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Short Biography

I am a Senior Lecturer at the College of Sciene and Engineering, James Cook University and an Honorary Research Fellow at the School of Computer Science, The University of Sydney. Prior to this, I was a postdoctoral research fellow at the Biomedical Multimedia Information Technology (BMIT) group, School of Computer Science, The Unviersity of Sydney. I obtained my PhD degree in Computer Science (medical image analysis) from The University of Sydney in 2020 under the supervision of Dr. Ashnil Kumar, Prof. David Feng, and Prof. Jinman Kim. I received B. IT degree from The University of Newcastle, Australia, 2009 and M. IT (2014) and MPhil (2016) degree from The University of Sydney.

I was an IT Consultant at the ECNESOFT, in Australia between 2010 to 2016.

I was born in , raised in (finished up to high school) and educated in (Uni).

Research Areas

Deep Learning, Machine Learning, Data Science, Medical Image Analysis, Health Informatics, Telehealth

My research focus is on the development of unsupervised deep learning models for medical image analysis, for improving image segmentation, retrieval, quantification and classification without relying on labelled data.

I also work at the coalface of translational health technology researches, e.g., health data analytics and telehealth.

I am always looking for highly-motivated undergraduate (Honours) and postgraduate students (MPhil and PhD). Please send me your CV and transcripts.

Selected Publications

A. Saha et al., "Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study", The Lancet Oncology, 2024. (IF=51.1) [paper]

H. Wang, E. Ahn and J. Kim, "A multi-resolution self-supervised learning framework for semantic segmentation in histopathology", Pattern Recognition, 2024. (IF=8) [paper][code]

T. Napier, E. Ahn, S. Allen-Ankins, L. Schwarzkopf and I. Lee, "Advancements in preprocessing, detection and classification techniques for ecoacoustic data: A comprehensive review for large-scale Passive Acoustic Monitoring", Experts Systems with Applications, 2024. (IF=8.5) [paper]

T. Napier, E. Ahn, S. Allen-Ankins and I. Lee, "An Optimised Grid Search Based Framework for Robust Large-Scale Natural Soundscape Classification", 36th Australasian Joint Conference on Artificial Intelligence, 2024. [paper]

S. Zhou, E. Ahn, H. Wang, A. Quinton, N. Kennedy, P. Sridar, R. Nanan and J. Kim, "Improving Automatic Fetal Biometry Measurement with Swoosh Activation Function", International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. [paper]

C. Jiang, Y. Yuan, B. Gu, E. Ahn, J. Kim, D. Feng, Q. Huang and S. Song, "Preoperative prediction of microvascular invasion and perineural invasion in pancreatic ductal adenocarcinoma with 18F-FDG PET/CT radiomics analysis", Clinical Radiology, 2023. (IF=2.6) [paper]

S. Zhou, P. Sridar, R. Nanan, A. Quinton, E. Ahn and J. Kim, "A Deep-Learning Enabled Automatic Fetal Thalamus Diameter Measurement Algorithm ", IEEE Engineering in Medicine and Biology Society (EMBC), 2023. [paper]

Y. Yuan, E. Ahn, D. Feng, M. Khadra and J. Kim, "SSPT-bpMRI: A Self-supervised Pre-training Scheme for Improving Prostate Cancer Detection and Diagnosis in Bi-parametric MRI ", IEEE Engineering in Medicine and Biology Society (EMBC), 2023. [paper]

Z. Kong, H. Ouyang, Y. Cao, T. Huang, E. Ahn, M. Zhang and H. Liu, "Automated Periodontitis Bone Loss Diagnosis in Panoramic Radiographs using a Bespoke Two-stage Detector", Computers in Biology and Medicine, 2023. (IF=7.7) [paper][code and dataset]

W. Wang, E. Ahn, D. Feng and J. Kim, "A Review of Predictive and Contrastive Self-supervised Learning for Medical Images", Machine Intelligence Research, 2023. [paper]

