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👏 Welcome to CityMind, we are dedicated to shaping the future of AI/DM for Spatio-Temporal Data!



2024/04/17Our EdgeBrain (with Xinghai IoT) won the Silver Medal at International Exhibition of Inventions Geneva!
2024/04/17Our paper on causal learning for trajectories was accepted by IJCAI. Congrats to Kang!
2024/04/07Our survey on SSL for time series was accepted by TPAMI. Congrats to all collaborators!
2024/03/29Our paper on cross-city traffic prediction was accepted by TR Part C. Congrats to Kehua!
2024/03/10Our paper on anomaly detection was accepted by ICDE. Congrats to Feiyi!
2024/01/24Congratulations to Xingchen for achieving the 1st Runner-Up position in the thesis writing competition in HKUST(GZ)!
2024/01/23One paper on modeling ST dynamic system was accepted by TKDE-24. Congrats to Kun and Hao!
2024/01/23Three papers on Time Series LLM, Urban LLM, and trajectory learning were accepted by WWW-24. Congrats to all!
2024/01/16Three papers on Time Series LLM, ST causal inference, and GLT were accepted by ICLR-24. Congrats to all collaborators!
2023/12/14One paper on spatio-temporal causal inference was accepted by ICASSP-24. Congrats to Guorui and Prof. Liu!
2023/12/09Three papers on spatio-temporal data and causal inference were accepted by AAAI-24. Congrats to all collaborators!
2023/12/08Our paper on graph lottery tickets was accepted by TPAMI. Congrats to Kun!
2023/12/07Our paper on DRL for urban sensing was accepted by ICDE. Congrats to Sijie!
2023/11/01Our survey on spatio-temporal neural networks for urban computing was accepted by TKDE.
2023/10/21Our paper about spatio-temporal causal inference was accepted by WSDM-24. Congrats to Chengxin!
2023/10/16We completed the first survey on large models for time series and spatio-temporal data! [link]
2023/09/23LargeST, a large-scale traffic benchmark, was accepted by NeurIPS-23 DB Track. Congrats to xu!
2023/09/23Our paper about spatio-temporal causal inference was accepted by NeurIPS-23. Congrats to Yutong!
2023/09/09Our paper about spatio-temporal diffusion model was accepted by SIGSPATIAL-23. Congrats to Haomin!
2023/07/26One paper about geospatial cross-view matching was accepted by ACM MM-23. Congrats to Wenmiao!
2023/07/15One paper about addressing spatio-temporal heterogeneity was accepted by TMC. Congrats to Zhengyang!
2023/06/30One paper about spatio-temporal extrapolation was accepted by TNNLS. Congrats to Junfeng!
2023/05/17Two papers about learning ST graphs were accepted by KDD-23. Congrats to Junfeng and Zhengyang!
2023/02/28An extension of AutoSTG was accepted by Artificial Intelligence (AI). Congrats to Songyu!
2023/02/08One paper about contrastive learning on trajectories was accepted by ICDE-23. Congrats to Yanchuan!
2023/01/21One paper about GNN pruning was accepted as poster by ICLR-23. Congrats to Kun!
2022/11/20One paper about large-scale air quality prediction via Transformer was accepted as oral presentation by AAAI-23.
2022/11/03One paper about learning mixed-order relationships in ST graphs was accepted by TKDE.
2022/08/23Two paper about periodic/contrastive learning for ST data were accepted as oral papers by SIGSPATIAL-22.
2022/08/03One paper entitled Efficient Trajectory Classification using Transformer was accepted by CIKM-22.
2022/07/04One paper about efficient video transformer was accepted by ECCV-22.
2022/07/01One paper about geo-orientation was accepted by ACM MM-22.
2022/05/20One paper about sequential recommendation was accepted by KDD-22.
2022/03/01Three papers were accepted by NAACL-22, IEEE Access and IJCNN-22.
2022/02/24ST-MetaNet was selected as Most Influential KDD Papers.
2022/02/24Two spatio-temporal AI papers (GeoMAN and stMTMVL) were selected as Most Influential IJCAI Papers.


We have released LaDe
the first comprehensive last-mile
delivery dataset from industry!
We have released LargeST
a benchmark dataset for
large-scale traffic forecasting!
We have multiple openings
including PhD, Mphil, PostDoc,
and Intern!
Rencent Survey
Spatio-Temporal Graph Neural Networks for Urban Computing
Rencent Survey
Self-Supervised Learning for
Time Series Analysis