About (Siru Zhong 钟嗣儒) PhD @ HKUST(GZ), Visiting @ THU & NSCS · Spatio-Temporal Intelligence · Beta Infinity · ex-Huawei / XPeng / Tencent

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 also hold visiting affiliations with Tsinghua University and the National Supercomputing Center in Shenzhen, hosted by Prof. Haohuan Fu. My research focuses on Spatial-Temporal Intelligence, Time Series, and AI4Science.

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 top venues including NeurIPS, ICLR, KDD, ACM MM, AAAI, PAKDD, IEEE TPAMI, FARS, MILETS, IJITDM, and Neurocomputing.

Beyond academia, I have sufficient industry experience. Currently, I work on Spatio-Temporal Memory in Embodied AI with Dr. Wulong Liu at Beta Infinity (2026). Previously, I worked on Spatio-Temporal Foundation Models deployed at scale at Huawei (2025), visual perception for autonomous driving at XPeng Motors (2024), and large-scale workflow data stream engineering at Tencent (2021–2023).

Education
  • Tsinghua University & National Supercomputing Center (SZ)
    Tsinghua University & National Supercomputing Center (SZ)
    Visiting PhD Student, HPGC Research Group
    Feb. 2026 - Present
  • Hong Kong University of Science and Technology (GZ)
    Hong Kong University of Science and Technology (GZ)
    PhD, Data Science and Analytics
    Feb. 2025 - Jan. 2028
  • Hong Kong University of Science and Technology (GZ)
    Hong Kong University of Science and Technology (GZ)
    MPhil, Data Science and Analytics
    Aug. 2023 - Jan. 2025
  • Hefei University of Technology
    Hefei University of Technology
    BE, School of Artificial Intelligence
    Sep. 2018 - Jun. 2022
Experience
  • Beta Infinity (Embodied Memory Team)
    Beta Infinity (Embodied Memory Team)
    Research Intern, Spatio-Temporal Memory in Embodied AI
    Jun. 2026 - Present
  • Huawei (2012 Laboratories)
    Huawei (2012 Laboratories)
    Research Intern, Spatio-Temporal Foundation Models
    Feb. 2025 - Dec. 2025
  • XPeng Motors (Autonomous Driving Center)
    XPeng Motors (Autonomous Driving Center)
    Research Intern, Visual Perception for Autonomous Driving
    May. 2024 - Nov. 2024
  • Tencent (Workflow Data Center)
    Tencent (Workflow Data Center)
    Software Engineer (Full-time), Large-Scale Data Stream Engineering
    Jun. 2022 - May. 2023
  • Tencent (Workflow Data Center)
    Tencent (Workflow Data Center)
    Software Intern, Event Series Orchestration
    Jun. 2021 - Sep. 2021
Service
  • Reviewer: NeurIPS 2026; ICLR 2025, 2026; KDD 2026, 2027; MM 2025; FARS (Fully Automated Research System); IEEE TPAMI; IEEE Neurocomputing; IJITDM
  • PC Member: ACM MM 2026; AAAI 2026; 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 Learning
    Spring 2026
  • PLED5001 Communicating Research in English
    Spring 2025
  • PDEV6800 Introduction to Teaching and Learning in Higher Education
    Fall 2024
Awards
  • Junior Student Track Awardees of 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, Tencent
    2022
  • Silver Award (2nd/12) in Code World Program, Tencent
    2022
  • Outstanding Student Award (8th/100) in New Employee Training, Tencent
    2022
  • Outstanding Graduation Thesis Award (Top 2%), HFUT
    2022
  • First Prize (Top 10) in CSDN Technology Blogger Competition
    2020
News
2026
One paper on Multimodal Spatio-Temporal forecasting was accepted to ACM MM 2026.
Jul 10
I was invited to serve as a reviewer for KDD 2027 (AI for Sciences Track).
Jul 01
I was invited to serve as a PC member for MILETS 2026 @ KDD 2026.
Jun 09
I passed my Ph.D. PQE and officially became a Ph.D. Candidate at HKUST (GZ).
May 21
One paper about time series memory was accepted by KDD 2026 research track.
May 16
One paper on sample-adaptive dropout for robust time series forecasting was accepted to ICML 2026.
May 01
