Scholar
Siru Zhong
Google Scholar ID: 3KMb5mUAAAAJ
PhD student, Hong Kong University of Science and Technology (Guangzhou)
Spatio-Temporal Data Mining
Foundation Models
Time Series
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Citations & Impact
All-time
Citations
223
H-index
7
i10-index
5
Publications
12
Co-authors
12
list available
Contact
Email
siruzhong@outlook.com
CV
Open ↗
GitHub
Open ↗
LinkedIn
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Publications
9 items
TS-Memory: Plug-and-Play Memory for Time Series Foundation Models
2026
Cited
0
DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting
2026
Cited
0
Breaking the Regional Barrier: Inductive Semantic Topology Learning for Worldwide Air Quality Forecasting
2026
Cited
0
Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models
2026
Cited
0
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
2025
Cited
0
Vision-Enhanced Time Series Forecasting via Latent Diffusion Models
2025
Cited
0
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
2025
Cited
0
AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networks
2025
Cited
0
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Resume (English only)
Academic Achievements
Paper on Spatio-Temporal Foundation Model accepted to NeurIPS 2025 (Spotlight)
Paper on Traffic Flow Forecasting accepted to IEEE TITS 2025
Paper on Multimodal Building Electricity Loads Forecasting accepted to ACM MM 2025
Paper on Urban Heat Island Effect Forecasting accepted to KDD 2025
Paper on Multimodal Time Series Forecasting accepted to ICML 2025
Tutorial on Multimodal Learning for Spatio-Temporal Data Mining accepted to ACM MM 2025 Tutorials
Two papers on Urban Indicator Prediction and Air Quality Inference accepted to AAAI 2025
Paper on Urban Multimodal Image-Text Retrieval accepted to ACM MM 2024
Two papers on Spatio-Temporal Prediction and Neural Networks accepted to IJCAI
Runner-Up Prize, 2024 HKUST(GZ) DSA Excellent Research Award
Program Committee Member for AAAI 2026 (Special Track on AI for Social Impact and main track)
Reviewer for ICLR 2025, ICLR 2026, KDD 2026 (Datasets and Benchmarks Track), and ACM MM 2025 (Dataset Track and general reviewing)
Co-authors
12 total
Yuxuan Liang
Assistant Professor, Hong Kong University of Science and Technology (Guangzhou)
Qingsong Wen (文青松)
Head of AI @ Squirrel Ai Learning, PhD Supervisor @ University of Oxford
Roger Zimmermann
Professor of Computer Science, National University of Singapore
Huan Li
ZJU100 Young Professor
Ming Jin
Assistant Professor, School of ICT, Griffith University
Co-author 6
Yangqiu Song
HKUST
Ying ZHANG
Senior Research Fellow @ National University of Singapore
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