Minjune Hwang

I am a graduate student in Computer Science at Stanford University, with interests in robotics and AI. I am a graduate research assistant in the Stanford Vision Lab, working with Prof. Fei-Fei Li and Postdoc Ruohan Zhang.

Previsouly, I completed my undergraduate studies at UC Berkeley, majoring in Computer Science and Statistics. I've done research in computer vision, robotics, and optimization in the Berkeley AI Research Group, where I was advised by Prof. Alexandre Bayen and Prof. Laurent El Ghaoui. I have also worked on deep learning security research in Prof. David Wagner's group, and optimization-based computational neuroscience research in LBNL & UCSF with Dr. Roy Ben-Shalom and Prof. Kevin Bender.

Email  /  Resume  /  GitHub  /  LinkedIn  /  Google Scholar

profile photo
Research

I am interested in developing and applying machine learning algorithms into real-world problems, especially for autonomous robots and vehicles. Espeically, I'm interested in learning-based control, perception, and reinforcement learning for robotics and mobile manipulation.

BEHAVIOR-1K: A Benchmark for Embodied AI with 1,000 Everyday Activities and Realistic Simulation
Chengshu Li, et al.,
Conference on Robot Learning (CoRL), 2022 (oral)
paper / project page

Decentralized Vehicle Coordination: The Berkeley DeepDrive Drone Dataset
Fangyu Wu, Dequan Wang, Minjune Hwang, Chenhui Hao, Jiawei Lu, Jiamu Zhang, Christopher Chou, Trevor Darrell, Alexandre Bayen,
In submission to The International Journal of Robotics Research (IJRR), 2022
paper / arxiv / github

Minority Reports Defense: Defending Against Adversarial Patches
Michael McCoyd, Won Park, Steven Chen, Neil Shah, Ryan Roggenkemper, Minjune Hwang, Jason Xinyu Liu, David Wagner,
Security in Machine Learning and its Applications (SiMLA), 2020 (ACNS'20 Best Workshop Paper Award)
paper / arXiv / github

Motion Planning in Understructured Road Environments with Stacked Reservation Grids
Fangyu Wu, Dequan Wang, Minjune Hwang, Chenhui Hao, Jiawei Lu, Trevor Darrell, Alexandre Bayen,
PAL workshop @ ICRA, 2020
paper

Text Analytics for Resilience-Enabled Extreme Events Reconnaissance
Alicia Yi-Ting Tsai*, Selim Günay*, Minjune Hwang*, Chenglong Li*, Pengyuan Zhai*, Laurent El Ghaoui, Khalid M.Mosalam,
Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop, NeurIPS, 2020
paper / arXiv / project page / github
(*: equal contribution)

Building Resilience Through Structural Health Monitoring and Reconnaissance
Khalid M.Mosalam, Selim Günay, Alicia Yi-Ting Tsai, Minjune Hwang, Laurent El Ghaoui,
World Conference on Earthquake Engineering (WCEE), 2020
paper / code
Work Experience
Amazon Robotics
Applied Scientist Intern
Microsoft
Research Intern
Apple, SPG
Software Engineering Intern, Motion & Trajectory Planning
Project & Repository
ME-MAML!: Multi-Label, Expert-Aided Meta-Learning for Chest X-ray Diagnosis
Minjune Hwang*, Samar Khanna*, Tony Sun*,
Stanford University (CS330), 2021
paper / arXiv / github
(*: equal contribution)

Implementation of RL & Control Agents (DQN, LQR, etc) for OpenAI Gym

Application of Gym Agents in Traffic Environments (in progress)
CS 182 (Designing, Visualizing and Understanding DNNs), Spring 2020

CS 287 (Advanced Robotics - Optimal Control, RL, Robotics), Fall 2019
Teaching
cs188 Reader, EE 227BT (Convex Optimization), Fall 2019

STEAM Instructor, Ecole Bilingue de Berkeley (under Prof. Alexandre Bayen), Spring 2019

Lab Assitant, CS 61A (Structure and Interpretation of Computer Programs), Spring 2018

Website template from Jon Barron.