Gu Zhang

I am an incoming Ph.D. student in Computer Science at Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University under the supervision of Prof. Huazhe Xu.

Currently, I am an undergraduate in Artificial Intelligence Class at Shanghai Jiao Tong University (SJTU) with GPA ranking 1/88. My research interest mainly lie in robotics and machine learning, with a particular focus on robotic manipulation and multisensory learning.

During my undergraduate study, I am fortunate to be mentored by Prof. Cewu Lu and Prof. Junchi Yan. I am also a research visiting student/visitor at Massachusetts Institute of Technology and MIT-IBM Watson AI Lab under the supervision of Prof. Josh Tenenbaum and Prof. Chuang Gan.

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* indicates equal contributions.

clean-usnob Flexible Handover with Real-Time Robust Dynamic Grasp Trajectory Generation
Gu Zhang, Hao-shu Fang, Hongjie Fang and Cewu Lu
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023

In this paper, we propose an approach for effective and robust flexible handover, which enables the robot to grasp moving objects with flexible motion trajectories with a high success rate.

clean-usnob Understanding and Generalizing Contrastive Learning from the Inverse Optimal Transport Perspective
Liangliang Shi, Gu Zhang, Haoyu Zhen, and Junchi Yan
International Conference on Machine Learning (ICML), 2023

In this paper, we aim to understand CL with a collective point set matching perspective and formulate CL as a form of inverse optimal transport (IOT).

clean-usnob Relative Entropic Optimal Transport: a (Prior-aware) Matching Perspective to (Unbalanced) Classification
Liangliang Shi, Haoyu Zhen, Gu Zhang, and Junchi Yan
Conference on Neural Information Processing Systems (NeurIPS), 2023

In this paper, we propose a new variant of optimal transport, called Relative Entropic Optimal Transport (RE-OT) and verify its effectiveness for inhancing visual learning.

clean-usnob Thin-Shell Object Manipulations With Differentiable Physics Simulations
Yian Wang*, Juntian Zheng*, Zhehuan Chen, Xian Zhou, Gu Zhang, Chao Liu, and Chuang Gan
Conference on Robot Learning (CoRL), Workshop L4SR , 2023
paper coming soon

In this paper, we introduce ThinShellLab, a fully differentiable simulation platform tailored for diverse thin-shell material interactions with varying properties.

clean-usnob ArrayBot: Reinforcement Learning for Generalizable Distributed Manipulation through Touch
Zhengrong Xue*, Han Zhang*, Jingwen Chen, Zhengmao He, Yuanchen Ju, Changyi Lin, Gu Zhang, and Huazhe Xu
Arxiv, 2023
project page / paper

In this paper, we present ArrayBot, a distributed manipulation system consisting of a 16×16 array of vertically sliding pillars integrated with tactile sensors, which can simultaneously support, perceive, and manipulate the tabletop objects.

Selected Awards and Honors

  • 2023: Shanghai Scholarship (8000RMB¥)
  • 2022: National Scholarship (8000RMB¥)
  • 2022: Hanying Juhua Scholarship (15 winners, 15000RMB¥)
  • 2021: National Scholarship (8000RMB¥)
  • 2021-2022: A-level Excellent Scholarship of SJTU

Academic Performance

  • GPA: 94.47/100 (or 4.12/4.3), Rank 1/88
  • Achieved A+ in more than 30 Courses.

Design and source code from Jon Barron's website.