I am honored to be invited as a reviewer of International Journal of Information Technology & Decision Making (IJITDM).
Apr 10
I was invited to be a reviewer of NeurIPS 2026.
Mar 25
I am honored to be invited as a reviewer of FARS (Fully Automated Research System).
Mar 21
I am glad to become a visiting student at Tsinghua University and National Supercomputing Center.
Mar 04
I was invited to serve as a reviewer for KDD 2026 (AI4Science Track).
Feb 28
I was invited to serve as a PC member for ACM MM 2026.
Feb 20
I was invited to serve as a PC member for PAKDD 2026.
Jan 15
I was invited to serve as a Reviewer for IEEE TPAMI.
Jan 15
2025
One tutorial on Multimodal Learning for Spatio-Temporal Data Mining Era of Foundation Models was accepted to ICME 2026.
Dec 24
I was invited to serve as a Reviewer for Neurocomputing.
Dec 24
One paper on vision for time series forecasting was accepted to AAAI 2026.
Nov 08
One paper on Spatio-Temporal Foundation Model was accepted to NeurIPS 2025 (spotlight).
Sep 18
I was invited to serve as a reviewer for ICLR 2026.
Sep 03
One paper on Traffic Flow Forecasting was accepted to TITS 2025.
Aug 20
I was invited to serve as a PC member for AAAI 2026 (Special Track on AI for Social Impact).
Aug 08
I was invited to serve as a PC member for AAAI 2026.
Jul 26
I was invited to serve as a reviewer for KDD 2026 Datasets and Benchmarks Track.
Jul 25
I was invited to serve as a reviewer for MM 2025 Dataset Track.
Jul 23
One paper on Multimodal Building Electricity Loads Forecasting was accepted to MM 2025.
Jul 05
One paper on Urban Heat Island Effect Forecasting was accepted to KDD 2025.
May 15
One paper on Multimodal Time Series Forecasting was accepted to ICML 2025.
May 01
I was invited to serve as a reviewer for MM 2025.
Apr 26
One tutorial on Multimodal Learning for Spatio-Temporal Data Mining was accepted to MM 2025.
Feb 28
I started to cooperate with Huawei Service Lab, leading the project of Spatio-temporal knowledge fusion.
Feb 06
I started my PhD studies at the Hong Kong University of Science and Technology (Guangzhou).
Feb 05
I received the Runner-Up Prize in the 2024 HKUST(GZ) DSA Excellent Research Award.
Jan 27
2024
Two papers on Urban Indicator Prediction and Air Quality Inference were accepted to AAAI 2025.
Dec 10
I successfully defended my MPhil thesis in Data Science and Analytics at HKUST(GZ).
Nov 25
I was invited to serve as a reviewer for ICLR 2025.
Aug 23
One paper on Urban Multimodal Image-Text Retrieval was accepted to MM 2024.
Jul 18
Two papers on Spatio-Temporal Prediction and Neural Networks were accepted to IJCAI 2024.
May 14
I joined XPENG XBrain Team as a Research Intern focusing on multimodal research in autonomous driving scenarios.
May 14
One paper on LLM-Enhanced Urban Region Profiling was accepted to WWW 2024.
Jan 23
2023
I started my MPhil studies at the Hong Kong University of Science and Technology (Guangzhou).
Aug 24
2022
I officially joined Tencent as a Software Engineer!
Jul 04
I graduated from Hefei University of Technology with Outstanding Thesis Award.
Jun 05
2021
I completed my three-month internship at Tencent and received a SP return offer.
Sep 14
Publications (view all )
DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting
DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting

Siru Zhong, Yiqiu Liu, Zhiqing Cui, Zezhi Shao, Fei Wang, Qingsong Wen, Yuxuan Liang

ICML (International Conference on Machine Learning) 2026, Seoul, South Korea

[Code] [Paper] [时空探索之旅] [时序大模型]

DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting
DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting

Siru Zhong, Yiqiu Liu, Zhiqing Cui, Zezhi Shao, Fei Wang, Qingsong Wen, Yuxuan Liang

ICML (International Conference on Machine Learning) 2026, Seoul, South Korea

[Code] [Paper] [时空探索之旅] [时序大模型]

Learning to Factorize Spatio-Temporal Foundation Models
Learning to Factorize Spatio-Temporal Foundation Models

