Shirui Pan

Shirui Pan

Professor and ARC Future Fellow

School of ICT

Griffith University

Biography

Shirui Pan is a Professor and an ARC Future Fellow with the School of Information and Communication Technology, Griffith University, Australia. Before joining Griffith in August, 2022, he was with the Faculty of Information Technology, Monash University between Feb 2019 and July 2022. He received his Ph.D degree in computer science from University of Technology Sydney (UTS), Australia.

Shirui has made contributions to advance graph machine learning methods for solving hard AI problems for real-life applications, including graph classification, anomaly detection, recommender systems, and multivariate time series forecasting. His research has been published in top conferences and journals including NeurIPS, ICML, KDD, TPAMI, TNNLS, and TKDE. He is recognised as one of the AI 2000 AAAI/IJCAI Most Influential Scholars in Australia (2021, 2022), and one of the World’s Top 2% Scientists (2021). His research received the IEEE ICDM Best Student Paper Award (2020), and the JCDL Best Paper Honorable Mention Award (2020). He has eight papers recognised as the Most Influential Papers in KDD (x1), IJCAI (x5), AAAI (x1), and CIKM (x1) (Feb 2022). He received a prestigious Future Fellowship (2022-2025), one of the most competitive grants from the Australian Research Council (ARC).

潘世瑞(中文简介)

博士招生信息(2022年6月更新)

PhD positions are open! I am looking for self-motivated Ph.D students. See more information here.

Interests
  • Artificial Intelligence
  • Data Mining
  • Machine Learning
  • Deep Learning
  • NLP
  • Graph Neural Networks
  • Trustworthy AI
Education
  • PhD in Computer Science

    University of Technology Sydney

What’s New

Recent Publications

IEEE TPAMI, TNNLS, TKDE, TCYB; ICML, NeurIPS, KDD, WWW, CVPR, WSDM, ICDM, AAAI, IJCAI

(2022). Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs. 2022 Conference on Neural Information Processing Systems, NeurIPS-22, New Orleans, Louisiana, United States, November 28 - December 9, 2022 (CORE A*).

(2022). Pseudo-Riemannian Graph Convolutional Networks. 2022 Conference on Neural Information Processing Systems, NeurIPS-22, New Orleans, Louisiana, United States, November 28 - December 9, 2022 (CORE A*).

(2022). Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination. 2022 Conference on Neural Information Processing Systems, NeurIPS-22, New Orleans, Louisiana, United States, November 28 - December 9, 2022 (CORE A*).

(2022). A Dynamic Variational Framework for Open-World Node Classification in Structured Sequences. 22nd IEEE International Conference on Data Mining, ICDM-22, Orlando, FL, United States, November 28 - December 1, 2022 (CORE A*).

(2022). Multi-Relational Graph Neural Architecture Search with Fine-grained Message Passing. 22nd IEEE International Conference on Data Mining, ICDM-22, Orlando, FL, United States, November 28 - December 1, 2022 (CORE A*).

(2022). Unifying Graph Contrastive Learning with Flexible Contextual Scopes. 22nd IEEE International Conference on Data Mining, ICDM-22, Orlando, FL, United States, November 28 - December 1, 2022 (CORE A*).

Team Leader

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Shirui Pan

Professor and ARC Future Fellow

PhD Students

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Bo Xiong

PhD Student @ Universität Stuttgart (09/2020-)

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Ming Jin

PhD Student @ Monash (08/2020-)

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Yizhen Zheng

PhD Student @ Monash (07/2021-)

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Xin Zheng

PhD Students @ Monash (04/2021-)

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Huan Yee Koh

PhD Student @ Monash (04/2022-)

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Yixin Liu

PhD Student @ Monash (01/2021-)

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Luzhi Wang

PhD Student @ Tianjin U. (07/2020-)

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Dongran Yu

PhD Student @ Jili (09/2019-)

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Mingjie Li

PhD Student @ Monash (11/2019-)

