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Jingkang Wang
PhD student
Machine Learning Group
Department of Computer Science
University of Toronto
Email: wangjk (at) cs (dot) toronto (dot) edu
CV /
LinkedIn /
GitHub /
Google Scholar
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Biography
I am a first-year Ph.D. student in Machine Learning Group, CS Department, University of Toronto. My advisors are Prof. Raquel Urtasun and Prof. Richard Zemel.
I am also part of Uber ATG and Vector Institute. I received my B.S. degree from Shanghai Jiao Tong University advised by Prof. Cewu Lu.
My research interests involve Machine Learning and Computer Vision. Prior to UofT, I spent a wonderful year working with Prof. Bo Li at UIUC as a research intern and did some works on trustworthy machine learning.
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Education
University of Toronto, Canada
Ph.D. in Computer Science
Sept 2019 to Aug 2024 (Expected)
Advisors: Professors Raquel Urtasun and Richard Zemel
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Shanghai Jiao Tong University, China
B.S. in Engineering
Sept 2015 to June 2019
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Research
BabyAI++: Towards Grounded-Language Learning beyond Memorization
Tianshi Cao*, Jingkang Wang*, Annie Zhang*, Sivabalan Manivasagam*
International Conference on Learning Representations (ICLR), BeTR-RL Workshop, 2020
Towards a Unified Min-Max Framework for Adversarial Exploration and Robustness
Jingkang Wang*, Tianyun Zhang*, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad and Bo Li
arXiv preprint arXiv:1906.03563
Reinforcement Learning with Perturbed Rewards
Jingkang Wang, Yang Liu and Bo Li
AAAI Conference on Artificial Intelligence (AAAI), 2020 (Spotlight)
[paper]
[code]
On the Impact of Perceptual Compression on Deep Learning
Gerald Friedland, Ruoxi Jia, Jingkang Wang, Bo Li and Nathan Mundhenk.
International Conference on Multimedia Information Processing and Retrieval (MIPR), 2020.
Multiple Character Embeddings for Chinese Word Segmentation
Jingkang Wang*, Jianing Zhou*, Jie Zhou and Gongshen Liu
Annual Meeting of the Association for Computational Linguistics (ACL), Student Research Workshop, 2019
[paper]
[code]
LiDAR-Video Driving Dataset: Learning Driving Policies Effectively
Yiping Chen*, Jingkang Wang*, Jonathan Li, Cewu Lu, Zhipeng Luo, Han Xue and Cheng Wang
Conference on Computer Vision and Pattern Recognition (CVPR), 2018
[paper]
[code]
[dataset]
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Research Internships
Ant Financial, Alibaba Group
Research Intern
Advisor: Professor Le Song
Research Focus: Trustworthy Machine Learning
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University of Illinois at Urbana-Champaign
Research Intern at CSD* (* = remote work)
Advisor: Professor Bo Li
Research Focus: Robust Reinforcement Learning
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University of California, Berkeley
Research Intern at BAIR Lab* (* = remote work)
Advisor: Professors Bo Li and Dawn Song
Research Focus: Trustworthy Machine Learning
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Machine Vision and Intelligence Group (MVIG)
Research Assistant
Advisor: Professor Cewu Lu
Research Focus: Computer Vision; Autonomous Driving
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Honors & Awards
Level-A SJTU Outstanding Scholarships
Excellent Bachelor Thesis (Top %1) of SJTU
Outstanding Undergraduate in Shanghai
First Prize in National College Student Information Security Contest
Meritorious Winner Prize in The Mathematical Contest in Modeling (MCM)
Second Prize in The Chinese Mathematics
Competition (CMC, Shanghai)
Second Prize in National College Students
Information Security Contest
First Prize in Chinese Mathematical Olympiad (CMO, 10th in Shanxi)
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Talks & Presentations
Trust Region Policy Optimization (TRPO). CSC2621 Topics in Robotics. 2021/02. [slides]
Efficient Nonmyopic Active Search. CSC2547 Learning to Search. 2019/10. [slides]
Towards Secure and Interpretable Learning in Deep Neural Networks. Uber ATG. 2019/07. [slides]
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Updated by Feb 28th, 2020.
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