Yuxuan Liang
Research Fellow @ National Univerisity of Singapore

Dr. Yuxuan Liang is a Research Fellow at School of Computing, National University of Singapore (NUS), working with Prof. Roger Zimmermann. He is working on the research, development, and innovation of spatio-temporal data mining and AI, with a broad range of applications in smart cities. Prior to that, he obtained his PhD degree in NUS. He published 40+ papers in refereed journals and conferences, such as TKDE, KDD, NeurIPS, ICLR, WWW, ECCV, IJCAI, AAAI, MM and UbiComp. According to Google Scholar, his publications collectively gathered 1,900+ citations, with h-index of 21 and i10-index of 27. Among them, three papers (GeoMAN, ST-MetaNet and STMTMVL) were selected as the most influential IJCAI/KDD papers according to PaperDigest, which indicates their significant impacts on both industry and academia. He also served as a PC member (reviewer) for some top-tier conferences, including KDD, ICML, ICLR, NeurIPS, WWW, CVPR, ECCV, IJCAI and AAAI.
He was recognized as 1 out of 10 most innovative and impactful PhD students focusing on Data Science in Singapore by Singapore Data Science Consortium (SDSC) in 2020. His research interests mainly lie in
- Spatio-temporal (ST) data mining: ST representation learning, time series forecasting, ST imputation, AI for social good (e.g., transportation, human mobility, environment, climate), physics-informed learning.
- Graph mining: learning graph representations (e.g., directed graphs, temporal graphs), GNN pruning.
- Computer vision: video understanding, image recognition, image/video super-resolution.
News
2023/02/28 | An extension of AutoSTG was accepted by the journal of Artificial Intelligence (AIJ). |
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2023/02/08 | One paper about contrastive learning on trajectories was accepted by ICDE’23. |
2023/01/25 | I successfully passed my PhD defense :-) Thanks Roger and David for their continuous support at NUS! |
2023/01/21 | One paper about GNN pruning was accepted as poster by ICLR’23. |
2022/11/20 | One paper about large-scale air quality prediction via Transformer was accepted as oral presentation by AAAI’23. |
2022/11/03 | One paper about learning mixed-order relationships in ST graphs was accepted by TKDE. |
2022/08/23 | Two paper about periodic/contrastive learning for ST data were accepted as oral papers by SIGSPATIAL’22. |
2022/08/03 | One paper entitled Efficient Trajectory Classification using Transformer was accepted by CIKM’22. |
2022/07/29 | I was honored to receive the Dean’s Graduate Award from NUS. Thanks Roger for the nomination and supports! |
2022/07/04 | One paper about efficient video transformer was accepted by ECCV’22. |
2022/07/01 | One paper about geo-orientation was accepted by ACM MM’22. |
2022/05/20 | One paper about sequential recommendation was accepted by KDD’22. |
2022/04/15 | I was awarded The 23rd China Patent Excellence Award. |
2022/03/01 | Three papers were accepted by NAACL’22, IEEE Access and IJCNN’22. |
2022/02/24 | ST-MetaNet was selected as Most Influential KDD Papers. |
2022/02/24 | Two spatio-temporal AI papers (GeoMAN and stMTMVL) were selected as Most Influential IJCAI Papers. |
Working experience
2022/11 - Present | Research Fellow @ National University of Singapore, Singapore |
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2021/07 - 2021/12 | Research intern @ Sea AI Lab (SAIL), Singapore |
2018/11 - 2019/04 | Full-time research assistant @ National University of Singapore, Singapore |
2018/01 - 2018/09 | Algorithm engineer intern @ JD.COM, Beijing, China |
2017/01 - 2018/01 | Research intern @ Microsoft Research, Beijing, China |
2015/12 - 2016/09 | Research intern @ Microsoft Research, Beijing, China |
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Selected publications [See more]
* denotes corresponding author and + indicates equal contribution.
- WWW’21
- KDD’19Urbanfm: Inferring Fine-Grained Urban FlowsIn Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019
- IJCAI’18GeoMAN: Multi-Level Attention Networks for Geo-sensory Time Series Prediction.In International Joint Conference on Artificial Intelligence, 2018
- KDD’19Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta LearningIn Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019
- IJCAI’16Urban Water Quality Prediction based on Multi-Task Multi-View LearningIn Proceedings of the 25th international joint conference on artificial intelligence, 2016
- NeurIPS’20Digraph Inception Convolutional NetworksAdvances in neural information processing systems 2020
Collaborators
I was really honored to closely work with the following researchers (in alphabetical order):
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Chao Huang, Assistant Professor, University of Hong Kong
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Kun Ouyang, Algorithm Engineer, Tencent
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Sijie Ruan, Assistant Professor, Beijing Institute of Technology
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Wenmiao Hu, PhD candidate, National University of Singapore
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Yiwei Wang, Applied Scientist, Amazon
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Zekun Tong, National University of Singapore
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Zheyi Pan, Doctor Management Trainee Program, JD.COM
For the students I mentored, please click here.