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Ross McVinish has research interests in applied probability, Bayesian statistics and mathematical modelling of complex systems in population biology.

He received his PhD from Queensland University of Technology in 2002.

He is currently an associate editor for the Australian and New Zealand Journal of Statistics.

Radislav (Slava) Vaisman is a faculty member in the School of Mathematics and Physics at the University of Queensland. Radislav earned his Ph.D. in Information System Engineering from the Technion, Israel Institute of Technology in 2014. Radislav’s research interests lie at the intersection of applied probability, statistics, and computer science. Such a multidisciplinary combination allows him to handle both theoretical and real-life problems, in the fields of machine learning, optimization, safety, and system reliability research, and more. He has published in top-ranking journals such as Statistics and Computing, INFORMS, Journal on Computing, Structural Safety, and IEEE Transactions on Reliability. The Stochastic Enumeration algorithm, which was introduced and analyzed by Radislav Vaisman, had led to the efficient solution of several problems that were out of reach of state of the art methods. In addition, he is an author of 3 books with three of the most prestigious publishers in the field, Wiley, Springer, and CRC Press. Radislav serves on the editorial board of the Stochastic Models journal.

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.

Adrian grew up in Perth and double majored in Pure Mathematics and Applied Mathematics at the University of Western Australia. Soonafter, he ventured to Canberra to undertake a PhD, focussing on analytic number theory: an enchanting area where one perplexingly uses calculus and analysis to study discrete structures such as the set of prime numbers.

After this, he worked as a derivatives trader at Optiver APAC for five years and stayed on there as Head of Academic Partnerships. He currently straddles both industry and academia and believes they both have much to offer mathematicians.

Adrian is available (and invariably keen) to supervise honours, masters and PhD projects in analytic number theory.

Dr Barbara Maenhaut's research interests are in combinatorial design theory and graph theory.

She received her PhD from the University of Queensland in 1999. Her current research projects are in the fields of:

• Graph decompositions
• Latin squares and perfect one-factorisations

Shakes an imaging expert that leads a strong deep learning, artificial intelligence (AI) focused research team interested in medical image analysis and signal/image processing applied to many areas of science and medicine. He received his Ph.D in Theoretical Physics from Monash University, Melbourne and has been involved in applying machine learning in medical imaging for over a decade.

Shakes’ past work has involved developing shape model-based algorithms for knee, hip and shoulder joint segmentation that is being developed and deployed as a product on the Siemens syngo.via platform. More recent work involves deep learning based algorithms for semantic segmentation and manifold learning of imaging data. Broadly, he is interested in understanding and developing the mathematical basis of imaging, image analysis algorithms and physical systems. He has developed algorithms that utilise exotic mathematical structures such as fractals, turbulence, group theoretic concepts and number theory in the image processing approaches that he has developed.

He is currently a Senior Lecturer and leads a team of 20+ researchers working image analysis and AI research across healthcare and medicine. He currently teaches the computer science courses Theory of Computation and Pattern Recognition and Analysis.

Methods and applications of statistics in evolutionary biology and population ecology.

My research involves the application and development of statistical methods in ecology, evolutionary biology, and general whole-organism biology. My two particular research foci are phylogenetic comparative methods and other uses of statistics in ecology, evolution, and systematics. I also have a strong interest in the application of Bayesian methods, and the statistical philosophy of the nature of evidence in whole-organism biology. How and why do scientists agree that certain data are evidence for or against a particular hypothesis?

I also provide a statistical consultation service for staff and students within the School of Biological Sciences

I am interested in taking graduate students at any level who are interested in quantitative methods in biology. Students in my lab will be able to (or be willing to learn) program computers in S (http://www.r-project.org), a compiled language such as C or Fortran, and/or a scripting language such as Python or Scheme in a Unix environment. Students are also encouraged to extend or develop their mathematical skills. A background in biology, statistics, mathematics, or computer science would be valuable. I can also co-supervise students who are interested in using quantitative methods for their thesis work, but for whom such methods are not a primary focus of research.

Professor Geoffrey McLachlan's research interests are in: data mining, statistical analysis of microarray, gene expression data, finite mixture models and medical statistics.

Professor McLachlan received his PhD from the University of Queensland in 1974 and his DSc from there in 1994. His current research projects in statistics are in the related fields of classification, cluster and discriminant analyses, image analysis, machine learning, neural networks, and pattern recognition, and in the field of statistical inference. The focus in the latter field has been on the theory and applications of finite mixture models and on estimation via the EM algorithm.