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Bang Wu

PhD Student @ Monash (08/2020-)

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Dongwon Ryu

PhD Student @ Monash (02/2021-)

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Man Wu

PhD Student @ FAU (2020-)

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Sheng Wan

PhD Student @ NUST

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He Zhang

PhD Student @ Monash (04/2021-)

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Chaojie Ji

PhD Student @ Monash (08/2022-)

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Guangsi Shi

PhD Student @ Monash (07/2020-)

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Linhao Luo

MPhil Student @ Monash (02/2022-)

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Mohit Gupta

PhD Student @ Monash (01/2022-)

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Yuanzhe Zhang

PhD Student @ Monash (06/2021-)

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Zahra Zamanzadeh

PhD Student @ Monash (01/2022)

Alumni

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Shichao Zhu

AI Scientist @ ByteDance

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Miao Zhang

Assistant Professor @ Aalborg University

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Hong Yang

Associate Professor @ Guangzhou University

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Chun Wang

Assistant Professor @ City University of Macau

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Ruiqi Hu

CEO

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Shaoxiong Ji

PhD Student @ Aalto U.

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Guojia Wan

Postdoc @ Wuhan U.

Awards and Grants

Shirui Pan’s research was supported by Australian Research Council (ARC), Defence Science and Technology Group (DSTG), Amazon, Metso Outotec, Shanghai Aircraft Manufacturing Co, Ltd, etc.

  • [Award]: Amazon Research Awards (APA) Fall 2021 round.

  • [Award]: AI 2000 AAAI/IJCAI Most Influential Scholars Honorable Mention (2022) (only three recipients in Australia) (25/01/2021).

  • [Award]: Enabling Automatic Graph Learning Pipelines with Limited Human Knowledge ($800,000 from ARC and $470,000 from Monash University) - 2021-2025

    • ARC Future Fellow
    • Australian Research Council (ARC)
  • [Award]: 5 Papers are Selected as Most Influential Papers in IJCAI (02/2022).

    • 2021 Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning, Ming Jin et al (Rank: 12)
    • 2019 Graph WaveNet For Deep Spatial-Temporal Graph Modeling, Zonghan Wu et al (Rank: 1)
    • 2019 Attributed Graph Clustering: A Deep Attentional Embedding Approach, Chun Wang et al (Rank: 9)
    • 2018 Adversarially Regularized Graph Autoencoder For Graph Embedding, Shirui Pan et al (Rank: 4)
    • 2016 Tri-Party Deep Network Representation, IJCAI-2016, Shirui Pan et al (Rank: 6)
  • [Award]: 1 Paper is Selected as Most Influential Paper in KDD (02/2022).

    • 2020 Connecting The Dots: Multivariate Time Series Forecasting With Graph Neural Networks, Zonghan Wu et al (Rank: 4)
  • [Award]: 1 Paper is Selected as Most Influential Paper in AAAI (02/2022).

    • 2018 DiSAN: Directional Self-Attention Network For RNN/CNN-Free Language Understanding, Tao Shen et al (Rank: 11)
  • [Award]: 1 Paper is Selected as Most Influential Paper in CIKM (02/2022).

    • 2017 MGAE: Marginalized Graph Autoencoder For Graph Clustering, CIKM-2017, Chun Wang et al (Rank: 9)
  • [Award]: 2021 FIT Dean’s Award for Excellence in Research by an Early Career Researcher

  • [Award]: AI 2000 AAAI/IJCAI Most Influential Scholars Honorable Mention (2021) (only five recipients in Australia) (08/04/2021).

