Jilin Hu

School of Data Science and Engineering, East China Normal University
Room 217 at Dili Building, 3663 North Zhongshan Road, Shanghai, China
jlhu [at] dase.ecnu.edu.cn
Google scholar | DBLP

Jilin Hu is a Professor at the School of Data Science and Engineering, East China Normal University. Prior to that, he was an Associate Professor at the Department of Computer Science, Aalborg University. He was a Research Assocaite at Inception Institute of Artificial Intelligence (UAE) under the supervision of Prof. Jianbing Shen. He obtained the Ph.D. degree from Aalborg Unviersity in 2019, under the supervision of Prof. Christian S. Jensen and Prof. Bin Yang. From Oct. 2017 to April. 2018, he visited University of California, Berkeley under the supervision of Prof. Alexandre Bayen.

Research interest: Spatio-Temporal Data Management, Traffic Data Analysis, AI For Science

Never stop looking for highly self-motivated students.

News

Nov 8, 2025	Our paper “Beyond Dynamic Quantization: An Efficient Static Hierarchical Mix-precision Framework for Near-Lossless LLM Compression” receives EMNLP Best Paper Award (Industry Track)!
Nov 8, 2025	One paper “Spatial-Temporal Feedback Diffusion Guidance for Controlled Traffic Imputation” is accepted as Oral by AAAI 2026, and congrats to Xiaowei Mao and Huihu Ding!
Nov 8, 2025	One paper “SculptDrug: A Spatial Condition-Aware Bayesian Flow Model for Structure-based Drug Design” is accepted as Oral by AAAI 2026, and congrats to Qingsong!
Nov 8, 2025	One paper “DiffMM: Efficient Method for Accurate Noisy and Sparse Trajectory Map Matching via One Step Diffusion” is accepted as Poster by AAAI 2026, and congrats to Chenxu Han!
Nov 8, 2025	One paper “Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline” is accepted as Oral by AAAI 2026, and congrats to Xuyuan Liu!
Oct 20, 2025	One paper “An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data” is accepted by ICDE 2026, and congrats to Buang!
Sep 25, 2025	One paper “1+1>2: A Synergistic Sparse and Low-Rank Compression Method for Large Language Models” is accepted by EMNLP 2025 Findings, and congrats to Zeliang Zong and Kai Zhang!
Sep 25, 2025	One paper “Beyond Dynamic Quantization: An Efficient Static Hierarchical Mix-precision Framework for Near-Lossless LLM Compression” is accepted as Poster by EMNLP 2025 Industry Track, and congrats to Zeliang Zong and Kai Zhang!

Selected Publications

(# Corresponding Author)

AAAI’26

SculptDrug: A Spatial Condition-Aware Bayesian Flow Model for Structure-based Drug Design

Qingsong Zhong, Haomin Yu, Yan Lin, Wangmeng Shen, Long Zeng, and Jilin Hu^#

In AAAI 2026
AAAI’26

DiffMM: Efficient Method for Accurate Noisy and Sparse Trajectory Map Matching via One Step Diffusion

Chenxu Han, Sean Bin Yang, and Jilin Hu^#

In AAAI 2026
AAAI’26

Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline

Xvyuan Liu, Xiangfei Qiu, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Jilin Hu^# , and Bin Yang

In AAAI 2026
NeuriPS’25

DBLoss: Decomposition-based Loss Function for Time Series Forecasting

Xiangfei Qiu, Xingjian Wu, Hanyin Cheng, Xvyuan Liu, Chenjuan Guo, Jilin Hu^# , and Bin Yang

In NeuriPS 2025
PVLDB’25

TAB: Unified Benchmarking of Time Series Anomaly Detection Methods

Xiangfei Qiu, Zhe Li, Wanghui Qiu, Shiyan Hu, Lekui Zhou, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Aoying Zhou, Zhenli Sheng, Jilin Hu^# , Christian S. Jensen, and Bin Yang

In PVLDB 2025
KDD’25

SSD-TS: Exploring the potential of linear state space models for diffusion models in time series imputation

Hongfan Gao, Wangmeng Shen, Xiangfei Qiu, Ronghui Xu, Bin Yang, and Jilin Hu^#

In KDD 2025
IJCAI’25

ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting

Haichen Wang, Liu Yang, Xinyuan Zhang, Haomin Yu, Ming Li, and Jilin Hu^#

In IJCAI 2025
KDD’25

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting

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

In KDD 2025
WWW’25

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, and Jilin Hu^#

In WWW 2025

PVLDB’24

TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods

Xiangfei Qiu, Jilin Hu^# , Lekui Zhou, Xingjian Wu, Junyang Du, Buang Zhang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Zhenli Sheng, and Bin Yang

