Javen Shi

Professor Javen Shi

Professor Probabilistic Graphical Model Group

School of Computer Science

Faculty of Engineering, Computer and Mathematical Sciences

Eligible to supervise Masters and PhD - email supervisor to discuss availability.


Professor Javen Shi is the Founding Director of Probabilistic Graphical Model Group at the University of Adelaide, Director in Advanced Releasing and Learning of Australian Institute for Machine Learning (AIML), and the Chief Scientist of Smarter Regions. He is a leader in machine learning in both high-end AI research and also real world applications with high impacts.

He is recognised both locally and internationally for the impact of his work, through an impressive record of publishing in the highest ranked venue in the field of Computer Vision & Pattern Recognition (22 CVPR papers), through an impeccable record of ARC funding (including his DECRA, 2 DP as 1st CI, 4 LP as Co-CI). He has published over 80 peer reviewed papers, over 80% are at ERA [A/A*]. He has over 5000 Google Scholar citations with h-index 31. Google Scholar ranks him 7th globally in Probabilistic Graphical Models, and 3rd globally in Counterfactuals.

He has transferred his research to diverse industries including agriculture, mining, sport, manufacturing, bushfire, water utility, health and education. Recent awards include:

1) 2nd place from a global mining competition OZ Minerals Explorer Challenge 2019 (over 1000 participants from 62 countries);

2) Golden prize (1st place) from Volkswagen in 2019 (digital factory powered by AI);

3) Finalist of SA Department of Energy and Mining’s Gawler Challenge 2020 (over 2k participants from 100+ countries) with his team’s work being considered as “The most innovative modelling” by the judge panel;

4) the top winning team (in collaboration with USC and CSIRO) in AUS/NZ Bushfire Data Quest 2020 using AI to predict fire scar and spread.  

He has initiated Smarter Regions CRC bid to empower regional Australia to gain the maximum benefit from the AI revolution and to transform existing industries and grow a technology sector in and for regional Australia.

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  • Appointments

    Date Position Institution name
    2020 Professor University of Adelaide
    2018 - 2019 Associate Professor University of Adelaide
    2015 - 2017 Senior Lecturer University of Adelaide
    2012 - 2014 ARC DECRA fellow University of Adelaide
    2010 - 2011 Senior Research Associate University of Adelaide
  • Awards and Achievements

    Date Type Title Institution Name Country Amount
    2012 Award ARC Discovery Early Career Researcher Award ARC Australia
  • Language Competencies

    Language Competency
    Chinese (Mandarin) Can read, write, speak, understand spoken and peer review
    English Can read, write, speak, understand spoken and peer review
  • Education

    Date Institution name Country Title
    2006 - 2010 Australian National University, Canberra Australia PhD
    2003 - 2006 Northwestern Polytechnical University, Xi'an China Master
    1999 - 2003 Northwestern Polytechnical University, Xi'an China Bachelor
  • Research Interests

Grants Summary

  • Total Australian Research Council (ARC) funding awarded: $2.8 M 
    • Lead (1st) Chief Investigator (CI) (2 DPs, 1 DECRA): $1M 
    • Co-CI (4 LPs): $1.7M
  • Other funding (RDCs, Industry, ...): ~$5M

ARC Grants

  • ARC Linkage Grant 2021-2024, 3rd Chief Investigator (CI), and Machine Learning Lead 
    A Machine Learning driven flow modelling of fragmented rocks in cave mining

 

  • ARC Discovery Project Grant 2016-2019, 1st Chief Investigator (CI) 
    Probabilistic Graphical Models For Interventional Queries
  • ARC Linkage Project Grant 2014-2017, 2nd CI 
    Sentient Buildings
  • ARC Discovery Project Grant 2014-2016, 1st CI 
    Online Learning for Large Scale Structured Data in Complex Situations
  • ARC Linkage Grant 2013-2016, 4th CI 
    Semantic change detection through large-scale learning
  • ARC Linkage Grant 2012-2015, 3rd CI 
    Scalable classification for massive datasets: randomized algorithms
  • ARC DECRA fellowship, 2012-2014, Sole CI 
    Compressive Sensing Based Probabilistic Graphical Models

University Courses 

AI, DL, ISML, MBD, ...

