Yan Lin's Homepage

Biography - Yan Lin

I am currently an assistant professor in the Department of Computer Science at Aalborg University, Denmark. I received my PhD and Bachelor's degrees from Beijing Jiaotong University, China. My research interests include spatiotemporal data mining, representation learning, and AI for science.

Publications

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NeurIPS | 2025

Poster

TrajMamba: An Efficient and Semantic-rich Vehicle Trajectory Pre-training Model

Yichen Liu*, Yan Lin*, Shengnan Guo, Zeyu Zhou, Youfang Lin, Huaiyu Wan

NeurIPS | 2025

Oral Poster Preprint

TransferTraj: A Vehicle Trajectory Learning Model for Region and Task Transferability

Tonglong Wei*, Yan Lin*, Zeyu Zhou, Haomin Wen, Jilin Hu, Shengnan Guo, Youfang Lin, Gao Cong, Huaiyu Wan

NeurIPS | 2025

Poster Preprint

PLMTrajRec: A Scalable and Generalizable Trajectory Recovery Method with Pre-trained Language Models

Tonglong Wei*, Yan Lin*, Youfang Lin, Shengnan Guo, Jilin Hu, Haitao Yuan, Gao Cong, Huaiyu Wan

IEEE TKDE | 2025

Paper Preprint Code

UVTM: Universal Vehicle Trajectory Modeling with ST Feature Domain Generation

Yan Lin, Jilin Hu, Shengnan Guo, Bin Yang, Christian S. Jensen, Youfang Lin, Huaiyu Wan

IJCAI | 2025

Preprint Code

TrajCogn: Leveraging LLMs for Cognizing Movement Patterns and Travel Purposes from Trajectories

Zeyu Zhou*, Yan Lin*, Haomin Wen, Shengnan Guo, Jilin Hu, Youfang Lin, Huaiyu Wan

IEEE TKDE | 2025

Paper Preprint Code

UniTE: A Survey and Unified Pipeline for Pre-training Spatiotemporal Trajectory Embeddings

Yan Lin, Zeyu Zhou, Yicheng Liu, Haochen Lv, Haomin Wen, Tianyi Li, Yushuai Li, Christian S. Jensen, Shengnan Guo, Youfang Lin, Huaiyu Wan

KDD | 2025

Paper Preprint Code

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting

Xiangfei Qiu, Xingjian Wu, Yan Lin, Chenjuan Guo, Jilin Hu, Bin Yang

IEEE TKDE | 2024

Paper Preprint Code

Diff-RNTraj: A Structure-aware Diffusion Model for Road Network-constrained Trajectory Generation

Tonglong Wei, Youfang Lin, Shengnan Guo, Yan Lin, Yiheng Huang, Chenyang Xiang, Yuqing Bai, Menglu Ya, Huaiyu Wan

IEEE TKDE | 2024

Paper

STCDM: Spatio-Temporal Contrastive Diffusion Model for Check-In Sequence Generation

Letian Gong, Shengnan Guo, Yan Lin, Yichen Liu, Erwen Zheng, Yiwei Shuang, Youfang Lin, Jilin Hu, Huaiyu Wan

IEEE TKDE | 2024

Paper Preprint Code

Micro-Macro Spatial-Temporal Graph-based Encoder-Decoder for Map-Constrained Trajectory Recovery

Tonglong Wei, Youfang Lin, Yan Lin, Shengnan Guo, Lan Zhang, Huaiyu Wan

KBS | 2024

Paper Code

Inductive and Adaptive Graph Convolution Networks Equipped with Constraint Task for Spatial-Temporal Traffic Data Kriging

Tonglong Wei, Youfang Lin, Shengnan Guo, Yan Lin, Yiji Zhao, Xiyuan Jin, Zhihao Wu, Huaiyu Wan

IEEE TKDE | 2024

Paper Preprint

Spatial-Temporal Cross-View Contrastive Pre-Training for Check-in Sequence Representation Learning

Letian Gong, Huaiyu Wan, Shengnan Guo, Li Xiucheng, Yan Lin, Erwen Zheng, Tianyi Wang, Zeyu Zhou, Youfang Lin

* Equal Contribution

Projects

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Fundamental Research Funds for the Central Universities of China

Research on Prediction of User Travel Destination and Travel Time Based on Trajectory Representation Learning

Applies representation learning to trajectory data to transform original features into high-level information, improving the performance of downstream tasks such as travel time and destination prediction.

Personal Interest Project

Home Install

Development of OverleafCopilot - Empowering Academic Writing in Overleaf with Large Language Models

This project aims to develop a Browser extension to seamlessly integrate Large Language Models (such as ChatGPT) into the popular online academic writing platform, Overleaf.

Personal Interest Project

Website Code

Development of PromptGenius - All-purpose prompts for LLMs

This project focuses on developing a website that offers a wide range of prompt categories, enhancing the versatility of LLMs for various tasks and improving their output quality.

Villum Foundation

Research on Inverse Design of Materials Using Diffusion Probabilistic Models

This project focuses on developing diffusion probabilistic models to first understand the relationship between chemistry/structure and material properties, then enable the inverse design of new materials with specific properties. This project currently supports my postdoctoral research position.

National Natural Science Foundation of China

Research on Pre-training Representation Learning Methods of Spatial-temporal Trajectory Data for Traffic Prediction

This project aims to propose pre-training representation learning methods for spatial-temporal trajectory data, modeling multiple features to improve traffic prediction tasks. It demonstrates how trajectory representation learning can enhance traffic data mining.

National Natural Science Foundation of China

Research on Spatial-temporal Trajectory Generation and Representation Learning Methods for Sparsity Problems

This project explores how to generate high-quality spatial-temporal trajectory data and corresponding representations to address sparsity-related issues, thereby supporting a variety of downstream tasks.

Presentations

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Oral Presentation | PNCS17

Slides

AMDEN: Amorphous Materials DEnoising Network

Guest lecture | Aalborg University

Slides

Self-supervised Learning of Trajectory Data

Workshop presentation | KDD 2024

Slides Paper

PLM4Traj: Leveraging Pre-trained Language Models for Cognizing Movement Patterns and Travel Purposes from Trajectories

Services

IEEE, ACM member
Secretary of IEEE (Denmark Section) Computer Society
Reviewer for journals: TKDE, TKDD, TIST, TII, and TVT
Member of program committees of conferences: KDD, ICLR, NeurIPS, AAAI, CVPR, ICCV, IJCAI, WWW, and WACV