A common theme of his research in these fields has been statistical computation, with particular attention being given to the computational aspects of the statistical methodology. This computational theme extends to Professor McLachlan's more recent interests in the field of data mining.

He is also actively involved in research in the field of medical statistics and, more recently, in the statistical analysis of microarray gene expression data.

Prof. Amin Abbosh specializes in Medical Microwave Imaging and Microwave and Millimeter-wave Engineering. His work focuses on designing and developing advanced imaging and sensing systems using electromagnetic techniques at radio-wave frequencies.

Prof. Abbosh’s significant contributions include the creation of innovative imaging systems that leverage his expertise in applied electromagnetics and microwave engineering. He has developed comprehensive analytical and computational frameworks, incorporating signal-processing techniques for detection and AI for classification. This approach has led to a new modality for detection and imaging, combining physics-guided and data-driven methods. His work is protected by over 16 patents.

In Communication Technologies, Prof. Abbosh's work focuses on designing flat-panel, low-cost reconfigurable antennas. These antennas form ground satellite terminals that communicate with low-earth-orbit (LEO) satellites, providing reliable broadband access to remote and regional communities. This technology supports e-health services, distance education, and business productivity, and can be used in various on-the-move environments.

Professor Ryan Ko is Chair and Director of UQ Cyber Research Centre, Director of Research at the School of Electrical Engineering and Computer Science, and an elected member of the Academic Board at the University of Queensland, Australia. He holds a Bachelor of Engineering (Computer Engineering)(Hons.) (2005), and PhD (2011) from Nanyang Technological University, Singapore.

Ko has held senior scientific leadership, executive, and directorship roles across industry and academia, and has more than a decade of board, governance and advisory experience across government, industry and NGOs across Australia, New Zealand, Singapore, and USA.

He currently serves on the Audit and Risk Committee for the board of the global not-for-profit ORCID, and has served on boards and advisory groups for AustCyber, Queensland Government, Meat and Livestock Australia (MLA), and the NZX-listed (NZE:LIC) Livestock Improvement Cooperation (LIC).

He has also served as expert advisor to INTERPOL, the government of Tonga, NZDF, NZ Minister for Communications' Cyber Security Skills Taskforce, and one of four nationally-appointed Technical Adviser for the Harmful Digital Communications Act 2015, Ministry of Justice. He has also served as independent technical expert for court cases.

He is also Adjunct Professor at the Singapore Institute of Technology, and Affiliate Faculty Member at NIATEC at the Idaho State University, USA.

He is co-founder of Dynamic Standards International (DSI), CyberCert, and First Watch Ltd (NZ) – an industrial cybersecurity spin-off based on his patented OT security and provenance research at the University of Waikato.

Since joining UQ in 2019, he has served as:

• Deputy Head of School (External Engagement) (2021-2022)
• Founding Discipline Leader of the Cyber Security and Software Engineering discipline (2020-2021)
• Group Leader - Cyber Security (2019)

Ko has successfully established several university-wide, multi-disciplinary academic research and education programmes, including establishing and leading:

• UQ Cyber - interdisciplinary cyber scurity research centre involving 60+ academics and their respective teams from the 6 Schools (EECS, Business, Economics, Law, Social Science, Mathematics & Physics), the Centre for Policy Futures, and 4 Faculties since 2019.
• UQ's interdisciplinary postgraduate programme (MCyber, PGDipCyber, GCertCyber) involving four UQ faculties in 2019,
• NZ's first cyber security graduate research programme and lab (Cybersecurity Researchers of Waikato (CROW)) in 2012,
• NZ's first Master of Cyber Security (encompassing technical and law courses), the NZ Cyber Security Challenge since 2014, and
• NZ Institute for Security and Crime Science – Te Puna Haumaru as its founding director, the Evidence Based Policing Centre (at Wellington with NZ Police and ESR), and Master of Security and Crime Science in 2017 with the University of Waikato, NZ.

Over his academic career, Ko has been awarded A$20+million in competitive grants as lead Chief Investigator, and ~A$40+million as co-investigator. Prior to UQ, he was the highest funded computer scientist in New Zealand, as Principal Investigator and Science Leader of the largest MBIE-awarded cloud security research funding for STRATUS (NZ$12.2 million; 2014-2018). STRATUS' research was awarded 'Gold' by MBIE (i.e. top performing project, 2017), adopted by INTERPOL and featured in NZ's Department of Prime Minister and Cabinet's NZ Cyber Security Strategy 2016 annual report.

