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Short Biography

I am a postdoctoral research fellow at the Biomedical Multimedia Information Technology (BMIT) group, School of Computer Science, The University of Sydney. I obtained a 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 A/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 am also a Research Associate at the Telehealth and Technology Centre, Nepean Hospital, Australia.

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).

Honours and Awards

  • 2019 School of Computer Science Research Students Excellence Prize Award, The University of Sydney, 2019
  • Best Oral Presentation Award, “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, “An Analysis and Visualisation of Emergency Department Data using Machine Learning Algorithms”, Nepean Blue Mountains Local Health District (Nepean Hospital), NSW, 2019.
  • Scholarship, The University of Sydney Merit Awards (Top ranked PhD Candidates), 2016-2019.
  • Scholarship, Australian Government Research Training Program Scholarship, 2016-2019.

Research Areas

Deep Learning, Machine Learning, 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.

Selected Publications

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=6.685). [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=11.148). [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=7.196). [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=2.496). [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=5.223). [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=4.424). [paper]

L. Bi, J. Kim, E. Ahn, D. Feng and M. Fulham, "Semi-automatic Skin Lesion Segmentation via Fully Convolutional Networks", IEEE International Symposium on Biomedical Imaging (ISBI), 2017. [paper]

E. Ahn, A. Kumar, J. Kim, C. Li, D. Feng and M. Fulham, "X-ray Image Classification Using Domain Transferred Convolutional Neural Networks and Local Sparse Spatial Pyramid", IEEE International Symposium on Biomedical Imaging (ISBI), 2016. [paper]

L. Bi, J. Kim, E. Ahn, D. Feng and M. Fulham, "Automatic Melanoma Detection via Multi-Scale Lesion-biased Representation and Joint Reverse Classification", IEEE International Symposium on Biomedical Imaging (ISBI), 2016. (Oral). [paper]

L. Bi, J. Kim, E. Ahn, D. Feng and M. Fulham, "Automated Skin Lesion Segmentation via Image-wise Supervised Learning and Multi-scale Superpixel Based Cellular Automata", IEEE International Symposium on Biomedical Imaging (ISBI), 2016. (Oral). [paper] [code]

E. Ahn, L. Bi, Y. Jung, J. Kim, C. Li, M. Fulham and D. Feng, "Automated Saliency-based Lesion Segmentation in Dermoscopic Images", IEEE Engineering in Medicine and Biology Society (EMBC), 2015. [paper] [code]

Research Competitions

  • Ranked at (2nd/24), “Sydney Innovation Challenge 2019: Diabetic Retinopathy Classification”, 2019 [leaderboard]
  • Ranked at (4th/21), "ISIC 2017: Skin Lesion Analysis Towards Melanoma Detection: Lesion Segmentation, 2017 [leaderboard]
  • Ranked at (4th/18), "ISIC 2016: Skin Lesion Analysis Towards Melanoma Detection: Lesion Segmentation, 2016 [leaderboard]

Teaching

  • Teaching Assistant, “Understanding IT Innovation (INFO5992)”, School of Computer Science, The University of Sydney, 2016 to Current.
  • Teaching Assistant, “Biomedical Design Technology (BMET3921/BMET5921)”, School of Biomedical Engineering, The University of Sydney, 2019.
  • Guest Lecturer, “Enterprise Healthcare Information System (INFO5306)”, School of Computer Science, The University of Sydney, 2019.

Scientific Community Service

Workshop Organisation

Invited Talks

  • Unsupervised Deep Learning for Medical Image Analysis, AI in Medical Imaging, The Westmead Institute for Medical Research, 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)
  • 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
  • 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: 30 Sep 2020.