Siru Zhong, Junjie Qiu, Yangyu Wu, Xingchen Zou, Zhongwen Rao, Bin Yang, Chenjuan Guo, Hao Xu, Yuxuan Liang

NeurIPS (Advances in Neural Information Processing Systems) 2025, Santiago, America Spotlight (688/21,575, 3.19%)

[Code] [Paper] [AI TIME 论道] [时空探索之旅] [南方科技大学统计与数据科学系]

Learning to Factorize Spatio-Temporal Foundation Models
Learning to Factorize Spatio-Temporal Foundation Models

Siru Zhong, Junjie Qiu, Yangyu Wu, Xingchen Zou, Zhongwen Rao, Bin Yang, Chenjuan Guo, Hao Xu, Yuxuan Liang

NeurIPS (Advances in Neural Information Processing Systems) 2025, Santiago, America Spotlight (688/21,575, 3.19%)

[Code] [Paper] [AI TIME 论道] [时空探索之旅] [南方科技大学统计与数据科学系]

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting

Siru Zhong, Weilin Ruan, Min Jin, Huan Li, Qingsong Wen, Yuxuan Liang

ICML (International Conference on Machine Learning) 2025, Vancouver, Canada

[Code] [Paper] [时序大模型] [大头的算法笔记] [时序量化Top] [时序前沿研究] [当交通遇上机器学习] [圆圆的算法笔记]

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting

Siru Zhong, Weilin Ruan, Min Jin, Huan Li, Qingsong Wen, Yuxuan Liang

ICML (International Conference on Machine Learning) 2025, Vancouver, Canada

[Code] [Paper] [时序大模型] [大头的算法笔记] [时序量化Top] [时序前沿研究] [当交通遇上机器学习] [圆圆的算法笔记]

Multimodal Learning for Spatio-Temporal Data Mining
Multimodal Learning for Spatio-Temporal Data Mining

Siru Zhong, Xixuan Hao, Hao Miao, Yan Zhao, Oingsong Wen, Roger Zimmermann, Yuxuan Liang

ACM MM (ACM International Conference on Multimedia) 2025, Dublin, Ireland

[Code] [Site] [Toturial]

Multimodal Learning for Spatio-Temporal Data Mining
Multimodal Learning for Spatio-Temporal Data Mining

Siru Zhong, Xixuan Hao, Hao Miao, Yan Zhao, Oingsong Wen, Roger Zimmermann, Yuxuan Liang

ACM MM (ACM International Conference on Multimedia) 2025, Dublin, Ireland

[Code] [Site] [Toturial]

UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation
UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation

Siru Zhong, Xixuan Hao, Yibo Yan, Ying Zhang, Yangqiu Song, Yuxuan Liang

ACM MM (ACM International Conference on Multimedia) 2024, Melbourne, Australia

[Code] [Paper] [遥感与深度学习]

UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation
UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation

Siru Zhong, Xixuan Hao, Yibo Yan, Ying Zhang, Yangqiu Song, Yuxuan Liang

ACM MM (ACM International Conference on Multimedia) 2024, Melbourne, Australia

[Code] [Paper] [遥感与深度学习]

Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting
Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting

Siru Zhong, Meng Zhao, Haohuan Fu, Haoyang Li, Qingsong Wen, Yuxuan Liang

Under review.

[Paper] [算法前哨站]

Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting
Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting

Siru Zhong, Meng Zhao, Haohuan Fu, Haoyang Li, Qingsong Wen, Yuxuan Liang

Under review.

[Paper] [算法前哨站]

Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models
Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models

Siru Zhong, Junjie Qiu, Yangyu Wu, Yiqiu Liu, Yuanpeng He, Zhongwen Rao, Bin Yang, Chenjuan Guo, Hao Xu, Yuxuan Liang

Under review.

[Code] [Paper] [AI TIME 论道] [时空探索之旅]

Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models
Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models

Siru Zhong, Junjie Qiu, Yangyu Wu, Yiqiu Liu, Yuanpeng He, Zhongwen Rao, Bin Yang, Chenjuan Guo, Hao Xu, Yuxuan Liang

Under review.

[Code] [Paper] [AI TIME 论道] [时空探索之旅]