Zhiao Huang (黄志翱)
Ph.D. Student, CSE, UCSD
z2huang [at] eng (dot) ucsd (dot) edu
Structured Policy Learning
I am currently a fourth-year Ph.D. student advised by Prof. Hao Su at the Computer Science & Engineering (CSE), University of California, San Diego. My general research interests cover Computer Vision and Machine Learning.
I have got my bachelor's degree at Tsinghua University, where I worked at the Machine Intelligence Group, advised by Prof. Chongjie Zhang. I spent most of my time being an intern at Megvii Inc. (Face++). During the spring of 2017, I was a visiting student at the University of Michigan, advised by Prof. Jia Deng.
Ph.D. in Computer Science, University of California, San Diego, 2018 - present
B.E. in Computer Science, Tsinghua University, 2014 - 2018
Learning Multi-Object Dynamics with Compositional Neural Radiance Fields
Danny Driess, Zhiao Huang, Yunzhu Li, Russ Tedrake, Marc Toussaint
RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks
Haochen Shi*, Huazhe Xu*, Zhiao Huang, Yunzhu Li, Jiajun Wu
Robotics: Science and Systems (RSS), 2022.
DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools
Xingyu Lin, Zhiao Huang, Yunzhu Li, Joshua B Tenenbaum, David Held, Chuang Gan
International Conference on Learning Representations (ICLR), 2022.
Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics
Sizhe Li*, Zhiao Huang*, Tao Du, Hao Su, Joshua B Tenenbaum, Chuang Gan
International Conference on Learning Representations (ICLR), 2022 (Spotlight).
Efficient Hierarchical Navigation and Manipulation by Constraint-induced Option-Reward Design
Zhiao Huang, Xiaochen Li and Hao Su
RSS 2021 Workshop on Declarative and Neurosymbolic Representations in Robot Learning and Control
ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
Tongzhou Mu, Zhan Ling, Fanbo Xiang, Derek Yang, Xuanlin Li, Stone Tao, Zhiao Huang, Zhiwei Jia, Hao Su
PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B. Tenenbaum, Chuang Gan
International Conference on Learning Representations (ICLR), 2021 (Spotlight) .
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks
Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu, Hao Su
Neural Information Processing Systems (NeurIPS), 2020.
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories
Tiange Luo, Kaichun Mo, Zhiao Huang, Jiarui Xu, Siyu Hu, Liwei Wang, Hao Su
International Conference on Learning Representations (ICLR), 2020.
Mapping State Space using Landmarks for Universal Goal Reaching
Zhiao Huang*, Fangchen* Liu, Hao Su
Neural Information Processing Systems (NeurIPS), 2019.
Object-oriented dynamics predictor
Guangxiang Zhu, Zhiao Huang, Chongjie Zhang
Neural Information Processing Systems (NeurIPS), 2018.
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
Alejandro Newell, Zhiao Huang, Jia Deng
Neural Information Processing Systems (NIPS), 2017.