Scholar
Ruihan Zhao
Google Scholar ID: dxco-1UAAAAJ
PhD Student, ECE, UT Austin
Citations & Impact
Citations
959
H-index
9
i10-index
9
Publications
17
Co-authors
10
list available
Publications
Resume (English only)
Academic Achievements
- Paper 'Human-Agent Coordination in Games under Incomplete Information via Multi-Step Intent' accepted to AAMAS 2025; 'Accelerating Visual Sparse-Reward Learning with Latent Nearest-Demonstration-Guided Exploration (LaNE)' accepted to CoRL 2024; Published multiple papers on topics such as robotics, reinforcement learning, and medical image segmentation in top conferences like NeurIPS and ICLR.
Research Experience
- Research Assistant at UT Austin since Aug 2021, advisors: Prof. Ufuk Topcu and Prof. Sandeep Chinchali; Deep Reinforcement Learning Intern at Intel Labs from May 2021 to Aug 2021, advisor: Dr. Mariano Phielipp; Research Assistant at Berkeley AI Research (BAIR) from Jan 2019 to May 2021, advisor: Prof. Pieter Abbeel; Research Assistant at Undergraduate Research Apprentice Program from Aug 2018 to Dec 2018, advisor: Prof. Gerald Friedland.
Education
- Ph.D. in ECE at University of Texas at Austin since Aug 2021, advised by Prof. Ufuk Topcu and Prof. Sandeep Chinchali; M.S. in Computer Science and B.A. in Computer Science & Applied Mathematics at UC Berkeley from Aug 2016 to May 2021, advised by Prof. Pieter Abbeel.
Background
- Research interests include robotics, deep reinforcement learning, and computer vision. Aiming to develop efficient representation learning methods to enable robots to better understand and plan in unstructured household environments.
Miscellany
- Other projects include 'Learning Meshes for In-gripper Objects', a final project for CS294-173: Learning 3D Vision, in collaboration with Angjoo Kanazawa.
