I am a PhD student at UT Austin, advised by Prof. Ufuk Topcu and Prof. Sandeep Chinchali.
Prior to joining UT, I earned my Master’s degree in Computer Science at UC Berkeley, advised by Prof. Pieter Abbeel; and my Bachelor’s degrees in Computer Science and Applied Mathematics.
My research interests include robotics, deep reinforcement learning, and computer vision. I aim to develop efficient representation learning methods to enable robots to better understand and plan in unstructured household environments, from high-dimensional sensor input.
Email: ruihan (dot) zhao [at] utexas (dot) edu
[GitHub][CV][LinkedIn][Google Scholar]
News
- Human-Agent Coordination in Games under Incomplete Information via Multi-Step Intent is accepted to AAMAS 2025.
- Accelerating Visual Sparse-Reward Learning with Latent Nearest-Demonstration-Guided Exploration (LaNE) is accepted to CoRL 2024.
Research
Aditya Narayanan, Pranav Kasibhatla, Minkyu Choi, Po-han Li, Ruihan Zhao, Sandeep Chinchal
PEERNet: An End-to-End Profiling Tool for Real-Time Networked Robotic Systems
Published at IROS 2024
Georgios Bakirtzis, Michail Savvas, Ruihan Zhao, Sandeep Chinchali, Ufuk Topcu
Reduce, Reuse, Recycle: Categories for Compositional Reinforcement Learning
Published at ECAI 2024
S P Sharan*, Ruihan Zhao*, Ufuk Topcu, Zhangyang Wang, Sandeep Chinchal
Plan Diffuser: Grounding LLM Planners with Diffusion Models for Robotic Manipulation
Presented at CoRL 2023 Workshop [Paper]
Po-han Li*, Sravan Kumar Ankireddy*, Ruihan Zhao, Hossein Nourkhiz Mahjoub
Task-aware Distributed Source Coding under Dynamic Bandwidth
Published at NeurIPS 2023 [Paper]
Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep Chinchali, Ufuk Topcu, Lawrence Staib, James S. Duncan
Class-Aware Adversarial Transformers for Medical Image Segmentation
Published at NeurIPS 2022 [Paper]
Kourosh Hakhamaneshi*, Ruihan Zhao*, Albert Zhan*, Pieter Abbeel, Michael Laskin
Hierarchical Few-Shot Imitation with Skill Transition Models
Published at ICLR 2022 [Project]
Albert Zhan*, Ruihan Zhao*, Lerrel Pinto, Pieter Abbeel, Michael Laskin
A Framework for Efficient Robotic Manipulation (FERM)
Published at IROS 2022 [Project]
Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin
Efficient Empowerment Estimation for Unsupervised Stabilization
Published at ICLR 2021 [Project Page] [Paper] [Code]
Ruihan Zhao, Stas Tiomkin, Pieter Abbeel
Learning Efficient Representation for Intrinsic Motivation
Presented at NeurIPS 2019 Deep RL Workshop [Paper]
Education
2021.8 – Now
University of Texas at Austin
Ph.D. in ECE
2016.8 – 2021.5
University of California, Berkeley
M.S. in Computer Science
B.A. in Computer Science & Applied Mathematics
Experience
- 2021.8 – Now, Research Assistant
Advisors: Prof. Ufuk Topcu, Prof. Sandeep Chinchali - 2021.5 – 2021.8, Deep Reinforcement Learning Intern, Intel Labs
Advisor: Dr. Mariano Phielipp - 2019.1 – 2021.5, Research Assistant, Berkeley AI Research (BAIR)
Advisor: Prof. Pieter Abbeel - 2018.8 – 2018.12, Research Assistant, Undergraduate Research Apprentice Program
Advisor: Prof. Gerald Friedland
