ruslan Salakhutdinov Neural Information Processing Systems (NeurIPS), 2021 [arXiv] [site] [video]
	Accelerating Online Reinforcement Learning with Offline Datasets Ashvin Nair, Abhishek Gupta, Murtaza Dalal, Sergey Levine [arXiv] [site] [code] [blog]
	Skew-Fit: State-Covering Self-Supervised Reinforcement Learning Vitchyr H. Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine International Conference on Machine Learning (ICML),* 2020 [arXiv] [site] [code]
	Scalable Multi-Task Imitation Learning with Autonomous Improvement Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn International Conference on Robotics and Automation (ICRA), 2020.* [arXiv] [site] [video]
	Visual Reinforcement Learning with Imagined Goals Ashvin Nair, Vitchyr H. Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine Advances in Neural Information Processing Systems (NeurIPS), 2018 (Spotlight Presentation) [arXiv] [site] [code] [blog]
	Composable Deep Reinforcement Learning for Robotic Manipulation Tuomas Haarnoja, Vitchyr H. Pong, Aurick Zhou, Murtaza Dalal, PieterAbbeel, Sergey Levine International Conference on Robotics and Automation (ICRA), 2018.* [arXiv] [site] [code]
	Temporal Difference Models: Model-Free Deep RL for Model-Based Control Vitchyr H. Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine International Conference on Learning Representations (ICLR), 2018. [arXiv] [code] [blog]

Teaching

CS188 - Spring 2019 (uGSI)

Credit to this great repo for providing the source code for the website!