In PVLDB 2024

arXiv Bib Code

@inproceedings{DBLP:journals/pvldb/QiuHZWDZGZJSY24,
  arxiv = {2403.20150},
  author = {Qiu, Xiangfei and Hu, Jilin and Zhou, Lekui and Wu, Xingjian and Du, Junyang and Zhang, Buang and Guo, Chenjuan and Zhou, Aoying and Jensen, Christian S. and Sheng, Zhenli and Yang, Bin},
  bibtex_show = {true},
  booktitle = {PVLDB},
  code = {https://github.com/decisionintelligence/TFB},
  corr = {true},
  number = {9},
  pages = {2363--2377},
  selected = {true},
  title = {{TFB:} Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods},
  volume = {17},
  year = {2024},
  abbr = {PVLDB'24}
}

SIGMOD’24

Origin-Destination Travel Time Oracle for Map-based Services

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

In SIGMOD 2024

arXiv Bib

@inproceedings{2307.03048,
  arxiv = {2307.03048},
  author = {Lin, Yan and Wan, Huaiyu and Hu, Jilin and Guo, Shengnan and Yang, Bin and Lin, Youfang and Jensen, Christian S.},
  bibtex_show = {true},
  booktitle = {SIGMOD},
  corr = {true},
  selected = {true},
  title = {Origin-Destination Travel Time Oracle for Map-based Services},
  year = {2024},
  abbr = {SIGMOD'24}
}

KDD

LightPath: Lightweight and Scalable Path Representation Learning

Sean Bin Yang, Jilin Hu^# , Chenjuan Guo, Bin Yang, and Christian S. Jensen

In KDD 2023

arXiv Bib Code

@inproceedings{10.1145/3580305.3599415,
  abbr = {KDD},
  arxiv = {2307.10171},
  author = {Yang, Sean Bin and Hu, Jilin and Guo, Chenjuan and Yang, Bin and Jensen, Christian S.},
  bibtex_show = {true},
  booktitle = {KDD},
  code = {https://github.com/Sean-Bin-Yang/LightPath},
  corr = {true},
  pages = {2999--3010},
  selected = {true},
  title = {LightPath: Lightweight and Scalable Path Representation Learning},
  year = {2023}
}

ICDE

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version

Sean Bin Yang, Chenjuan Guo, Jilin Hu^# , Bin Yang, Jian Tang, and Christian S. Jensen

In ICDE 2022

arXiv Bib Code

@inproceedings{DBLP:journals/corr/abs-2203-16110,
  abbr = {ICDE},
  arxiv = {2203.16110},
  author = {Yang, Sean Bin and Guo, Chenjuan and Hu, Jilin and Yang, Bin and Tang, Jian and Jensen, Christian S.},
  bibtex_show = {true},
  booktitle = {ICDE},
  code = {https://github.com/Sean-Bin-Yang/TPR.git},
  corr = {true},
  selected = {true},
  title = {Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version},
  year = {2022}
}

AAAI

Hyperverlet: A Symplectic Hypersolver for Hamiltonian Systems

Frederik Mathiesen, Bin Yang, and Jilin Hu^#

In AAAI 2022

Bib Code

@inproceedings{aaai22_hamilton,
  abbr = {AAAI},
  author = {Mathiesen, Frederik and Yang, Bin and Hu, Jilin},
  bibtex_show = {true},
  booktitle = {AAAI},
  code = {https://github.com/Zinoex/hyperverlet},
  corr = {true},
  selected = {true},
  title = {Hyperverlet: A Symplectic Hypersolver for Hamiltonian Systems},
  year = {2022}
}

IJCAI

Unsupervised Path Representation Learning with Curriculum Negative Sampling

Sean Bin Yang, Chenjuan Guo, Jilin Hu^# , Jian Tang, and Bin Yang

In IJCAI 2021

arXiv Bib PDF Code

@inproceedings{DBLP:conf/ijcai/YangGHT021,
  abbr = {IJCAI},
  arxiv = {2106.09373},
  author = {Yang, Sean Bin and Guo, Chenjuan and Hu, Jilin and Tang, Jian and Yang, Bin},
  bibtex_show = {true},
  booktitle = {IJCAI},
  code = {https://github.com/Sean-Bin-Yang/Path-InfoMax.git},
  corr = {true},
  pages = {3286--3292},
  pdf = {IJCAI21.pdf},
  selected = {true},
  title = {Unsupervised Path Representation Learning with Curriculum Negative Sampling},
  year = {2021}
}

