Tingwu Wang

Tingwu Wang
Research scientist at Nvidia. Email = A.replace("school", "uoft") + B;
A: wilsonwangschool; B: @ .com

CV / Resume | Semantic Scholar | Google Scholar | Github | Twitter

I am currently a research scientist in Nvidia's animation group. Previously I obtained my PhD in University of Toronto, proudly advised by Prof. Sanja Fidler and Prof. Jimmy Ba. My name is pronounced as Ting-Wu, and it means "midday" in Chinese.

I have been exploring scalable, generalized and efficient methods to learn physics-based motion skills for robotics and animation tasks. Reinforcement learning and graph neural networks have been the two most important mathematical tools for my research.
I am especially interested in character animation. I believe in the near future, characters animated by neural networks will be used in real-life applications in movies and video games.

Education

PhD in Computer Science @ University of Toronto Jan. 2018 - June. 2022
Toronto, Ontario, Canada Advisor: Prof. Sanja Fidler and Prof. Jimmy Ba

MSc in Computer Science @ University of Toronto Aug. 2016 - Jan. 2018
Toronto, Ontario, Canada, GPA: 4.0/4.0 Advisor: Prof. Sanja Fidler

BSc in Electronic Engineering @ Tsinghua University Sep. 2012 - Jun. 2016
Beijing, P. R. China Advisor: Prof. Xing Li

Visitor in Electronic Information @ Technischen Universität München Sep. 2014 - Feb. 2015
Munich, Bavaria, Germany

Publications and Patents

	Synthesizing Physical Character-Scene Interactions Mohamed Hassan, Yunrong Guo, Tingwu Wang, Michael Black, Sanja Fidler & Xue Bin Peng SIGGRAPH, 2023 Video \| Arxiv \| Project Webpage
	Learning Scalable Physics-based Motion Skills with Reinforcement Learning Tingwu Wang PhD Thesis, 2022 Project Webpage
	Physics-based Human Motion Estimation and Synthesis from Videos Kevin Xie, Tingwu Wang, Umar Iqbal, Yunrong Guo, Sanja Fidler & Florian Shkurti International Conference on Computer Vision, ICCV, 2021 Two Minute Papers \| Arxiv \| Project Webpage
	UniCon: Universal Neural Controller For Physics-based Character Motion Tingwu Wang, Yunrong Guo, Maria Shugrina & Sanja Fidler Arxiv, 2020 Project Webpage \| Arxiv \| Teaser Demo \| Video \| PDF
	Learning to Generate Diverse Dance Motions with Transformer Jiaman Li, Yihang Yin, Hang Chu, Yi Zhou, Tingwu Wang, Sanja Fidler & Hao Li Arxiv, 2020 Arxiv \| Video \| Code
	Benchmarking Model-Based Reinforcement Learning Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel & Jimmy Ba Arxiv, 2019 Code \| Project Page \| Arxiv \| PDF
	Exploring Model-based Planning with Policy Networks Tingwu Wang & Jimmy Ba 8th International Conference on Learning Representations (ICLR), 2020 Code \| Arxiv
	Neural Graph Evolution: Towards Efficient Automatic Robot Design Tingwu Wang, Henry Zhou, Sanja Fidler & Jimmy Ba 7th International Conference on Learning Representations (ICLR), 2019 Project Webpage \| Slides \| OpenReview \| Code \| Video \| Arxiv
	NerveNet: Learning Structured Policy with Graph Neural Networks Tingwu Wang, Renjie Liao, Jimmy Ba & Sanja Fidler 6th International Conference on Learning Representations (ICLR), 2018 Project Webpage \| Video \| OpenReview \| Slides
	VirtualHome: Simulating Household Activities via Programs Xavier Puig, Kevin Ra, Marko Boben, Jiaman Li, Tingwu Wang, Sanja Fidler & Antonio Torralba Conference on Computer Vision and Pattern Recognition (CVPR), 2018 (Oral) Project Webpage \| Slides \| Talk \| Arxiv \| BBC News \| MIT News
	Access Points Selection in Super WiFi Network Powered by Solar Energy Harvesting Tingwu Wang, Chunxiao Jiang & Yong Ren IEEE Wireless Communications and Networking Conference (WCNC), 2016 PDF \| IEEE Webpage
	Access Strategy in Energy Harvesting Super WiFi Network: A POMDP Method Tingwu Wang, Jian Wang, Chunxiao Jiang, Jingjing Wang & Yong Ren IEEE 83rd Vehicular Technology Conference (VTC), 2016 PDF \| Arxiv \| IEEE Webpage \| Code
	Costume Detection and Attribute Value Identification Method and System Qiu Shi, Po Man Cheng, Tingwu Wang, Yan Xia & Wei Zhang. Patent: CN105447529 A, 2016. Work done as an intern in SenseTime. Contributions used in DeepFashion.

*Two authors contribute equally.

Teaching

Teaching Assistant, CSC 420: Introduction to Image Understanding Aug. 2016 - Dec. 2016
Teaching Assistant, CSC 320: Introduction to Visual Computing Jan. 2017 - Mar. 2017
Teaching Assistant, CSC 411: Introduction to Machine Learning Aug. 2017 - Jan. 2018
Teaching Assistant, CSC 411: Machine Learning and Data Mining Jan. 2018 - Mar. 2018
Teaching Assistant, CSC 2541: Topics in Machine Learning: Deep Reinforcement Learning Aug. 2018 - Jan. 2019
Teaching Assistant, CSC 2621: Topics in Robotics: Deep Reinforcement Learning Jan. 2020 - Mar. 2020

Tutorial

Tutorial on Trust Region Policy Optimization
Tutorial on model-based RL: A Step Closer to Model Based Reinforcement Learning
Tutorial on Reinforcement Learning: Policy Gradient in CSC 411: Introduction to Machine Learning
Tutorial on Reinforcement Learning: Q-Learning in CSC 411: Introduction to Machine Learning
Tutorial on Semantic Segmentation in CSC 420: Introduction to Image Understanding
Tutorial on Recurrent Neural Network in CSC2541: Sport Analytics

About Myself (

or Ting-Wu Wang)

I was born in Changsha. I was named by my grandfather, where "Ting-wu" means "the exact midday". The name comes from the Commentary on the Water Classic written by an ancient Chinese geographer called Li Daoyuan:
"To witness the Sun and the Moon, one shall wait until the exact midday or midnight."

Last Update: July, 2023; special thanks to Mr. Zhicong Lu, Mr. Ziyu Zhang, Mr. Bin Yang, Ms. Rachel Ye,
my supervisor Prof. Sanja Fidler for their help when I first arrived in this country. Thank you Mia Ma for being by my side :)!
Your help is so important to me, and I will always be grateful ;P
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