About (Siru Zhong 钟嗣儒) PhD @ HKUST(GZ) · Visiting @ THU · Spatio-Temporal Intelligence
Hi there, I'm Siru Zhong, a Ph.D. Candidate at The Hong Kong University of Science and Technology, Guangzhou, advised by Prof. Yuxuan Liang and Prof. Yang Yue. I am also fortunate to receive guidance from Prof. James T. Kwok, Prof. Jeffrey Xu Yu, and Prof. Yangqiu Song. I am currently visiting Tsinghua University and the National Supercomputing Center in Shenzhen, hosted by Prof. Haohuan Fu.
My research centers on Spatio-Temporal Intelligence, with a focus on time series modeling, foundation models, AI for dynamic real-world environments. Beyond academia, I have substantial industry experience: temporal data infrastructure at Tencent, multimodal perception at XPeng Motors, foundation models at Huawei, and memory for Embodied AI at Beta Infinity.
I am honored to be a consecutive recipient of the HKUST (GZ) DSA Excellent Research Award, a Tutorial Speaker for MM4ST @ MM 2025 & ICME 2026 and MM4TS @ AAAI 2026, a Web Master for WebST 2025 & UrbComp 2025, and a reviewer/PC member for venues including NeurIPS, ICLR, KDD, ACM MM, AAAI, PAKDD, IEEE TPAMI, FARS, MILETS, IJITDM, and Neurocomputing.
Action required
Problem: The current root path of this site is "",
which does not match the baseurl ("") configured in _config.yml.
Solution: Please set the
baseurl in _config.yml to "".
Selected Publications View all
Learning to Factorize Spatio-Temporal Foundation Models
NeurIPS (Advances in Neural Information Processing Systems) 2025, Santiago, America Spotlight (688/21,575, 3.19%)
Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models
Under review.
Education
-
Hong Kong University of Science and Technology (GZ) -
Tsinghua University -
Hong Kong University of Science and Technology (GZ) -
Hefei University of Technology
Industry Experience
-
Beta Infinity -
National Supercomputing Center (SZ) -
Huawei 2012 Laboratories -
XPENG Autonomous Driving Center -
Tencent -
Tencent
Service
-
Reviewer: NeurIPS 2026; FMTS 2026 @ NeurIPS 2026; ICLR 2025, 2026, 2027; KDD 2026, 2027; AAAI 2027; ACML 2026; MM 2025; FARS (Fully Automated Research System); IEEE TPAMI; Neurocomputing; IJITDM
-
PC Member: WSDM 2027; ACM MM 2026; AAAI 2026, 2027; PAKDD 2026; MILETS 2026 @ KDD 2026
-
Tutorial Speaker: MM4ST @ MM 2025, MM4ST @ ICME 2026, MM4TS @ AAAI 2026
-
Web Master: WebST 2025, UrbComp 2025
Teaching
-
DSAA60000 Table Representation LearningSpring 2026
-
PLED5001 Communicating Research in EnglishSpring 2025
-
PDEV6800 Introduction to Teaching and Learning in Higher EducationFall 2024
Awards
-
Junior Student Track Award, DSA Excellent Research Award, HKUST(GZ)2026
-
Runner-Up Prize for DSA Excellent Research Award, HKUST(GZ)2025
-
Best Project Award (1st/15) in Data Science Computing, HKUST(GZ)2023
-
Outstanding Student (Top 10%) in Red Bird Summer Camp, HKUST(GZ)2023
-
iCode Certification of R&D Engineering Competency Evaluation, Tencent2022
-
Silver Award (2nd/12) in Code World Program, Tencent2022
-
Outstanding Student Award (8th/100) in New Employee Training, Tencent2022
-
Outstanding Graduation Thesis Award (Top 2%), HFUT2022
-
First Prize (Top 10) in CSDN Technology Blogger Competition2020
News
Talks
-
跨时空学习:多模态感知、跨域泛化与鲁棒适应 [link]中南大学计算机学院第六届青年学者论坛, 长沙2026.07
-
DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting [link]AI TIME × ICML 2026, Online2026.06
-
Multi-modal TS Analysis: Methods, Datasets, and Applications [link]AAAI 2026 Tutorial, Singapore2026.03
-
Learning across Space and Time: Multimodal Integration, Foundation Models, and Dynamic Networks清华大学深圳国际研究院, 深圳2026.03
-
Multimodal Learning for Spatio-Temporal Data Mining [link]ACM MM 2025 Tutorial, Dublin2025.12
-
NeurIPS 2025(深圳)研讨会 [link]南方科技大学统计与数据科学系, 深圳2025.11
-
Learning to Factorize Spatio-Temporal Foundation Models [link]AI TIME × ICML 2025, Online2025.11