H. Wang, E. Ahn and J. Kim, "SLF-RPM: Self-supervised Representation Learning Framework for Remote Physiological Measurement Using Spatiotemporal Augmentation Loss", 36th AAAI Conference on Artificial Intelligence (AAAI-22), 2022. (Acceptance Rate: 15%) [paper][code]

E. Ahn, D. Feng and J. Kim, "A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation", International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [paper][code][poster][slides][video]

E. Ahn, N. Liu, T. Parekh, R. Patel, T. Baldacchino, T. Mullavey, A. Robinson and J. Kim, "A Mobile App and Dashboard for Early Detection of Infectious Disease Outbreaks: Development Study", JMIR Public Health and Surveillance, 2021. (IF=8.5) [paper]

C. Baird, Y. Oytam, K. Rahman, M. Fornasari, A. Sharma, J. Kim, E. Ahn and R. Hughes, "The Checkpoint Program: Collaborative Care to Reduce the Reliance of Frequent Presenters on Emergency Department", International Journal of Integrated Care, 2021. (IF=2.913) [paper]

E. Ahn, "Unsupervised Deep Feature Learning for Medical Image Analysis", The University of Sydney (PhD Thesis), 2020. [paper]

Y. Guo, L. Bi, E. Ahn, D. Feng, Q. Wang and J. Kim, "A Spatiotemporal Volumetric Interpolation Network for 4D Dynamic Medical Image", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Acceptance Rate: 22.1%) [paper] [code]

E. Ahn, A. Kumar, M. Fulham, D. Feng and J. Kim, "Unsupervised Domain Adaptation to Classify Medical Images using Zero-bias Convolutional Auto-encoders and Context-based Feature Augmentation", IEEE Transactions on Medical Imaging, 2020. (IF=10.6). [paper][code]

E. Ahn, A. Kumar, D. Feng, M. Fulham and J. Kim, "Convolutional Sparse Kernel Network for Unsupervised Medical Image Analysis", Medical Image Analysis, 2019. (IF=10.9). [paper]

E. Ahn, A. Kumar, D. Feng, M. Fulham and J. Kim., "Unsupervised Deep Transfer Feature Learning for Medical Image Classification", IEEE International Symposium on Biomedical Imaging (ISBI), 2019. (Oral). [paper][code]

L. Bi, J. Kim, E. Ahn, A. Kumar, M. Fulham and D. Feng., "Step-wise Integration of Deep Class-specific Learning for Dermoscopic Image Segmentation", Pattern Recognition, 2019. (IF=8). [paper]

E. Ahn, J. Kim, K. Rahman, T. Baldachhino and C. Baird, "Development of a Risk Predictive Scoring System to Identify Patients at Risk of Representation to Emergency Department: a Retrospective Population-based Analysis in Australia", British Medical Journal Open (BMJ Open), 2018. (IF=2.9). [paper][supplementary data]

E. Ahn, J. Kim, L. Bi, A. Kumar, C. Li, M. Fulham and D. Feng, "Saliency-based Lesion Segmentation via Background Detection in Dermoscopic Images", IEEE Journal of Biomedical Health Informatic, 2017. (IF=7.7). [paper]

L. Bi, J. Kim, E. Ahn, A. Kumar, M. Fulham and D. Feng, "Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks", IEEE Transactions on Biomedical Engineering, 2017. (IF=4.6). [paper]

Research Group

Current PhD Students (as primary or secondary supervisor)

  • Yuan Yuan (2021 - )
  • Wei-Chien Wang (2021 - )
  • Hao Wang (2022 - )
  • Shijia Zhou (2022 - )
  • Thomas Napier (2022 - )
  • Abdullah (2023 - )
  • Chameera (2024 - )

