I obtained my Ph.D degree in CSE Department from the Hong Kong University of Science and Technology. My Ph.D supervisor was Prof. Dit-Yan Yeung. I was a visiting scholar working with Prof. Matt Mason’s Manipulation Lab in Robotics Institute of Carnegie Mellon University. Before that, I got my Bachelor Degree of Engineering in June 2014 from the College of Computer Science and Technology of Zhejiang University. I am now a senior research engineer at Sea AI Lab working on reinforcement learning (RL) algorithms and applications. From 2019 to 2021 I worked as a senior applied resercher at Tencent on RL for game AI.
I am especially interested in applying machine learning to real-world problems.
My research interest focuses on applying computational and statistical approaches to real problems in computer vision and robotics control. Currently, I mainly work on deep learning and reinforcement learning. Especially I am interested in the perception and control of aerial robots.
- Siyi Li, Jiaji Zhou, Zhenzhong Jia, Dit-Yan Yeung, and Matthew T. Mason. Learning accurate objectness instance segmentation from photo-realistic rendering for robotic manipulation. Proceedings of the 2018 International Symposium on Experimental Robotics (ISER), Buenos Aires, Argentina, 5-8 November 2018.
- Siyi Li, Tianbo Liu, Chi Zhang, Dit-Yan Yeung, and Shaojie Shen. Learning unmanned aerial vehicle control for autonomous target following. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, 13-19 July 2018.
- Siyi Li, Dit-Yan Yeung. Visual object tracking for unmanned aerial vehicles: A benchmark and new motion models. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), pp.4140-4146, San Francisco, California, USA, 4-9 February 2017.
[Paper] [Project Page] [Data]
- Naiyan Wang, Siyi Li, Abhinav Gupta, Dit-Yan Yeung. Transferring rich feature hierarchies for robust visual tracking. CoRR abs/1501.04587 (2015)
- A survey on methods and applications of deep reinforcement learning. PhD Qualifying Exam, 2017.
- COMP2711 Discrete Mathematical Tools for Computer Science,
Spring 2015, Teaching Assistant.
- COMP1022Q Introduction to Computing with Excel VBA,
Fall 2015, Teaching Assistant.
- COMP5212 Machine Learning,
Spring 2016, Teaching Assistant.
- PC Member: IJCAI 2015, AAAI 2018
- Journal Reviewer: TNNLS, TIP