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 second-year Ph.D. student 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 is neural fields and their applications, 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 fast adaptation. 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, 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, submitted to IEEE International Conference on Robotics and Automation (ICRA), 2023.

Zhenggang Tang*, Yuchen Fang*, Kan Ren, Weiqing Liu, Jiang Bian, Zongqing Lu, Weinan Zhang, Yong Yu, Tie-yan Liu, “Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance”, submitted to IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. (*contribute equally).

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”, accepted in 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)

Working Experiences

NVIDIA mentored by Dr. Stan Birchfield from May. 2022 to Sept. 2022.

Microsoft Research Asia mentored by Dr. Kan Ren and Dr. Weiqing Liu from Dec. 2020 to May. 2021, and was awarded Stars of Tomorrow.

Institute for Interdisciplinary Information Sciences, Tsinghua University mentored by Prof. Yi Wu from Nov. 2019 to May. 2020.

Random photos of travel

Mt. Rainier, WA
Michigan Upper Peninsula, MI
Olympic National Park, WA