Zhenggang Tang

Ph.D. Student

Department of Computer Science

University of Illinois Urbana Champaign

Office: CSL 130, 1308 W Main St, Urbana, IL 61801, United States

Email: zt15 [at] illinois [dot] edu

Who am I?

Hi there! I am Zhenggang Tang (唐正纲 in Chinese), a third-year Ph.D. candidate in the Department of Computer Science at University of Illinois Urbana-Champaign (UIUC), advised by Prof. Alexander Schwing. Prior to that, I get my Bachelor of Science degree in computer science at Peking University with a Summa Cum Laude. In my high school years, I learned informatics and got a silver award in the National Olympiad of Informatics (NOI 2016).

My current research interest focus on topics in 3D vision, from obj/scene reconstruction to transformation and editing, Previously I also had some research on reinforcement learning(RL) and multi-agent(MA) system. I have conducted or am conducting research in the following fields: 1) NeRF transformation given single RGBD view. 2). RGB-only SDF reconstruction for robotics manipulator control 3) MARL applications on finance and 4) epidemic simulation and 5) reward randomization for RL exploration.

You can check my CV, Google Scholar, Github and Linkedin here.

Publications and Preprints.

Zhenggang Tang, Zhongzheng Ren, Xiaoming Zhao, Bowen Wen, Jonathan Tremblay, Stan Birchfield, Alexander Schwing, “NeRFDeformer: NeRF Transformation from a Single View via 3D Scene Flows”, CVPR 2024.

Yuchen Fang*, Zhenggang Tang*, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu, "”Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance”, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023. (*contribute equally).

Zhenggang Tang, Balakumar Sundaralingam, Jonathan Tremblay, Bowen Wen, Ye Yuan, Stephen Tyree, Charles Loop, Alexander Schwing, Stan Birchfield. “RGB-Only Reconstruction of Tabletop Scenes for Collision-Free Manipulator Control”, Arxiv 2210.11668, IEEE International Conference on Robotics and Automation (ICRA), 2023.

Zhenggang Tang*, Chao Yu*, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Shaolei Du, Yu Wang, Yi Wu, “Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization”, International Conference on Learning Representations (ICLR), 2021 (*contribute equally)

Zhenggang Tang*, Kai Yan*, Liting Sun, Wei Zhan, Changliu Liu. A Microscopic Pandemic Simulator for Pandemic Prediction Using Scalable Million-Agent Reinforcement Learning., Arxiv 2108.06589. (*contribute equally)