Looking for Ph.D students in areas of graph foundational model and data mining. Drop an email if you are interested to work with me.

• 1/2024 Three papers accepted by ICLR'24. Congrats to Yang, Jiashun, Ziqi and Tao!

• 12/2023 Graph prompt learning survey is at this repo and pdf.

• 11/2023 Our thoughts and survey about graph foundational model is at this repo and pdf.

• 08/2023 Glad to receive the Best Research Paper Award of KDD'23. It is the first time for Mainland and Hongkong of China.

• 06/2023 GADBench is published. It is the first comprehensive comparison between GNN and ensemble models on Anomaly Detection.

• 05/2023 Two papers accepted by KDD'23. Big congrats to Jiawen and Xiangguo!

• 05/2023 Three papers accepted by ACL'23. Big congrats to Nuo and Jianheng!

• 03/2023 Establish Graph Data Joint-Lab with CreateLink, here are the news and video.

• 03/2023 Our paper in Nature Communications received Editors’ Highlight and was reported by DrugAI and ScienceAI.

• 01/2023 One paper about Protein-Protein Interaction accepted by Nature Communications. Big congrats to Ziqi!

• 11/2022 Opensource Harry Potter Dialogue benchmark with Tencent AI Lab. 

• 11/2022 Three papers accepted by AAAI'23. Big congrats to Yang, Ziqi, Jiashun!

• 08/2022 One paper accepted by TPAMI'22.

• 05/2022 One paper accepted by ICML'22. Big congrats to Jianheng!

• 04/2022 Received Tencent AI Lab Rhino-Bird Fund!

Biography

I am an Assistant Professor in Data Science and Analytics Thrust of HKUST (Guangzhou) and an Affiliated Assistant Professor in the Department of Computer Science Engineering of HKUST (Hong Kong). I serve as the Co-Director of HKUST-GZ Create Link Joint Lab. I received Ph.D. degree at The Chinese University of Hong Kong in 2021. During my Ph.D. study, I worked as research intern at Google AI (Mountain view) and Tencent AI Lab. Before my Ph.D. study, I worked as a full-time data mining engineer in Tencent from 2014 to 2017, where I was responsible for WeChat and WeBank fraud prevention. 

Research Interests

• Graph Foundation Model, e.g., graph neural networks, prompt learning, graph multimodal model

• Data Mining, e.g., anomaly detection, time series forecasting

• AI for Science, e.g., drug discovery, healthcare

Talk

• 2023 July, Benchmarking Graph Anomaly Detection at Global AI Conference [Video]

• 2023 May, HKUST Workshop on Big Data and Biomedical & Chemical Science [Slides]

• 2022 July, Invited Talk at LOGS about Graph Anomaly Detection [Video]

Publications

(* stands for the corresponding author)

1. Parameter Efficient Fine-Tuning with Discrete Fourier Transform
   Ziqi Gao^, Qichao Wang^, Aochuan Chen^, Zijing Liu, Bingzhe Wu, Liang Chen, Jia Li*
   ICML 2024

2. A Survey of Graph Meets Large Language Model: Progress and Future Directions
   Yuhan Li^, Zhixun Li^, Peisong Wang^, Jia Li*, Xiangguo Sun, Hong Cheng, Jeffrey Xu Yu
   IJCAI 2024

3. Weakly Supervised Anomaly Detection via Knowledge-Data Alignment
   Haihong Zhao, Chenyi Zi, Yang Liu, Chen Zhang, Yan Zhou, Jia Li*
   WWW 2024

4. Protein Multimer Structure Prediction via Prompt Learning
   Ziqi Gao, Xiangguo Sun, Zijing Liu, Xu Li, Hong Cheng, Jia Li*
   ICLR 2024

5.  Deep Reinforcement Learning for Modelling Protein Complexes
   Ziqi Gao^, Tao Feng^, Jiaxuan You, Chenyi Zi, Yan Zhou, Chen Zhang, Jia Li*
   ICLR 2024

6. SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
   Yang Liu^, Jiashun Cheng^, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li*, Yu Rong*
   ICLR 2024 Spotlight

7. GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction
   Amit Roy, Juan Shu, Jia Li, Carl Yang, Olivier Elshocht, Jeroen Smeets, Pan Li
   WSDM 2024

8. GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
   Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li*
   NeurIPS 2023

9. Deep Insights into Noisy Pseudo Labeling on Graph Data
   Botao Wang, Jia Li*, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung
   NeurIPS 2023

10. Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters
    Nuo Chen, Yan Wang*, Haiyun Jiang, Deng Cai, Yuhan Li, Ziyang Chen, Longyue Wang, Jia Li*
    EMNLP 2023 Findings

11. Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension
    Nuo Chen, Hongguang Li, Yinan Bao, Junqing He, Xinshi Lin, Qi Yang, Jianfeng Liu, Ruyi Gan, Jiaxing Zhang, Baoyuan Wang, Jia Li*
    EMNLP 2023 Findings

12. Nature Response Generation for Chinese Reading Comprehension
    Nuo Chen, Hongguang Li, Yinan Bao, Baoyuan Wang, Jia Li*
    EMNLP 2023 Findings

13. A Co-training Approach for Noisy Time Series Learning
    Weiqi Zhang, Jianfeng Zhang, Jia Li*, Fugee Tsung
    CIKM 2023

14. Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series  
    Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li*
    KDD 2023 

15. All in One: Multi-task Prompting for Graph Neural Networks  
    Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan
    KDD 2023 [Code] Best Paper Award

