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August, 2019: Post Doctoral Researchers/Resercah Associates/PhD Candidates

A/Prof Abeyratne is accepting (2021) post-doctoral researchers/covering the areas of: pattern recognition, machine learning, respiratory sound analysis, digital signal processing and smart phone programming. Qualified students are invited to apply for PhD scholarships on a competitve basis.

June 2021:

Snore sound based Sleep Apnea diagnostics intellectual property developed by Dr. Udantha Abeyratne and his team are available for commercialisation. The technology is the culmination of 20 years of ground breaking work leading to four patent applications including two granted ones in the USA (the rest are under examination at various stages) and a large portfolio of peer reviewed publications in international scholarly journals. A Matlab implementation of re-trainable technology and performance comparions against American Academy of Sleep Medicine scoring critera of 2007 (AASM 2007) are available. Prior comparisons on Chicago Criteria ("AASM 1999") are also available via peer-reviewed literature. Our software models indicate that the technology can diagnose sleep apnea at a sensitivity and specificity approching that of a standard facility-based polysomnography (sensitivity, specificity around 90%, 90%-- cross validation studies). Note that the model development data sets available to us (n=100 approx) had been scored per AASM 2007 clinical criteria. Thus, the resulting models require a straight-forward re-training (re-calibration) process on AASM 2012 data before they can be used on subjects diagnosed under AASM 2012 criteria (which is the clinical scoring standard in effect since 2012).

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Assoc./Prof. Udantha Abeyratne is the inventor of the cough-sound based respiratory diagnosis technology (ResApp Health Ltd. (ASX: RAP)) and snore sound based sleep apnea diagnosis technology SnoreSounds.

He earned a PhD (Biomedical Engineering) from Drexel University, USA, and MEng and BScEE degrees in Electrical & Electronic Engineering from Tokushima U, Japan and U Peradeniya, (video here) Sri Lanka respectively. He also received formal post-graduate training in Higher Education (Grad Cert , U of Queensland, Australia) and Paediatric Sleep Science (Grad Cert., U of Western Australia, Australia). He is a Senior Member of the Institute of Electrical & Electronic Engineers (IEEE, USA), and a full Member of the American Academy of Sleep Medicine (AASM).

​Dr. Abeyratne started his research career with a paper on coding techniques for low-bandwidth communication channels. His master's thesis was on a machine learning approach to the human brain activity analysis using electroencephalography (EEG, Brain Waves) and evoked potentials. This approach won the best paper award in ISBET Brain Topography Conference (Osaka, Japan, 1990) and also placed Dr. Abeyratne as a finalist at the Young Investigators' Competition in IFMBE World Congress on Medical Physics and Biomedical Engineering, 1991 (Kyoto, Japan). He completed his PhD (1996) with Prof. Athina Petropulu as the advisor, working on Higher-Order-Spectra and medical ultrasound imaging. The thesis developed slice-based low-complexity algorithms for blind signal identification, tumor detection in ultarsound images, and image deconvolution.

Teaching Activities:

Assoc/Prof. Abeyratne has designed and taught university level courses on digital signal processing, electronic circuits, medical and general instrumentation, medical signal processing, medical imaging, control systems, project management and electromagnetic waves. He has supervised both undergraduate and postgraduate dissertation thesis projects in these areas. Within the last decade five students supervised by him won competitive awards at the UQ Innovation Expo.

Current Research Profile:

Assoc./Prof. Abeyratne's research interests encompass digital signal processing, machine learning, medical instrumentation, medical imaging, electrophysiology, bio-signal analysis and electronics. Over the last two decades A/Prof. Abeyratne has conceptualized, initiated and led the development of a number of innovative technologies funded by prestigious granting agencies such as the Bill & Melinda Gates Foundation, Australian Research Council and the A*-Star Singapore. His research programmes are characteristic of unorthodox approaches resulting in pioneering outcomes that produced spin-off companies, patents and scholarly publications. His research has recieved multiple peer accolades at the international level.

1. Electronic Instrument Design: hand-held ultrasound devices for medical, agricultural and industrial use; stethoscopes for the 21st century (The "Magithescope(c)", winner of two UQ Expo awards in 2013, 2014); biomimetic sensing devices (e.g. electronic nose, e-tongue), low-cost, portable electronic devices ("Tricoders") for diagnosing diseases such as apnea, asthma, pneumonia; wearable electrophysiological devices; real-time fatigue measurement and warning systems; hand-held instruments for the condition monitoring of machinery such as power transformers. Development of diagnostic and treatment devices for sleep apnea. Dr. Abeyratne is especially interested in developing accurate, multi-purpose and low-cost in-situ decision devices for applications in resource-poor regions of the world.