ICDE

Stochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural Networks

Jilin Hu , Bin Yang, Chenjuan Guo, Christian S. Jensen, and Hui Xiong

In ICDE 2020

Bib PDF Code

@inproceedings{DBLP:conf/icde/Hu0GJX20,
  abbr = {ICDE},
  author = {Hu, Jilin and Yang, Bin and Guo, Chenjuan and Jensen, Christian S. and Xiong, Hui},
  bibtex_show = {true},
  booktitle = {ICDE},
  code = {https://github.com/hujilin1229/od-pred},
  pages = {1417--1428},
  pdf = {ICDE2020},
  publisher = {{IEEE}},
  selected = {true},
  title = {Stochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural Networks},
  year = {2020}
}

ICDE

Stochastic Weight Completion for Road Networks Using Graph Convolutional Networks

Jilin Hu , Chenjuan Guo, Bin Yang, and Christian S. Jensen

In ICDE 2019

Bib PDF Code

@inproceedings{DBLP:conf/icde/HuG0J19,
  abbr = {ICDE},
  author = {Hu, Jilin and Guo, Chenjuan and Yang, Bin and Jensen, Christian S.},
  bibtex_show = {true},
  booktitle = {ICDE},
  code = {https://github.com/hujilin1229/GraphCompletion},
  pages = {1274--1285},
  pdf = {ICDE2019.pdf},
  selected = {true},
  title = {Stochastic Weight Completion for Road Networks Using Graph Convolutional Networks},
  year = {2019}
}

ISs

Residual memory inference network for regression tracking with weighted gradient harmonized loss

Huanlong Zhang, Jiapeng Zhang, Guohao Nie, Jilin Hu^# , and W.J. (Chris) Zhang

Information Sciences 2022

Bib

@article{ZHANG2022105,
  author = {Zhang, Huanlong and Zhang, Jiapeng and Nie, Guohao and Hu, Jilin and Zhang, W.J. (Chris)},
  title = {Residual memory inference network for regression tracking with weighted gradient harmonized loss},
  journal = {Information Sciences},
  volume = {597},
  pages = {105-124},
  year = {2022},
  bibtex_show = {true},
  abbr = {ISs},
  corr = {true},
  selected = {true}
}

GeoInformatica

Enabling time-dependent uncertain eco-weights for road networks

Jilin Hu , Bin Yang, Christian S. Jensen, and Yu Ma

GeoInformatica 2017

Bib PDF

@article{DBLP:journals/geoinformatica/HuYJM17,
  author = {Hu, Jilin and Yang, Bin and Jensen, Christian S. and Ma, Yu},
  title = {Enabling time-dependent uncertain eco-weights for road networks},
  journal = {GeoInformatica},
  volume = {21},
  number = {1},
  pages = {57--88},
  year = {2017},
  pdf = {GeoInfo.pdf},
  bibtex_show = {true},
  abbr = {GeoInformatica},
  selected = {true}
}

VLDBJ

Risk-aware path selection with time-varying, uncertain travel costs: a time series approach

Jilin Hu , Bin Yang, Chenjuan Guo, and Christian S. Jensen

VLDB J. 2018

Bib PDF

@article{DBLP:journals/vldb/HuYGJ18,
  author = {Hu, Jilin and Yang, Bin and Guo, Chenjuan and Jensen, Christian S.},
  title = {Risk-aware path selection with time-varying, uncertain travel costs: a time series approach},
  journal = {{VLDB} J.},
  volume = {27},
  number = {2},
  pages = {179--200},
  year = {2018},
  bibtex_show = {true},
  abbr = {VLDBJ},
  selected = {true},
  pdf = {https://link.springer.com/article/10.1007/s00778-018-0494-9}
}

TNNLS

Few-Shot Object Detection With Self-Supervising and Cooperative Classifier

Di Qi, Jilin Hu^# , and Jianbing Shen

IEEE TNNLS 2024

Bib

@article{qi2022fsod,
  author = {Qi, Di and Hu, Jilin and Shen, Jianbing},
  title = {Few-Shot Object Detection With Self-Supervising and Cooperative Classifier},
  journal = {IEEE TNNLS},
  volume = {35},
  number = {4},
  pages = {5435--5446},
  year = {2024},
  bibtex_show = {true},
  abbr = {TNNLS},
  selected = {true},
  corr = {true}
}

News

Selected Publications

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