16. Alleviating Over-smoothing for Unsupervised Sentence Representation
    Nuo Chen, Linjun Shou, Jian Pei, Ming Gong, Bowen Cao, Jianhui Chang, Daxin Jiang, Jia Li*
    ACL 2023 

17. Structural Contrastive Pretraining for Cross-Lingual Comprehension
    Nuo Chen, Linjun Shou, Tengtao Song, Ming Gong, Jian Pei, Jianhui Chang, Daxin Jiang, Jia Li*
    ACL 2023 Findings

18. A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment
    Jianheng Tang, Kangfei Zhao, Jia Li*
    ACL 2023 Findings

19. Hierarchical Graph Learning for Protein-Protein Interaction
    Ziqi Gao, Chenran Jiang, Jiawen Zhang, Xiaosen Jiang, Lanqing Li, Peilin Zhao, Huanming Yang, Yong Huang*, Jia Li*
    Nature Communications 2023 [Editors’ Highlight] [DrugAI] [ScienceAI]

20. A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph data
    Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose Blanchet
    ICLR 2023

21. Knowledge Graph Completion with Counterfactual Augmentation
    Heng Chang, Jie Cai, Jia Li*
    WWW 2023

22. Self-Supervised Hypergraph Representation Learning for Sociological Analysis
    Xiangguo Sun, Hong Cheng, Bo Liu, Jia Li, Hongyang Chen, Guandong Xu, Hongzhi Yin
    TKDE 2023

23. Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
    Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Tingyang Xu, Peilin Zhao, Lanqing Li*, Fugee Tsung, Jia Li*
    AAAI 2023 Oral

24. Human Mobility Modeling During the COVID-19 Pandemic via Deep Graph Diffusion Infomax
    Yang Liu, Yu Rong, Zhuoning Guo, Nuo Chen, Tingyang Xu, Fugee Tsung, Jia Li*
    AAAI 2023

25. Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning
    Jiashun Cheng, Man Li, Jia Li*, Fugee Tsung
    AAAI 2023 [code] [news]

26. Decision Support System for Chronic Diseases Based on Drug-Drug Interactions
    Tian Bian, Yuli Jiang, Jia Li*, Tingyang Xu*, Yu Rong, Yi Su, Timothy Kwok, Helen Meng, Hong Cheng
    ICDE 2023

27. Robust Attributed Graph Alignment via Joint Structure Learning and Optimal Transport
    Jianheng Tang, Weiqi Zhang, Jiajin Li, Kangfei Zhao, Fugee Tsung, Jia Li*
    ICDE 2023 [code]

28. Semi-Supervised Hierarchical Graph Classification   
    Jia Li, Yongfeng Huang, Heng Chang, Yu Rong
    TPAMI 2022

29. Rethinking Graph Neural Networks for Anomaly Detection
    Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li*
    ICML 2022 [code] [news]

30. Deconvolutional Networks on Graph Data
    Jia Li, Jiajin Li, Yang Liu, Jianwei Yu, Yueting Li, Hong Cheng
    NeurIPS 2021 [video][code] 

31. Mask-GVAE: Blind Denoising Graphs via Partition
    Jia Li, Mengzhou Liu, Honglei Zhang, Pengyun Wang, Yong Wen, Lujia Pan, Hong Cheng
    WWW 2021 [code]

32. Dirichlet Graph Variational Autoencoder
    Jia Li, Jianwei Yu, Jiajin Li,Honglei Zhang, Kangfei Zhao, Yu Rong, Hong Cheng, Junzhou Huang
    NeurIPS 2020 [code]

33. Adversarial Attack on Community Detection by Hiding Individuals
    Jia Li, Honglei Zhang, Zhichao Han, Yu Rong, Hong Cheng, Junzhou Huang
    WWW 2020 Oral [code]

34. Predicting Path Failure In Time-Evolving Graphs
    Jia Li, Zhichao Han, Hong Cheng, Jiao Su, Pengyun Wang, Jianfeng Zhang, Lujia Pan
    KDD 2019 Oral [code] [video] 

35. Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
    Jia Li, Yu Rong, Hong Cheng, Helen Meng, Wenbing Huang, Junzhou Huang
    WWW 2019 [pytorch] [tensorflow]

36. TATC: Predicting Alzheimers Disease with Actigraphy Data
    Jia Li, Yu Rong, Helen Meng, Zhihui Lu, Timothy Kwok, Hong Cheng
    KDD 2018 Oral [talk] [video] 

Work Experiences

• Assistant Professor, Hong Kong University of Science and Technology, starting from Aug. 2021

• Senior Data Mining Engineer, Tencent, Shenzhen, 2014-2017

• Fraud Detection System Programmer, China Mobile, Shenzhen, 2010-2013

Supervision

• Jianheng Tang (PhD student since 2021 Fall, DSA Excellent Research Award 2023)

• Yang Liu (PhD student since 2021 Fall)

• Ziqi Gao (PhD student since 2022 Spring, HKUST IPO Best Research Award 2022/23)

• Nuo Chen (PhD student since 2022 Fall, DSA Merit Research Award 2023)

• Jiawen Zhang (PhD student since 2022 Fall)

• Yifan Niu (PhD student since 2022 Fall)

• Haihong Zhao (PhD student since 2023 Fall)

• Yuhan Li (PhD student since 2023 Fall)

• Bing Tong (PhD student since 2023 Fall)

• Aochuan Chen (PhD student since 2024 Spring)

sERVICES

Senior Area Chair for ACL 2024

Registration Chair for VLDB 2024

PC member or Reviewer for WWW, KDD, ICML, NeurIPS, ICLR, ICDE, TKDE, CIKM, TPAMI, WSDM, Nature Communications