Weilin Ruan

Weilin Ruan

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 Spatio-Temporal Data Mining, Computer Vision, LLM-Agents, and Graph Learning.

Education

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

Latest News

  • 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

Publications

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

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

Under review. 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

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

Under review. 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

LDM4TS: Latent Diffusion Model for Time Series Forecasting
LDM4TS: Latent Diffusion Model for Time Series Forecasting

Weilin Ruan, Siru Zhong, Haomin Wen, Yuxuan Liang

Under review. 2025

This paper introduces LDM4TS, a novel latent diffusion model for time series forecasting that transforms time series into multiple image representations and leverages diffusion models to enhance forecasting capabilities.

Paper

A Game-Theoretic Spatio-Temporal Reinforcement Learning Framework for Collaborative Public Resource Allocation
A Game-Theoretic Spatio-Temporal Reinforcement Learning Framework for Collaborative Public Resource Allocation

Songxin Lei, Qiongyan WANG, Yanchen ZHU, Hanyu Yao, Sijie Ruan, Weilin Ruan, Yuyu Luo, Yuxuan Liang

Under review. 2024

We introduce GSTRL, a novel game-theoretic reinforcement learning framework that addresses collaborative public resource allocation by modeling it as a cooperative potential game and incorporating spatio-temporal learning to capture crowd dynamics, outperforming existing methods on real-world datasets.

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
View All Awards