Weilin Ruan (阮炜霖)

Weilin Ruan (阮炜霖)

MPhil Student @ HKUST(GZ)

Bachelor of Engineering @ Jinan University

I am a first-year MPhil student in Data Science at the Hong Kong University of Science and Technology (Guangzhou), supervised by Prof. Yuxuan Liang.

[Highlight] Now I am looking for research partners and PhD opportunities. If interested in my research direction, please feel free to contact me!

My research interests include Time Series Forecasting, Spatio-Temporal Data Mining, Multimodal Learning, Urban Computing, and Deep Learning.

Education

  • HKUST(GZ) Logo
    HKUST(GZ) - Information Hub - Data Science and Analysis
    Sep 2024 - June 2026
  • Jinan University Logo
    Jinan University - Computer Science Department - Network Engineering
    Sep 2020 - June 2024

Latest News

  • Program Committee - Invited to serve as a Program Committee member for AAAI 2026.
    July 2025
  • Paper Acceptance - Paper accepted to ICCV 2025 Workshop.
    July 2025
  • Paper Acceptance - Paper on Traffic Flow Forecasting accepted to IEEE TITS Journal.
    Aug 2025
  • Paper Acceptance - Paper on Multimodal Building Electricity Loads Forecasting accepted to ACM MM 2025.
    July 2025
  • Paper Acceptance - Paper on Urban Heat Island Effect Forecasting accepted to KDD 2025.
    May 2025
  • Paper Acceptance - Paper on Spatio-Temporal Forecasting accepted to ECML-PKDD 2025.
    May 2025
  • Paper Acceptance - Paper on Multimodal Time Series Forecasting accepted to ICML 2025.
    May 2025
  • Reviewer Appointment - Appointed as a reviewer for IJCNN and ICASSP conferences.
    Dec 2024
  • Outstanding Graduate - Received the undergraduate certificate from Jinan University as an outstanding graduate of the department of Information Science and Technology.
    June 2024
  • Research Internship - Joined the CityMind team as an intern led by Prof. Yuxuan Liang.
    Aug 2023
  • RBCC Achievement - Participated in the RBCC offline held in HKUST(GZ) and achieved outstanding camper.
    July 2023

Featured Publications

Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting
Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting Featured

Weilin Ruan, Wenzhuo Wang, Siru Zhong, Wei Chen, Li Liu, Yuxuan Liang

TITS. 2025

This paper proposes a novel spatio-temporal unitized model for traffic flow forecasting that effectively captures complex dependencies across both space and time dimensions, achieving state-of-the-art performance on multiple benchmark datasets.

Paper Code

Towards Multi-Scenario Forecasting of Building Electricity Loads with Multimodal Data
Towards Multi-Scenario Forecasting of Building Electricity Loads with Multimodal Data Featured

Yongzheng Liu, Siru Zhong, Gefeng Luo, Weilin Ruan, Yuxuan Liang

ACM MM. 2025

We propose MMLoad, a novel diffusion-based multimodal framework for multi-scenario building load forecasting with three innovations: Multimodal Data Enhancement Pipeline, Cross-modal Relation Encoder, and Scenario-Conditioned Diffusion Generator with uncertainty quantification, establishing a new paradigm for multimodal learning in smart energy systems.

Paper Code

Low-rank Adaptation for Spatio-Temporal Forecasting
Low-rank Adaptation for Spatio-Temporal Forecasting Featured

Weilin Ruan, Wei Chen, Xilin Dang, Jianxiang Zhou, Weichuang Li, Xu Liu, Yuxuan Liang

ECML. 2025

This paper presents ST-LoRA, a novel low-rank adaptation framework as an off-the-shelf plugin for existing spatial-temporal prediction models, which alleviates node heterogeneity problems through node-level adjustments while minimally increasing parameters and training time.

Paper Code

Fine-grained Urban Heat Island Effect Forecasting: A Context-aware Thermodynamic Modeling Framework
Fine-grained Urban Heat Island Effect Forecasting: A Context-aware Thermodynamic Modeling Framework Featured

Xingchen Zou, Weilin Ruan, Siru Zhong, Yuehong HU, Yuxuan Liang

KDD. 2025

We present DeepUHI, a heat equation-based framework that models urban heat island effects through thermodynamic cycles and thermal flows, integrating multimodal environmental data to achieve precise street-level temperature forecasting, now deployed as a real-time warning system in Seoul.

Paper Code

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

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

ICML. 2025

This paper proposes Time-VLM, a novel multimodal framework that leverages pre-trained Vision-Language Models (VLMs) to bridge temporal, visual, and textual modalities for enhanced time series forecasting.

Paper Code

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Selected Awards

  • Outstanding Graduates - Jinan University
    Fall 2024
  • Golden Arowana Scholarship - Jinan University
    Fall 2023
  • Bronze Medal - ICPC International Collegiate Programming Contest
    Fall 2022
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