2. Diagnostic and Treatment Technology for Sleep Disorders: speech-like analysis of snore and breathing sounds; sleep diagnostic instrument design; sleep polysomnography, brain wave (EEG) analysis in sleep, quantification of fatigue and sleepiness; sleep apnea; design of apnea treatment devices (CPAP, dental devices); interaction of apnea and chronic diseases. mHealth approaches in sleep diagnostics. A/Prof. Abeyratne pioneered speech-like processing of respiratory sounds, leading to patents, papers and a spin-off company. He conceptualized and led the development of EEG based technology to quantifiy sleepiness in real-time in actual work environments. Outcomes of this program have recieved wide coverage in international media outlets due to its groundbreaking nature and the potential impact.

3. Respiratory Diagnostic Technology: diagnostic instrumentation and algorithm design for respiratory illnesses such as pneumonia, bronchiolitis, asthma, bronchiectasis and COPD; cough sound analysis in respiratory medicine; imaging technology for respiratory diagnosis; Portable diagnostic technologies and mHealth approaches for remote resource-poor areas of the world. About 1 million children below the age of 5 yrs die every year of pneumonia alone, mainly in remote resource-poor areas of the world. Poor access to diagnostics and medical treatment are the major reasons for pneumonia fatalities. A/Prof. Abeyratne proposed a ground-breaking new technology to diagnose pneumonia centred about cough sound analysis. For this research Dr. Abeyratne received funding from UQ, UniQuest and the Bill & Melinda Gates Foundation, which lauded the project (Page 4) as an exmaple for an innovative idea with high impact. Outcomes led to scholarly publications and contributed to patents as well as a spinoff company by UQ.

4. Signal Processing and Machine Intelligence: the analysis of bio-signals such as electroencephalography (EEG), electromyography (EMG); speech and industrial sound analysis, bowel sound analysis and the characterisation of inflammatory bowel disease; cardiovascular signal processing, source localization and blind source separation, higher order spectra, wavelets, pattern recognition, classifier design. Developing technology for monitoring the condition of Left Ventricular Assist Devices (LVAD).

5. mHealth: research on smart phone and other consumer devices as a platform for healthcare delivery. A/Prof Abeyratne is actively engaged in developing mHealth diagnostic solutions, including translating and customising sleep and respiratory technologies. He is also in the process of expanding the work to include meaningful deployment of the technology in both the developed and developing worlds, in collaboration with international NGOs, experts in community medicine, and the UQ spin-off companies resulting from the research program. New national and international collaborations are currently being negotiated to fund and facilitate this work.

The Research Team, Past & Present:

Associate professor Udantha Abeyratne, Dr. Keegan Kosasih (Past PhD graduate); Dr Duleep Herath (past PhD gradute, )Dr. Shahin Akhter (Past PhD graduate), Dr. Vinayak Swarnkar (Past PhD graduate ); Dr. Yusuf Amrulloh (Past PhD graduate); Dr. Shaminda de Silva (Past PhD graduate); Dr. Samantha Karunajeewa (Past PhD graduate); Dr. Suren Rathnayake (Past PhD graduate), Dr. Xiao Di (Past PhD graduate), Dr. T. Emoto (Past PhD work in UQ while at UT), ; Mrunal Markendeya (Current PhD Student); Karen McCloy (current PhD student), Ajith Wakwella (Past MPhil graduate); Lee Teck Hock (Past MPhil Graduate), Tang Xiaoyan (Past MPhil Graduate), Dr. Zhang Guanglan (Past MPhil Graduate), Dr. Syed Adnan (Past MPhil Graduate) and many past and present dissertation thesis students.

Research Collaborators:

Dr. Craig Hukins & Brett Duce (Princess Alexandra Hospital), Prof. Y. Kinouchi & Dr. T. Emoto (U of Tokushima, Japan), Dr. Sarah Biggs (Monash), Dr.Simon Smith (QUT), Dr. Chandima Ekanayake (Griffith U), Dr. Paul Porter (PMH Hospital), Prof. Anne Chang (Menzies School of Health Reserach, CDU), Dr. Scott Mckenzie (Princess Charles Hospital), Dr. Nirmal Weeresekera (JKMRC, UQ), Dr. Rina Triasih (Gadjah Mada U, Indonesia), Dr. K. Puvanendran (1998-2002: Singapore General Hospital, Singapore), Prof.Stanislaw Gubanski (Chalmers U, Sweden).

Markus graduated from the Vienna University of Technology in Technical Physics in 1995 and was awarded his Doctorate in 1999 after which he worked as postdoctoral research associate and then Assistant Professor at the Department of Radiodiagnostics, Medical University Vienna (AT). From 2004 he worked as Senior Researcher at the Donders Institute for Brain, Cognition and Behaviour (Radboud University Nijmegen, NL) and at the Erwin L. Hahn Institute for Magnetic Resonance Imaging (University Essen-Duisburg, DE). In 2014 he relocated to the University of Queensland to head the Ultra-high Field Human MR Research program at the Centre for Advanced Imaging and was awarded an ARC Future Fellowship. In 2019 he joined the School of Information Technology and Electrical Engineering as Full Professor MR Physics and Medical Imaging and has been appointed as Director for the National Imaging Facility – Queensland Node.

