Yuxuan Liang

Research Fellow @ National Univerisity of Singapore

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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 1,800+ citations, with h-index of 20 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, geo-localization.

News

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 by ICLR’23.
2023/01/13 I will attend AAAI’23 at Washington DC in person. Hope to meet you at the conference!
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.
2022/10/15 I will attend CIKM’22, ECCV’22 and SIGSPATIAL’22 in person. Hope to meet you at the conferences!
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
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.

  1. ICLR’23
    [New] Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
    Kun Wang, Yuxuan Liang*, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, and Yang Wang*
    In The International Conference on Learning Representations, 2023
  2. AAAI’23
    [New] AirFormer: Predicting Nationwide Air Quality in China with Transformers
    Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, and Roger Zimmermann
    In Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
  3. SIGSPATIAL’22
    When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?
    Xu Liu+, Yuxuan Liang+, Chao Huang, Yu Zheng, Bryan Hooi, and Roger Zimmermann
    In Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022
  4. WWW’21
    Fine-grained Urban Flow Prediction
    Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David Rosenblum, and Roger Zimmermann
    In Proceedings of the Web Conference, 2021
  5. KDD’19
    Urbanfm: Inferring Fine-Grained Urban Flows
    Yuxuan Liang+, Kun Ouyang+, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S Rosenblum, and Yu Zheng
    In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019
  6. IJCAI’18
    GeoMAN: Multi-Level Attention Networks for Geo-sensory Time Series Prediction.
    Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, and Yu Zheng
    In International Joint Conference on Artificial Intelligence, 2018
  7. KDD’19
    Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning
    Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, and Junbo Zhang
    In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019
  8. IJCAI’16
    Urban Water Quality Prediction based on Multi-Task Multi-View Learning
    Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, and David S Rosenblum
    In Proceedings of the 25th international joint conference on artificial intelligence, 2016
  9. NeurIPS’20
    Digraph Inception Convolutional Networks
    Zekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David Rosenblum, and Andrew Lim
    Advances in neural information processing systems 2020

Services

Conference program commitee member & Reviewer

  • KDD’23, ICML’23, ICLR’23, CVPR’23, WWW’23, IJCAI’23, AAAI’23, ICASSP’23

  • KDD’22, NeurIPS’22, ICML’22, ICLR’22, ECCV’22, IJCAI’22, AAAI’22, SDM’22

  • KDD’21, NeurIPS’21, ICML’21, ICLR’21, AAAI’21

  • NeurIPS’20, AAAI’20, ECML-PKDD’20, SPATIALDI’20

Journal reviewer:

  • Data mining: TKDE, TMC, IMWUT, TIST

  • Artificial intelligence: TNNLS, TASLP, Neurocomputing, TMLR

  • Interdiscipline: T-ITS, Transportation Research Part C, Sensor Journal

Awards

  • Dean's Graduate Award, NUS, 2022.

  • The 23rd China Patent Excellence Award, 2022.

  • SDSC Dissertation Research Fellowship, 2020 (1 out of 10 most innovative and impactful PhD students focusing on Data Science in Singapore by the Singapore Data Science Consortium.)

  • Outstanding Winners of The Interdisciplinary Contest in Modeling, 2015

  • CCF(China Computer Federation) Elite Collegiate Award

  • The star of graduates in Xidian University (10 out of 4917)

  • ACM/ICPC Shaanxi province silver medal

  • Research Scholarship at NUS: 2019-2023

  • National Scholarship (four times): 2015, 2016, 2017 and 2018

  • National Scholarship for Encouragement: 2014

  • Attending DiDi Elite Forum 2021

  • Conference travel grants for SIGSPATIAL'22, CIKM'22, AAAI'20, KDD'19, SIGSPATIAL'17