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KAIXIN WANG
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Email: kaixin96.wang@gmail.com
Homepage: https://kaixin96.github.io
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Education
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National University of Singapore
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Singapore
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Ph.D. in Data Science
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Aug 2018 - Aug 2022
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Advisors: Jiashi Feng, Bryan Hooi, Xinchao Wang
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Nanjing University
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Nanjing, China
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Bachelor in Information Management and Information System
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Sep 2014 - Jun 2018
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Research Works
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*Equal contribution
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Peer-Reviewed Conference Publications
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[9] Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments
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Kaixin Wang, Kuangqi Zhou, Bingyi Kang, Jiashi Feng, Shuicheng Yan
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in International Conference on Learning Representations (ICLR), 2023.
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[8] Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction
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Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang
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in Learning on Graphs Conference (LoG), 2022.
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[7] Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL
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Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Y. F. Tan, Zhuoran Yang, Zhaoran Wang
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in Neural Information Processing Systems (NeurIPS), 2022.
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[6] The Geometry of Robust Value Functions
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Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor
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in International Conference on Machine Learning (ICML), 2022.
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[5] Understanding and Resolving Performance Degradation in Graph Convolutional Networks
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Kuangqi Zhou*, Yanfei Dong*, Kaixin Wang, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng
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in Conference on Information and Knowledge Management (CIKM), 2021. (oral)
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[4] Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
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Kaixin Wang*, Kuangqi Zhou*, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng
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in International Conference on Machine Learning (ICML), 2021.
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[3] Improving Generalization in Reinforcement Learning with Mixture Regularization
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Kaixin Wang, Bingyi Kang, Jie Shao, Jiashi Feng
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in Neural Information Processing Systems (NeurIPS), 2020.
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[2] Neural Epitome Search for Architecture-Agnostic Network Compression
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Daquan Zhou, Xiaojie Jin, Qibin Hou, Kaixin Wang, Jianchao Yang, Jiashi Feng
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in International Conference on Learning Representations (ICLR), 2020.
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[1] PANet: Few-shot Image Semantic Segmentation with Prototype Alignment
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Kaixin Wang, Jun Hao Liew, Yingtian Zou, Daquan Zhou, Jiashi Feng
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in International Conference on Computer Vision (ICCV), 2019. (oral)
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Non-archival / Workshop Papers
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[6] PPG Reloaded: An Empirical Study on What Matters in Phasic Policy Gradient
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Kaixin Wang, Daquan Zhou, Jiashi Feng, Shie Mannor
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Technical report, 2023.
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[5] Reachability-Aware Laplacian Representation in Reinforcement Learning
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Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang
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Technical report, 2022.
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[4] Q-Learning for L_p Robust Markov Decision Processes
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Navdeep Kumar, Kaixin Wang, Kfir Levy, Shie Mannor
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in The European Workshop on Reinforcement Learning (EWRL), 2022.
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[3] Efficient Policy Iteration for Robust Markov Decision Processes via Regularization
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Navdeep Kumar, Kfir Levy, Kaixin Wang, Shie Mannor
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Technical report, 2022.
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[2] Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction
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Kuangqi Zhou, Kaixin Wang, Jiashi Feng, Jian Tang, Tingyang Xu, Xinchao Wang
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Technical report, 2022.
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[1] Policy Gradient for Reinforcement Learning with General Utilities
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Navdeep Kumar, Kaixin Wang, Kfir Levy, Shie Mannor
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in The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2022.
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Academic Experience
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Technion - Israel Institute of Technology
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Haifa, Israel
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Postdoctoral Fellow (Supervisor: Prof. Shie Mannor)
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Aug 2022 - present
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Technion - Israel Institute of Technology
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Haifa, Israel
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Visiting PhD Student (Supervisor: Prof. Shie Mannor)
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Sep 2021 - Feb 2022
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University of Western Australia
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Perth, Australia
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Research Intern (Supervisor: Prof. Mark Reynolds)
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Jul 2017 - Aug 2017
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Zhejiang University
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Hangzhou, China
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Exchange Student
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Mar 2017 - Jun 2017
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Working Experience
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Intelligent Creation Research, TikTok
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Singapore
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Intern, mentored by Jiashi Feng
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Apr 2022 - July 2022
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Sea AI Lab
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Singapore
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Intern, mentored by Bingyi Kang
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Mar 2021 - Jun 2021
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ByteDance AI Lab
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Singapore
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Intern, mentored by Jie Shao
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Apr 2020 - Feb 2021
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Horizon Robotics
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Nanjing, China
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Intern, mentored by Guixing Chen
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Nov 2017 - Mar 2018
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Awards & Scholarships
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PREMIA Best Student Paper, Silver Award
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2021
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NUS NGS Scholarship
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2018 - 2022
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Services
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Conference Reviewer
- AAAI: 2023
- ICML: 2021 (top 10%), 2022, 2023
- ICLR: 2022, 2023
- NeurIPS: 2021
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Journal Reviewer
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- IEEE Transactions on Multimedia
- IEEE Transactions on Image Processing
- Machine Vision and Applications
- Transactions on Machine Learning Research
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Volunteer
- ICML: 2020, 2021
- NeurIPS: 2020
- ICLR: 2020, 2021
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Teaching
- NUS EE5934/6934: Deep Learning - Teaching Assistant
- NUS IDS PhD-Teach-PhD workshop 2019 - Instructor
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