Dr Gobert Lee

Lecturer in Statistical Science

College of Science and Engineering

place Tonsley Building (4.10)
GPO Box 2100, Adelaide 5001, South Australia

Gobert Lee received her PhD in Statistical Image Analysis from Flinders University, Australia, in 2004. In 2005-2007, she was awarded a JSPS Postdoctoral Fellowship in Japan. In 2007-2009, she was a researcher associate in the Department of Intelligent Image Information at the Graduate School of Medicine, Gifu University, developing computer-aided diagnosis (CAD) algorithms for a range of diseases such as breast cancer and liver cirrhosis. Since 2009, she has joined Flinders University as a lecturer and a researcher and has been a member of the Medical Device Research Institute at Flinders University. Her research interests include medical image analysis and segmentation, machine learning and deep learning, digital pathology, and statistical issues relating to machine learning and medical imaging.

Qualifications

PhD, Flinders University, Australia

Honours, awards and grants
  • Channel 7 Children Research Foundation Grant, 2022
  • Freemason's Centre for Male Health and Wellbeing Grant, 2021-2022
  • NeuroSurgical Research Foundation Grant, 2020-2021
  • Australian Mathematical Society, WIMSIG Cheryl E Praeger Award, 2019
  • Australian Mathematical Society, WIMSIG Cheryl E Praeger Award, 2017
  • Faculty of Science and Engineering Reinventing Teaching and Learning Grant, 2016
  • Channel 7 Children's Research Foundation Grant, 2012-2014
  • Flinders Establishment Grant 2011-2013
  • Lyn Wrigley Breast Cancer Research & Development Fund, Breast Cancer Research Grant, 2011
Key responsibilities
Topic coordinator
STAT1121 Data Science
STAT8721 Data Science (GE)
STAT3701 Statistical Science
STAT1132 Statistical Analysis
STAT9701 Statistical Science GE
STAT8132 Statistical Analysis GE
Topic lecturer
STAT1121 Data Science
STAT8721 Data Science (GE)
STAT3701 Statistical Science
STAT9701 Statistical Science GE
STAT1132 Statistical Analysis
STAT8721 Data Science GE
Supervisory interests
Artificial intelligence and image processing
Biomedical engineering
Data science
Machine learning
Medical image analysis