Philippe Hansen-Estruch

I am currently a first-year PhD student in Electrical and Computer Enginering (ECE) at the University of Texas, Austin, advised by Prof. Amy Zhang and Prof. Sriram Vishwanath.

I received my Bachelor's degree in Electrical Engineering and Computer Science (EECS) with highest honors from the University of California, Berkeley, in 2022, and my Master's degree, also from Berkeley, in 2023. During my time at Berkeley, I was a student researcher at the Robotic AI & Learning Lab (RAIL), where I was advised by Prof. Sergey Levine.

Email / CV / Google Scholar / Github

Research

My research interests lie in the fields of generative modeling, representation learning, and learning based control. Lately, I am passionate about diffusion models and large langauge models.

	BridgeData V2: A Dataset for Robot Learning at Scale Homer Walke, Kevin Black, Abraham Lee, Moo Jin Kim, Max Du, Chongyi Zheng, Tony Zhao, Philippe Hansen-Estruch, Quan Vuong, Andre He, Vivek Myers, Kuan Fang, Chelsea Finn, Sergey Levine, Conference on Robot Learning (CORL), 2023
	Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine, Conference on Robot Learning (CORL), 2023
	IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine arxiv, 2023
	Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine International Conference on Machine Learning (ICML), 2022