I'm a CS Ph.D. student at the University of Pennsylvania advised by Dinesh Jayaraman. I received my BS/MS in CS from the University of Southern California, where I worked with Joseph J. Lim. I also developed software for nonprofits at Code The Change, and interned at Tesla and Intel.


I develop intelligent decision-making systems, ranging from virtual agents to physical robots. I currently work in reinforcement learning and robotics.


I am looking for internships!

Publications

(The code and reviews for all of my PhD papers are readily accessible.)

Planning Goals for Exploration
Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman

International Conference on Learning Representations, 2023 (Spotlight)
CoRL22 Roboadapt Workshop, (Oral, Best Paper Award)

Keywords: Exploration, Goal-conditioned RL, World Models

Paper / Website / Talk / Code / Reviews
image for IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning
Kun Huang, Edward S. Hu, Dinesh Jayaraman

Conference on Robot Learning, 2022 (Oral, Best Paper Award)

Keywords: Interactive Perception, Task Specification, RL

Paper / Website / Code / Reviews
image for IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
Transferable Visual Control Policies Through Robot-Awareness
Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

International Conference on Learning Representations (ICLR), 2022
ICLR Generalizable Policy Learning Workshop, 2022 (Oral)

Keywords: World Models, Transfer, Manipulation

Paper / Website / Code / Reviews
image for IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
Youngwoon Lee, Edward S. Hu, Joseph J. Lim

International Conference on Robotics and Automation (ICRA), 2021

Keywords: RL, Manipulation, Benchmark

Paper / Website / Code
image for To Follow or not to Follow: Selective Imitation Learning from Observations
To Follow or not to Follow: Selective Imitation Learning from Observations
Youngwoon Lee, Edward S. Hu, Zhengyu Yang, Joseph J. Lim

Conference on Robot Learning (CoRL), 2019

Keywords: Learning from Demonstrations, Goal-conditioned RL

Paper / Website / Talk
Composing Complex Skills by Learning Transition Policies
Youngwoon Lee*, Shao-Hua Sun*, Sriram Somasundaram, Edward S. Hu, Joseph J. Lim

International Conference on Learning Representations (ICLR), 2019

Keywords: Hierarchical RL

Paper / Website / Code

peg

Implementation of Planning Exploratory Goals, an unsupervised RL agent for hard exploration tasks. ICLR 2023

● Python 37

robot_aware_control

Code for "Know Thyself: Transferable Visual Control Policies Through Robot-Awareness" (ICLR'22)

● Python 5

interactive_reward_functions

Code release for "Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning" (CoRL'22)

● Python 14

furniture

IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks (ICRA'21)

● Python 448 52

slack-gpt2

OpenAI's GPT2 integrated with slack.

● Python 40 9

optical_illusion

A simple optical illusion in python

● Python 40 1