  • Best Student Paper Award for ICDM-2020 (CORE A* conference)

  • The Vannevar Bush Best Paper Honorable Mention for JCDL-2020 (CORE-2018 A* conference)

  • Anomaly Detection in Social Networks ($11,000) - 2019-2020

    • Faculty Early Career Researcher Grant
    • Monash University
  • Cyberbullying Detection on Social Networks ($20,000) - 2016-2017

    • UTS Early Career Researcher Grant (UTS - ECRG)
    • University of Technology Sydney

Professional Services

Editorship

  • Guest Editor for Special Issue: Pattern Recognition (2022)
  • Guest Editor for Special Issue: IEEE Transactions on Neural Networks and Learning Systems (2021)
  • Guest Editor for Special Issue: Future Generation Computer Systems (2020)
  • Guest Editor for Special Issue: Neurocomputing (2020)
  • Guest Editor for Special Issue: Complexity (2019)
  • Associate Editor: IEEE Access (2018-2019)

Conference Organisation

  • Proceeding Co-chair: 2022 IEEE International Conference on Data Mining(ADMA-2022)
  • Tutorial Chair: 2022 IEEE International Conference on Data Mining(ICDM-2022)
  • Program Chair: 2021 International Conference on Data Science and Systems (DSS-2021)
  • Workshop Chair: 2021 IEEE International Conference on Big Data (IEEE BigData-2021)
  • Tutorial Chair: 2020 Digital Image Computing: Techniques and Applications (DICTA-2020)
  • Special Session Chair: Learning from Big Graph Data: Theory and Applications, IJCNN-2018 (CORE A)
  • Special Session Chair: Advanced Data Analytics for Large-scale Complex Data Environment, IJCNN- 2017 (CORE A)
  • Special Session Chair: Advanced Machine Learning Methods and Applications from Complicated Data Environment, IJCNN-2016 (CORE A)

Journal Reviewer

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (CORE A*)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (CORE A*)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)((CORE A*)
  • IEEE Transactions on Cybernetics (TCYB) (CORE A)
  • IEEE Transactions on Systems, Man and Cybernetics: Systems (SMCA) (CORE B)
  • IEEE Signal Processing Letters
  • ACM Transactions on Intelligent Systems and Technology (TIST)
  • World Wide Web (WWW) (CORE A)
  • Social Network Analysis and Mining
  • Neural Computing and Applications
  • Neurocomputing
  • Information Sciences (CORE A)

(Senior) Program Committee

  • The International Conference on Learning Representations (ICLR 23-21)
  • Annual Conference on Neural Information Processing Systems (NeurIPS 22-19) (CORE A*)
  • SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 22-19) (CORE A*)
  • Conference on Computer Vision and Pattern Recognition (CVPR 22-21) (CORE A*)
  • IEEE International Conference on Data Mining (ICDM 22-19) (CORE A*)
  • AAAI Conference on Artificial Intelligence (AAAI 23-17) (CORE A*)
  • The Web Conference (WWW 23-19) (CORE A*)
  • International Joint Conference on Artificial Intelligence (IJCAI 22-17) (CORE A*)
  • SIAM International Conference on Data Mining (SDM-19) (CORE A)
  • Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-19,18,17,16)(CORE A)
  • IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014-15)
  • International Conference on Advanced Data Mining and Applications (ADMA 2014, 2016)
  • The international conference on Advances in Social Network Analysis and Mining (ASONAM 2017)
  • The China Computer FedCOREtion (CCF) Conference on Big Data (CCF Big Data 2017)

Recent & Upcoming Talks

Source Codes

Curated List

A list of open source code is maintained on Github. Other source code will be released as it is ready for publishing.

Graph Classification

Teaching

  • FIT5196: Data Wrangling, Lecturer, 2019 S1, Monash University
  • FIT5196: Data Wrangling, Lecturer, 2020 S2, Monash University
  • FIT5196: Data Wrangling, Chief Examiner & Lecturer, 2021 S2, Monash University
  • FIT5212: Data Analysis for Semi-Structured Data, Co-Chief Examiner & Lecturer, 2020 S1, Monash University
  • FIT5212: Data Analysis for Semi-Structured Data, Co-Chief Examiner & Lecturer, 2021 S1, Monash University

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