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• Biography/ Background

  Dr. Tony Weitong Chen is an ARC EC Industry Fellow, a senior lecturer at the University of Adelaide (UoA) and a researcher at the Australian Institute for Machine Learning (AIML), having previously served as an Associate Lecturer and Post-Doc Research Fellow at the University of Queensland. He earned his PhD from the University of Queensland in 2020, after completing both his Master's and Bachelor's degrees at the University of Queensland and at Griffith University respectively. His research primarily focuses on machine learning, with a special interest in its application to medical data. Dr. Chen is known for his extensive collaborative efforts with professionals in academia, industry, government, and professional bodies, and various internal and external grants have supported his research.

• Qualifications

  Ph.D. of Computer Science	The University of Queensland	Australia	2017 - 2020
  Master of Computer Science	The University of Queensland	Australia	2011 - 2013
  Bachelor of Information System	Griffith University	Australia	2009 - 2011

• Awards & Achievements

  2023	Early Career Research Excellence Award, The University of Adelaide	Australia
  2023	Outstanding Service Award, The 36th Australasian Joint Conference on Artificial Intelligence	Australia
  2022	Best Student Paper Award, APWEB-WAIM 2022	China
  2022	Best Poster Award, The 34th Australasian Joint Conference on Artificial Intelligence	Australia
  2021	Best Presentation Award, 17th International Conference on Advanced Data Mining and Applications	Australia
  2021	Best Paper - Highly Commended Award, Australasian Computer Science Week Multiconference	New Zealand
  2019	Best Student Paper Award, 15th nternational Conference on Advanced Data Mining and Applications	China
  2018	Student Travel Grant, International Conference on Data Mining 2018	Singapore
  2016	Outstanding Service Award, 12th International Conference on Advanced Data Mining and Applications	Australia
  2014	1st Place, Premier‘s Awards for Open Data	Australia
  2014	1st Place, Microsoft Startup Q Award for Open Data	Australia

• Research Funding

  ·       ARC ECR Industry Fellowship 2024 - 2026 Future of Work: Achieving Efficiency and Productivity through Optimisation (ARC & SA PAthology)

  ·       ARC LP - Principal Investigator 2025 - 2027 Advanced Data Analytics for Cost-effective Mushroom Cultivation (ARC & CLEVER MUSHROOMS PTY LTD; PIXELFORCE SYSTEMS PTY LTD; HOKKEN CO., LTD)

  ·       ARC DP - Principal Investigator 2024 - 2026 Towards knowledge discovery from imperfect and evolving data (ARC)

  ·       UoA Sustainability FAME Strategy  Grant 2023 - Investigator 2023 - 2023 Sustainable Warriors or Marketing Mirage? (UoA)

  ·       UoA CMS Research Grants 2023 - 2023 

  ·       ANA Partnership Fund- Principal Investigator 2023 - 2023 AID-MI: Artificial Intelligence Based Diagnosis Using Multimodal Information For Cardiopulmonary Disease (UoA & UoN)

  ·       UoA START-UP GRANT - Principal Investigator 2022 - 2024 

  ·       UQ AI-ECR Research Fund - Principal Investigator 2022 - 2022 Towards Positive Emotion: Artificial Intelligence-Based Expression Rephrasing (UQ) 

  ·       UQ Cyber Security Seed Fund - Principal Investigator 2022 - 2022 Collaborated Learning with Medical Data Making High-Stake Decision Without Information Leakage (UQ & RBWH) 

  ·       UQ AI Initiative - Investigator 2021 - 2022 AI Monitored ICU Illness Severity Prediction (UQ & RBWH)

  ·       ITEE Research Support Fund - Principal Investigator 2021 - 2021   Multi-Task Memory-Fused RNNs for Explainable Illness Severity Prediction (UQ)

• Professional Interests

  Machine Learning    Weakly Supervised Learning, Deep Learning, Multi-task Learning, Collaborative Learning

  Data Analytics          Data Analytics, Medical Knowledge Graph Mining, Sentiment Analysis on Socia Media

• Community Engagement

  Early to Mid-Career Researchers Representative at SAT UoA

  Early to Mid-Career Researchers Representative at UQ

Entry last updated: Friday, 20 Sep 2024

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