Teaching

  • Subject Coordinator, Lecturer, “Operating Systems and Shell Scripting (CP1409)”, James Cook University, 2022-Present.
  • Subject Coordinator, Lecturer, “Introductry Machine Learning and Data Science (CP1407)”, James Cook University, 2022-Present.
  • Subject Coordinator, Lecturer, “Advanced Data Communications Principles (CP5601)”, James Cook University, 2024-Present.
  • Lecturer, “Problem Solving and Programming I (CP1401)”, James Cook University, 2022-Present.
  • Lecturer, “Programming II (CP1404)”, James Cook University, 2022-Present.
  • Subject Coordinator, “3D Modelling and Animation”, James Cook Unviersity, 2022-2024.
  • Teaching Assistant, “Understanding IT Innovation (INFO5992)”, School of Computer Science, The University of Sydney, 2016 to 2020.
  • Teaching Assistant, “Biomedical Design Technology (BMET3921/BMET5921)”, School of Biomedical Engineering, The University of Sydney, 2019 to 2020.
  • Guest Lecturer, “Enterprise Healthcare Information System (INFO5306)”, School of Computer Science, The University of Sydney, 2019 to 2021.

Grants, Honours and Awards

  • CodeCraft: Augmented Learning for IT students ($10,000) , JCU Learning and Teaching Innovation Grants, 2024.
  • Patient-centered Digital Platform for Early-stage Chronic Kidney Disease ($50,000) , The Northern Australian Regional Digital Health Collaborative, 2022.
  • Fusion of wearable and environmental sensors for remote monitoring of health and wellbeing in elderly populations ($50,000) , The Northern Australian Regional Digital Health Collaborative, 2022.
  • CSE ECR Research Support Award ($4,500) , James Cook University, 2022.
  • 2019 School of Computer Science Research Students Excellence Prize Award ($5,000), The University of Sydney, 2019
  • Best Oral Presentation Award ($500), “A Self-Supervised Deep Learning Framework for Plane Identification in Fetal Ultrasound Images”, Annual Nepean Research Day, The University of Sydney Nepean Clinical School, 2019.
  • Telehealth Technology Innovation Award ($50,000), “DeepVitals for Remote Patient Monitoring – A Non-contact Image-based Blood Pressure via Deep Photoplethysmography Network”, Nepean Blue Mountains Local Health District (Nepean Hospital), NSW, 2019.
  • Telehealth Technology Innovation Award ($10,000), “An Analysis and Visualisation of Emergency Department Data using Machine Learning Algorithms”, Nepean Blue Mountains Local Health District (Nepean Hospital), NSW, 2018.

Scientific Community Service

Workshop Organisation

Invited Talks

  • Transforming Healthcare with AI, Queensland AI Hub Launch, JCU Ideas Lab, 2023
  • Transforming Healthcare with AI, JCU Inspiration on Tap (Public Lecture), Salt House, Cairns city, 2022
  • AI for Medical Image Analysis and Digital Health, Digitrek (Research Showcase), TAFE Queensland, 2022
  • An AI-based Remote Patient Monitoring System using Facial Videos, NBMLHD Together Achieving Better Health Conference, 2021
  • Unsupervised Deep Learning for Medical Image Analysis, AI in Medical Imaging, The Westmead Institute for Medical Research, 2020
  • Unsupervised Deep Transfer Feature Learning for Medical Image Classification, IEEE 16th International Symposium on Biomedical Imaging, Venice, Italy, 2020
  • Data Visualization and Analytics in Healthcare, Research Conversazione, Faculty of Engineering, University of Sydney, 2019
  • Automated Melanoma Segmentation and Classification, Statistical Bioinformatics Seminar, Faculty of Science, University of Sydney, 2015

Journal Reviewer:

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Medical Imaging (TMI) - Distinguished Gold Level Reviewer 2020-2022
  • Medical Image Analysis (MedIA)
  • Nature Communication
  • Computer Vision and Image Understanding
  • IEEE Transactions on Biomedical Engineering (TBME)
  • IEEE Journal of Biomedical and Health Informatics (JBHI)
  • IEEE Access
  • Pattern Recognition
  • Neurocomputing
  • Computer Methods and Programs in Biomedicine
  • Information Fusion
  • The Visual Computer
  • Computational and Structural Biotechnology Journal
  • Journal of Medical Internet Research

Conference Reviewer:

  • International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
  • International Symposium on Biomedical Imaging (ISBI)

Last updated date: 2 Jan 2025.