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个人简介
Dr. Yuxuan Liang is currently an Assistant Professor at Intelligent Transportation Thrust, also affiliated with Data Science and Analytics Thrust, Hong Kong University of Science and Technology (Guangzhou). 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. He published 40+ papers in refereed journals (e.g., AI, TKDE) and conferences (such as KDD, NeurIPS, ICLR, WWW, ECCV, IJCAI, AAAI, and MM). His publications collectively gathered 2,200+ citations on Google Scholar, with h-index of 22 and i10-index of 32. 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 (or reviewer) for some prestigious conferences, including KDD, ICML, ICLR, NeurIPS, WWW, CVPR, ICCV, ECCV, IJCAI, AAAI, SIGSPATIAL, and Ubicomp.
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, 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.
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, 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.
研究兴趣
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ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)pp.1701-1705, (2024)
arxiv(2024)
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arxiv(2024)
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CoRR (2024)
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ICLR 2024 (2024)
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arxiv(2024)
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Wei Chen,Yuxuan Liang,Yuanshao Zhu, Yanchuan Chang, Kang Luo,Haomin Wen,Lei Li,Yanwei Yu,Qingsong Wen,Chao Chen,Kai Zheng,Yunjun Gao,
arxiv(2024)
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Xingchen Zou,Yibo Yan, Xixuan Hao, Yuehong Hu,Haomin Wen, Erdong Liu,Junbo Zhang,Yong Li,Tianrui Li,Yu Zheng,Yuxuan Liang
CoRR (2024)
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