PhD (University of Queensland)
I am a Chartered Professional Engineer, Engineering Executive and Fellow of Engineers Australia. I am also a Senior Member of the IEEE in the Engineering in Medicine and Biology and Signal Processing societies. I am currently the Associate Dean of Research and Innovation for the Science and Engineering Faculty at Queensland University of Technology. From 2011 to 2016 I was an ARC Future Fellow and Director of Research for The School of Information Technology and Electrical Engineering at The University of Queensland. I have previously been the Chief Technology Officer for Ausonex Pty Ltd, a company specialising in the design and development of hearing test instruments, and Principal Biomedical Engineer for Maxwell MRI, a company developing the next generation of diagnostic tools powered by artificial intelligence and multi-parametric magnetic resonance imaging. I have a broad interdisciplinary knowledge across biomedical and electrical engineering, computing science and communications technology, with over 20 years of experience in commercially focused research with companies such as Maxwell MRI, Ausonex, Canon Information Systems Research Australia (CiSRA), the CRC for Sensor Signal and Information Processing (CSSIP). I have made a significant impact across a number of areas in both commercial and academic research, particularly in the application and evaluation of computer aided diagnosis (CAD) systems in medical imaging. Over my career I have contributed to a broad array of collaborative research projects ranging from deep brain stimulation, total artificial hearts, neonatal hearing screening to medical imaging for prostate, breast and cervical cancer diagnosis. I have published more than 140 peer-reviewed papers and hold 20 granted patents in the USA, Japan, Europe and Australia. According to Google Scholar, my research has received over 8,400 citations with an h-index of 35 and an i10 index of 74. These achievements are exemplary given that they are uniquely balanced by significant time working in industry, where intellectual property considerations often constrained publication. I have been granted more than $6M in competitive research funding and been actively involved in two start-up companies raising over $4M in venture capital. I have successfully graduated 21 Ph.D. and 4 Research Masters candidates and am currently on the advisory team of three others.
Additional information
- Carneiro, G., Nascimento, J. & Bradley, A. (2017). Automated analysis of unregistered multi-view mammograms with deep learning. IEEE Transactions on Medical Imaging, 36(11), 2355–2365. https://eprints.qut.edu.au/114146
- Oakden-Rayner, L., Carneiro, G., Bessen, T., Nascimento, J., Bradley, A. & Palmer, L. (2017). Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework. Scientific Reports, 7, 1–13. https://eprints.qut.edu.au/114134
- Lu, Z., Carneiro, G. & Bradley, A. (2015). An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cells. IEEE Transactions on Image Processing, 24(4), 1261–1272. https://eprints.qut.edu.au/114163
- Timms, D., Frazier, O., Cohn, W., Nestler, F., Bradley, A. & Wilson, S. (2014). A hybrid mock circulation loop for a total artificial heart. Artificial Organs, 38(9), 775–782. https://eprints.qut.edu.au/114174
- Bradley, A., (2013). ROC curve equivalence using the Kolmogorov-Smirnov test. Pattern Recognition Letters, 34(5), 470–475. https://eprints.qut.edu.au/114191
- Ng, K., Bradley, A. & Cunnington, R. (2012). Stimulus specificity of a steady-state visual-evoked potential-based brain-computer interface. Journal of Neural Engineering, 9(3), 1–13. https://eprints.qut.edu.au/114196
- Gal, Y., Mehnert, A., Bradley, A., McMahon, K., Kennedy, D. & Crozier, S. (2010). Denoising of dynamic contrast-enhanced MR images using dynamic nonlocal means. IEEE Transactions on Medical Imaging, 29(2), 302–310. https://eprints.qut.edu.au/114209
- Barakat, N., Bradley, A. & Barakat, M. (2010). Intelligible support vector machines for diagnosis of diabetes mellitus. IEEE Transactions on Information Technology in Biomedicine, 14(4), 1114–1120. https://eprints.qut.edu.au/114211
- O'Brien, I., Wilson, W. & Bradley, A. (2008). Nature of orchestral noise. Journal of the Acoustical Society of America, 124(2), 926–939. https://eprints.qut.edu.au/114220
- Barakat, N. & Bradley, A. (2007). Rule extraction from support vector machines: A sequential covering approach. IEEE Transactions on Knowledge and Data Engineering, 19(6), 729–741. https://eprints.qut.edu.au/114234
- Title
- Human-Machine Teaming:Designing Synergistic Learning of Humans and Machines
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP200103582
- Start year
- 2021
- Keywords