 

 

Tutorials 

Probabilistic Graphical Models

  1. Representation [ pdf], ACVT, UoA, April 15, 2011 

     

  2. Inference [ pdf], ACVT, UoA, May 6, 2011 

     

  3. Learning [ pdf], ACVT, UoA, May 27, 2011 

     

  4. Sampling-based approximate inference [ pdf], ACVT, UoA, June 10, 2011 

     

  5. Temporal models [ pdf], ACVT, UoA, August 12, 2011 

     

Generalisation Bounds

  1. Basics [ pdf], ACVT, UoA, April 13, 2012 

     

  2. VC dimensions and bounds [ pdf], ACVT, UoA, April 27, 2012 

     

  3. Rademacher complexity and bounds [ pdf], ACVT, UoA, August 17, 2012 

     

  4. PAC Bayesian Bounds, [ pdf], ACVT, UoA, August 31, 2012 

     

  5. Regret bounds for online learning, [ pdf], ACVT, UoA, Nov. 2, 2012 

     

Please email me if you find errors or typos in the slides.

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  • Current Higher Degree by Research Supervision (University of Adelaide)

    Date Role Research Topic Program Degree Type Student Load Student Name
    2021 Principal Supervisor Research on lightweight intelligent models based on deep learning: incorporating artificial intelligence on end devices Doctor of Philosophy Doctorate Full Time Ms Hongrong Cheng
    2020 Principal Supervisor End-To-End semi-supervised text classification with automated text augmentation and character attention Master of Philosophy Master Full Time Mr Adrian John Orenstein
    2019 Principal Supervisor Machine Learning and Natural Language Processing in Stock Prediction Doctor of Philosophy Doctorate Full Time Mr Jinan Zou
    2019 Principal Supervisor Visual Navigation in Embodied Autonomous Agents Doctor of Philosophy Doctorate Full Time Mr Mahdi Kazemi Moghaddam
    2018 Principal Supervisor Development of Goal-Oriented Dialogue Systems via Deep Neural Networks Doctor of Philosophy Doctorate Full Time Mr Amin Parvaneh
    2018 Co-Supervisor Social Human Activity Recognition and Localization in Video Sequences Doctor of Philosophy Doctorate Full Time Ms Mahsa Ehsanpour
    2017 Principal Supervisor Social network analysis using statistical machine learning Doctor of Philosophy Doctorate Part Time Mrs Iman Fahmy Shoaib
    2016 Principal Supervisor Markov Logic Networks. Generalisations and Applications Doctor of Philosophy Doctorate Part Time Mr Xian Wang
  • Past Higher Degree by Research Supervision (University of Adelaide)

    Date Role Research Topic Program Degree Type Student Load Student Name
    2017 - 2020 Co-Supervisor Deep Learning Methods for Human Activity Recognition using Wearables Doctor of Philosophy Doctorate Full Time Mr Alireza Abedin Varamin
    2015 - 2018 Principal Supervisor Adaptive Markov Random Fields for Structured Compressive Sensing Doctor of Philosophy Doctorate Full Time Miss Suwichaya Suwanwimolkul
    2014 - 2019 Principal Supervisor Joint Appearance and Motion Model for Multi-class Multi-object Tracking Doctor of Philosophy Doctorate Full Time Mr Chongyu Liu
    2014 - 2016 Co-Supervisor Deep Learning for Multi-label Scene Classification Master of Philosophy Master Full Time Mr Junjie Zhang
    2012 - 2014 Co-Supervisor Markov Random Fields with Unknown Heterogeneous Graphs Doctor of Philosophy Doctorate Full Time Mr Zhenhua Wang
  • Position: Professor Probabilistic Graphical Model Group
  • Phone: 83130324
  • Email: javen.shi@adelaide.edu.au
  • Fax: 8313 4366
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 1
  • Room: 1.06.A
  • Org Unit: Australian Institute for Machine Learning

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