Research Interests. I develop graph machine learning (GML) techniques, with a focus on but not limited to graph neural networks (GNNs), graph foundation models (GFMs), neuro-symbolic GML and trustworthy GML.

1. Accelerate electronic design automation (EDA) tasks by leveraging GML techniques.
2. Develop open-source GML tools to support applications in EDA.
3. Develop large circuit models (LCMs).

Research Keywords: Graph machine learning, AI for EDA.

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Recent Publications

See my Google Scholar for the full publication list. ^†Equal contribution; ^♠Corresponding author

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Preprints & Working Papers

• Towards Graph Foundation Models: A Survey and Beyond.
  Jiawei Liu^†, Cheng Yang^†, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi^♠.
  Preprint

Journal Papers

• Heterogeneous Spatio-temporal Graph Contrastive Learning for Point-of-Interest Recommendation.
  Jiawei Liu, Haihan Gao, Cheng Yang, Chuan Shi^♠, Tianchi Yang, Hongtao Cheng, Qianlong Xie, Xingxing Wang, Dong Wang.
  Tsinghua Science and Technology, 2024.
• Self-Supervised Spatio-Temporal Graph Learning for Point-of-Interest Recommendation.
  Jiawei Liu, Haihan Gao, Chuan Shi^♠, Hongtao Cheng, Qianlong Xie.
  Applied Sciences, 2023.
• A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources.
  Jiawei Liu, Chuan Shi^♠, Cheng Yang, Zhiyuan Lu, Philip S.Yu.
  AI Open, 2022.
• 基于异质信息网络的推荐系统研究综述.
  刘佳玮, 石川^♠, 杨成, 菲利普·俞.
  信息安全学报, 2021.

Conference Papers

• PGAU: Static IR Drop Analysis for Power Grid using Attention U-Net Architecture and Label Distribution Smoothing.
  Feng Guo^†, Jiawei Liu^†, Jianwang Zhai^♠, Jingyu Jia, Kang Zhao, Chuan Shi^♠.
  GLSVLSI, 2024.
• SATGL: an Open-source Graph Learning Toolkit for Boolean Satisfiability.
  Hongtao Cheng^†, Jiawei Liu^†, Jianwang Zhai, Mingyu Zhao, Cheng Yang, Chuan Shi^♠.
  ISEDA, 2024.
• Endowing Pre-trained Graph Models with Provable Fairness.
  Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi^♠.
  WWW, 2024.
• Abnormal Event Detection via Hypergraph Contrastive Learning.
  Bo Yan, Cheng Yang, Chuan Shi^♠, Jiawei Liu, Xiaochen Wang.
  SDM, 2023.
• Learning to Distill Graph Neural Networks.
  Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi^♠, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin.
  WSDM, 2023.
• Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework.
  Cheng Yang, Jiawei Liu, Chuan Shi^♠.
  WWW, 2021.
• Decorrelated Clustering with Data Selection Bias.
  Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi^♠, Jiawei Liu, Bai Wang.
  IJCAI, 2020.

Book Chapters

• Chapter 7: Distilling Graph Neural Networks.
  In: Advances in Graph Neural Networks. Springer. 978-3-031-16173-5. 2022.
  Preprint
• Chapter 3: Structure-preserved Heterogeneous Graph Representation.
  In: Heterogeneous Graph Representation Learning and Applications. Springer. 978-981-16-6166-2. 2022.
  Preprint

Awards

- 2023年北邮GAMMA Lab服务卓越奖、项目优秀奖、学术优秀奖, 2024.1

- 第五届集成电路EDA设计精英挑战赛总决赛一等奖、行芯企业特别奖, 2023.12

- 2022年北邮GAMMA Lab项目卓越奖、服务优秀奖、学术贡献奖, 2023.1

- 北京邮电大学计算机学院优秀研究生, 2021.12

- 2021年北邮GAMMA Lab服务优秀奖、学术优秀奖, 2021.12

- 北京邮电大学计算机学院"助顺邮我"科技扶贫团队重要贡献个人, 2021.3

- 2020年北邮GAMMA Lab服务优秀奖、学术贡献奖, 2020.12

- 北京市优秀毕业生、北京邮电大学优秀毕业生, 2020.6

- 2019年北邮DMGroup服务贡献奖、学术贡献奖, 2020.1

- 2018-2019学年北京邮电大学校级三好学生、优秀团员, 2019.12

- 美国大学生数学建模竞赛H奖, 2019.4

- 2019年北京邮电大学寒假大学生回母校宣传活动优秀个人, 2019.4

- 2017-2018学年北京邮电大学校级三好学生、优秀团员, 2018.12

- 全国大学生数学建模竞赛全国二等奖, 2018.10

- 2018高校校园大数据竞赛优胜奖, 2018.6

- 北京邮电大学程序设计竞赛银奖, 2018.4

- 2016-2017学年北京邮电大学校级三好学生、优秀团员, 2017.12

- 河北省大学生程序设计竞赛一等奖, 2017.10