👏 Welcome to CityMind, we are dedicated to shaping the future of AI/DM for Spatio-Temporal Data!
INTR & DSA Thrust, HKUST(GZ)
News
| 2024/04/17 | Our EdgeBrain (with Xinghai IoT) won the Silver Medal at International Exhibition of Inventions Geneva! |
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| 2024/04/17 | Our paper on causal learning for trajectories was accepted by IJCAI. Congrats to Kang! |
| 2024/04/07 | Our survey on SSL for time series was accepted by TPAMI. Congrats to all collaborators! |
| 2024/03/29 | Our paper on cross-city traffic prediction was accepted by TR Part C. Congrats to Kehua! |
| 2024/03/10 | Our paper on anomaly detection was accepted by ICDE. Congrats to Feiyi! |
| 2024/01/24 | Congratulations to Xingchen for achieving the 1st Runner-Up position in the thesis writing competition in HKUST(GZ)! |
| 2024/01/23 | One paper on modeling ST dynamic system was accepted by TKDE-24. Congrats to Kun and Hao! |
| 2024/01/23 | Three papers on Time Series LLM, Urban LLM, and trajectory learning were accepted by WWW-24. Congrats to all! |
| 2024/01/16 | Three papers on Time Series LLM, ST causal inference, and GLT were accepted by ICLR-24. Congrats to all collaborators! |
| 2023/12/14 | One paper on spatio-temporal causal inference was accepted by ICASSP-24. Congrats to Guorui and Prof. Liu! |
| 2023/12/09 | Three papers on spatio-temporal data and causal inference were accepted by AAAI-24. Congrats to all collaborators! |
| 2023/12/08 | Our paper on graph lottery tickets was accepted by TPAMI. Congrats to Kun! |
| 2023/12/07 | Our paper on DRL for urban sensing was accepted by ICDE. Congrats to Sijie! |
| 2023/11/01 | Our survey on spatio-temporal neural networks for urban computing was accepted by TKDE. |
| 2023/10/21 | Our paper about spatio-temporal causal inference was accepted by WSDM-24. Congrats to Chengxin! |
| 2023/10/16 | We completed the first survey on large models for time series and spatio-temporal data! [link] |
| 2023/09/23 | LargeST, a large-scale traffic benchmark, was accepted by NeurIPS-23 DB Track. Congrats to xu! |
| 2023/09/23 | Our paper about spatio-temporal causal inference was accepted by NeurIPS-23. Congrats to Yutong! |
| 2023/09/09 | Our paper about spatio-temporal diffusion model was accepted by SIGSPATIAL-23. Congrats to Haomin! |
| 2023/07/26 | One paper about geospatial cross-view matching was accepted by ACM MM-23. Congrats to Wenmiao! |
| 2023/07/15 | One paper about addressing spatio-temporal heterogeneity was accepted by TMC. Congrats to Zhengyang! |
| 2023/06/30 | One paper about spatio-temporal extrapolation was accepted by TNNLS. Congrats to Junfeng! |
| 2023/05/17 | Two papers about learning ST graphs were accepted by KDD-23. Congrats to Junfeng and Zhengyang! |
| 2023/02/28 | An extension of AutoSTG was accepted by Artificial Intelligence (AI). Congrats to Songyu! |
| 2023/02/08 | One paper about contrastive learning on trajectories was accepted by ICDE-23. Congrats to Yanchuan! |
| 2023/01/21 | One paper about GNN pruning was accepted as poster by ICLR-23. Congrats to Kun! |
| 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. |
| 2022/07/04 | 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. |
| 2022/03/01 | 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. |
Highlights
the first comprehensive last-mile
delivery dataset from industry!
a benchmark dataset for
large-scale traffic forecasting!
including PhD, Mphil, PostDoc,
and Intern!
Spatio-Temporal Graph Neural Networks for Urban Computing
Self-Supervised Learning for
Time Series Analysis