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Personal profile

Biography

Shirui Pan is currently an ARC Future Fellow and a Senior Lecturer with the Faculty of Information Technology, Monash University, 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. 

Shirui is recognised as one of the AI 2000 AAAI/IJCAI Most Influential Scholars in Australia (2021). He is an awardee of a prestigious Future Fellowship (2021-2025), one of the most competitive grants from the Australian Research Council (ARC).

Research interests

Dr Pan's research interests include

  • data mining
  • machine learning
  • deep learning
  • graph and network analytics
  • NLP

To date, Dr Pan has published over 100 research papers in top-tier journals and conferences, including the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Cybernetics (TCYB), NeurIPS, KDD, ICML, WWW, CVPR, ICDE, AAAI, IJCAI, ICDM, SDM, PAKDD.

More information about his research can be found at https://shiruipan.github.io/.

Monash teaching commitment

Dr Pan is the Director of Master of AI at Monash since 2022.

Dr Pan lectured the following unit(s) at Monash University

  • FIT5196 Data Wrangling
  • FIT5212 Data Analysis for Semi-structured Data

 

Community service

Dr Pan regularly serves as an Associate Editor, Session Chair, Invited Reviewer, Program Committee Member for a number of journals and conferences. His professional services include:

Editorship

  • Guest Editor: IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • Guest Editor: Future Generation Computing Systems
  • Guest Editor: Complexity 
  • Guest Editor: Neurocomputing

Conference Organisation

  • 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)
  • Pattern Recognition (PR) (CORE A*)
  • Information Sciences (CORE A)
  • 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

Program Committee

  • Annual Conference on Neural Information Processing Systems (NeurIPS 20,19)(CORE A*)
  • SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-20,19)(CORE A*)
  • The Web Conference (WWW-20,19)(CORE A*)
  • AAAI Conference on Artificial Intelligence (AAAI-20,19,18,17) (CORE A*)
  • International Joint Conference on Artificial Intelligence (IJCAI-20, 19, 18,17) (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 Federation (CCF) Conference on Big Data (CCF Big Data 2017)

Research area keywords

  • Data Mining
  • Machine Learning
  • Deep Learning
  • Artificial intelligence
  • Network Analysis
  • Graph embedding
  • Natural Language Processing

Network

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