Weilin Ruan (阮炜霖)

Weilin Ruan (阮炜霖)

MPhil Student @ HKUST(GZ)

Bachelor of Engineering @ Jinan University

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

[Highlight] I will start my joint Ph.D. program between CUHK and Knowin AI in 2026Fall, under the supervision of Prof. James Cheng. 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, Multi-Agent Systems, and Embodied AI.

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

  • Paper Acceptance - Two papers accepted to AAAI 2026.
    Nov 2025
  • Reviewer Appointment - Appointed as a reviewer for ICLR 2026 conference.
    Sep 2025
  • New Position - Joined Knowin AI Inc. as an Algorithm Researcher.
    Sep 2025
  • 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
  • Program Committee - Invited to serve as a Program Committee member for WebST 2025.
    Jan 2025
  • 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

Pinned Publications

OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting Pinned

Sisuo Lyu, Siru Zhong, Weilin Ruan, Qingxiang Liu, Qingsong Wen, Hui Xiong, Yuxuan Liang

AAAI. 2026

We propose OccamVTS, a novel framework that distills large vision models to only 1% of their original parameters for efficient time series forecasting, demonstrating that extreme parameter reduction can be achieved while maintaining strong predictive performance through innovative distillation techniques.

Paper Code

Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction
Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction Pinned

Weilin Ruan, Xilin Dang, Ziyu Zhou, Sisuo Lyu, Yuxuan Liang

AAAI. 2026

We propose RAST, a universal framework that integrates retrieval-augmented mechanisms with spatio-temporal modeling to address limited contextual capacity and low predictability in traffic prediction. Our framework consists of three key designs: Decoupled Encoder and Query Generator, Spatio-temporal Retrieval Store and Retrievers, and Universal Backbone Predictor that flexibly accommodates pre-trained STGNNs or simple MLP predictors.

Paper Code

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 Pinned

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 Pinned

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 Pinned

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

View All Publications

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