MBChB FRCA FANZCA FFICM PhD

Dr Mostafa Kamal Masud is a CCQ Next Generation Cancer Research Fellow at the Australian Institute for Bioengineering & Nanotechnology (AIBN), the University of Queensland (UQ). In 2020, he received his PhD in Medical Biotechnology Diagnostics and Nanobiotechnology from AIBN, UQ. He received his MS and B.Sc. (Hons.) in Chemistry from Shahjalal University of Science and Technology (SUST), Sylhet-3114, Bangladesh. After completing his PhD, he was awarded a prestigious JSPS Postdoctoral Fellowship (success rate >10%) from Japan and served as a Postdoctoral Fellow at Japan's National Institute for Materials Science (NIMS).He recently been awarded a highly prestigious ARC DECRA fellowship for the period 2024-2026 and a QLD Cancer Council fellowship for the period 2024–2028. His research focuses on the development of novel nanostructures and nanodiagnostic technologies to address critical issues in medical diagnosis. As an early career researcher, he has an excellent track record with more than 50 peer-reviewed publications in prestigious and high-impact journals in the area that achieve <2400 citations with an h-index of 26 (Scholar google link: https://bit.ly/2Vtv67l). He has developed new classes of superparamagnetic nanostructures and fabricated novel biosensors for the detection of disease-specific biomolecular targets e.g., for miRNA, DNA, exosome and protein biomarker detection that have proven to be easy and effective, allowing for rapid diagnosis with minimal equipment. He made a major contribution to nanotechnology integrated-analytical and diagnostic fields by providing analytical and technological input as well as developing key collaborations with clinicians and biologists for translational research. His strategy is to create nano-architecture point-of-care diagnostic technology for early diagnosis of cancer that could hopefully lead to a healthy and happier life for humans.

Dr Antonio Padilha L. Bo completed the BEng and MSc at the University of Brasília, Brazil, in 2004 and 2007, respectively, and he was awarded the PhD from the University of Montpellier, France, in 2011. From 2011 to 2019, he has been a tenured assistant professor in electrical engineering at the University of Brasilia, Brazil, where he coordinated Project EMA (Empowering Mobility and Autonomy), which is one of the teams that took part in the Cybathlon competition in 2016 and 2020. He has co-authored over 75 peer-reviewed publications, including awards from societies such as IFAC, IFESS, and MICCAI.

Over the past ten years, Dr Bo has been engaged in research projects concerning the development of technology dedicated to healthcare, particularly in the design of systems to be directly used by a patient in rehabilitation or assistive settings. Every effort featured strong experimental work and was conducted in close collaboration with local rehabilitation centers. In his work, tools from neuroengineering, robotics, control, virtual reality, and instrumentation are often integrated to create devices and algorithms to sense and control human motion. For instance, he has used wearable sensors to segment and estimate parameters of human movement in real-time, a technique that may lead to novel rehabilitation protocols. More importantly, his work has also focused on developing closed-loop control strategies for electrical stimulation applications and prosthetic/orthotic devices. Some examples include systems based on superficial electrical stimulation to enable persons with spinal cord injury to exercise using the lower limbs (e.g. in cycling or rowing) and to attenuate the effects of pathological tremor in essential tremor and Parkinson's Disease.

His long-term research goal is to develop and evaluate the use of noninvasive technology, including electrical stimulation, robotics, virtual reality, and wearable devices, for improving rehabilitation and assistance for persons with motor disabilities.

Dr Hongfu Sun completed his PhD in Biomedical Engineering at the University of Alberta in 2015, followed by postdoctoral training in Calgary until 2018. He joined the Imaging, Sensing and Biomedical Engineering team in the School of ITEE at UQ in 2019 and was awarded the ARC DECRA fellowship in 2021. His research interests include developing novel magnetic resonance imaging (MRI) contrast mechanisms, e.g. Quantitative Susceptibility Mapping (QSM), fast and multi-parametric MRI acquisitions, and advanced image reconstruction techniques, including deep learning and artificial intelligence, to advance medical imaging techniques for clinical applications.

Dr Sun is currently recruiting graduate students. Check out Available Projects for details. Open to both Domestic and International students.

Dr Torniainen's main research interests are in the fields of biomedical signal and image processing, biophotonics, and applied spectroscopy. He holds BSc/MSc in Electrical Engineering from Aalto University (Finland, 2015) and a PhD in Applied Physics from University of Eastern Finland (Finland, 2020). He has previously worked with developing preprocessing techniques for EEG/MEG, real-time analysis methods for physiological signals (e.g., ECG/EMG/EDA), and near-infrared spectroscopy based analysis of tissue integrity for musculoskeletal tissues. His current research focus is on machine learning in image processing, analysis, and synthesis of biomedical images acquired using a combination of terahertz imaging, nano-FTIR, and Raman spectroscopy. The purpose of this study is to better understand the interaction between light and multi-layered tissues such as articular cartilage and skin.