Biography - Yan Lin

I am currently a postdoctoral researcher in the Department of Computer Science at Aalborg University. 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.

Yan Lin

Publications

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IEEE TKDE | 2025

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

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

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

WWW | 2025

Path-LLM: A Multi-Modal Path Representation Learning by Aligning and Fusing with Large Language Models

Yongfu Wei*, Yan Lin*, Hongfan Gao, Ronghui Xu, Sean Bin Yang, Jilin Hu

AAAI | 2025

DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation

Xiaowei Mao*, Yan Lin*, Shengnan Guo, Yubin Chen, Xingyu Xian, Haomin Wen, Qisen Xu, Youfang Lin, Huaiyu Wan

NeurIPS | 2024

Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models

Letian Gong*, Yan Lin*, Xinyue Zhang, Yiwen Lu, Xuedi Han, Yichen Liu, Shengnan Guo, Youfang Lin, Huaiyu Wan

SIGMOD | 2024

Origin-Destination Travel Time Oracle for Map-based Services

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

IEEE TKDE | 2023

Pre-training General Trajectory Embeddings with Maximum Multi-view Entropy Coding

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

IEEE TKDE | 2022

Pre-training Time-aware location embeddings from spatial-temporal trajectories

Huaiyu Wan, Yan Lin, Shengnan Guo, Youfang Lin

AAAI | 2021

Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction

Yan Lin, Huaiyu Wan, Shengnan Guo, Youfang Lin


KDD | 2025

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting

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

IEEE TKDE | 2024

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

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

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

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

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

AAAI | 2023

Contrastive Pre-training with Adversarial Perturbations for Check-In Sequence Representation Learning

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

ESWA | 2023

Adversarial Self-Attentive Time-Variant Neural Networks for Multi-Step Time Series Forecasting

Changxia Gao, Ning Zhang, Youru Li, Yan Lin, Huaiyu Wan

APIN | 2023

Multi-scale Adaptive Attention-based Time-Variant Neural Networks for Multi-step Time Series Forecasting

Changxia Gao, Ning Zhang, Youru Li, Yan Lin, Huaiyu Wan

NeurIPS | 2023

WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting

Yuxin Jia, Youfang Lin, Xinyan Hao, Yan Lin, Shengnan Guo, Huaiyu Wan

* 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

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

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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Guest lecture | Aalborg University

Self-supervised Learning of Trajectory Data

Workshop presentation | KDD 2024

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

Paper Oral | SIGMOD 2024

Origin-Destination Travel Time Oracle for Map-based Services

Tutorial | SpatialDI 2024

Self-supervised Learning of Spatial-temporal Trajectories

Paper Oral | AAAI 2021

Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction

Services

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