Thao Le

My name is Thao. I am a PhD Candidate in Explainable AI (XAI) in School of Computing and Information Systems, The University of Melbourne, advised by Prof Tim Miller (primary supervisor), Prof Liz Sonenberg and Dr Ronal Singh. My research interests lie at the intersection of artificial intelligence (AI) and cognitive science.

My PhD project applies explainable AI techniques to explain the uncertainty of machine learning models. In doing so, we aim to promote trust, improve understanding and improve decision-making for users. I apply mixed methods in my research by using machine learning techniques, running human-subject experiments and doing qualitative/quantitative data analysis.

Research Interests

  • Explainable AI
  • Decision making
  • Human-AI Interaction
Selected Awards
  • Google Conference Grant (2023)
  • Melbourne Centre for Data Science (MCDS) Top Up Scholarship (2022)
  • Melbourne Research Scholarship: Full fee offset and stipend
  • Second Prize - Electronic Trading Competition - Jane Street Capital (2019)


Dec, 2022 Present my research at AJCAI 2022 Doctoral Consortium in Perth
Nov, 2022 A paper has been accepted to AAAI Main Track. Preprint coming soon.
Oct, 2022 My application to AAAI Doctoral Consortium 2023 has been accepted.
Jul, 2022 Selected as a Doctoral Academy Fellow at Melbourne Centre for Data Science (MCDS) and received a top-up scholarship
Jun, 2022 Our paper Improving Model Understanding and Trust with Counterfactual Explanations of Model Confidence has been accepted to IJCAI 2022 Workshop on Explainable Artificial Intelligence (XAI)
Apr, 2022 Received an invite to present our paper JAIR at IJCAI-ECAI 2022 Journal Track
Aug, 2021 Our paper Goal Recognition for Deceptive Human Agents through Planning and Gaze was published in Journal of Artificial Intelligence Research (JAIR)