Ko has a track record developing international and national cyber security curricula, including:

• Co-creation of the gold-standard (ISC)2 Certified Cloud Security Professional (CCSP) curriculum (2014-2015)
• Authoring the draft of the NZQA's Level 6 Cybersecurity Diploma qualification as part of the NZ Cyber Security Skills Taskforce on behalf of the Department of Prime Minister and Cabinet.

Ko has also experience developing competitions and coaching competitive cyber security teams, including:

• Co-founding the NZ Cyber Security Challenge in 2014, and leading the NZCSC from 2014 to 2018. NZCSC is now the premier national cyber security competition in NZ.
• Co-founding the Oceania Cybersecurity Challenge (OCC) in 2020, and leading the competition from 2022 to present. OCC is now the regional qualifiers for the International Cybersecurity Challenge
• Co-founding the International Cybersecurity Challenge (ICC) as part of the Steering Committee in 2022. ICC has been held in Athens (2022) and San Diego (2023). It is aiming to be the world cup of cyber competitions.
• Head Coach of Team Oceania for the ICC. 2022 Results: Overall 4th; 2023 Results: Overall 2nd in the world.

He contributed to the establishment of the Government of Tonga CERT and CERT NZ, and has spoken regularly on cyber and cloud security research across the globe, including the OECD, Republic of Korea National Assembly (2018), INTERPOL (2017), TEDx Ruakura (2017), and the NZ Members of Parliament (2016).

Within the ISO/IEC JTC 1/SC 27, Prof Ko was Head of Delegation for the Singapore national body, served as Editor, ISO/IEC 21878 “Security guidelines for design and implementation of virtualized servers”, and hosted the ISO/IEC JTC 1/SC 27 meetings at Hamilton, NZ, in 2017. He is currently one of the editors of the ISO/IEC PWI 5181 Data Provenance Reference Model. In 2022, Ko co-chaired the development of the Singapore standard TR 106:2022 Tiered cybersecurity standards for enterprises in collaboration with the SPSTC and Singapore Cyber Security Agency.

Ko serves as an assessor for the Australian Research Council (ARC), Irish Research Council, Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), and NZ MBIE College of Assessors (since 2015).

He is also an external expert for the Tertiary Education Quality and Standards Agency (TEQSA), and a member of the Australian Computer Society (ACS) Accreditation Committee. He has experience reviewing course proposals and served in governance roles for higher education institutes.

Ko has externally examined 11 PhD and 3 Masters theses for universities in Australia, New Zealand, Canada, Hong Kong and Singapore.

For his contributions to the field, he was elected Fellow of the Australian Computer Society, Fellow of the Queensland Academy of Arts and Sciences, and Fellow of Cloud Security Alliance (CSA) (2016). He was awarded the Singapore Government (Enterprise Singapore)’s Young Professional Award (2018) for his leadership at ISO, and awarded the inaugural CSA Ron Knode Service Award 2012 for the establishment of Cloud Data Governance and Cloud Vulnerabilities Research Working Groups. He is also recipient of the 2015 (ISC)2 Information Security Leadership Award.

For his research and teaching excellence, he was awarded the University of Queensland Awards for Excellence - Leadership (Commendation) (2023), EAIT Nominations for Most Effective Teacher (both semesters of 2020, 2021, 2022, 2023), University of Waikato's Early Career Excellence Award (2014), Faculty Teaching Excellence Awards (2014, 2015, 2018), and the Nola Campbell eLearning Excellence Award (2014). During his PhD, he was also awarded A*STAR SIMTech's Best Student Award (2009), and clinched the 1st Prize of the IEEE Services Cup 2009 at IEEE ICWS (CORE A*) in Los Angeles, CA.

Earlier in his career, Ko was a systems engineer, and subsequently founded two start-ups (one was a social enterprise which became an events/conventions management contractor with IMG at mega-events in Singapore, including the inaugural Youth Olympics in 2010).

He is an active science communicator and is regularly interviewed and featured by Australian (ABC News, SBS News, 7 News, 9 News, Courier Mail, Network 10, AFR), Singaporean (Channel NewsAsia, CNA Radio938), NZ (NZ Herald, Dominion Post, Stuff.co.nz, Waikato Times, TVNZ, Central TV) and international media on topics of cyber security, cybercrime and data privacy.

Malcolm has applied fundamental comminution research to design and process improvement on over 70 mines worldwide during 40 years at Mintek, UCT, Professor of comminution at the JKMRC in Australia, and through private research companies. His work is published in over 240 papers and has been presented in as many conferences worldwide. Malcolm collaborates extensively, with close compatriots on 5 continents forming the Global Comminution Collaborative (GCC) – providing an expert research and consulting base covering the full comminution process chain. Malcolm provides on-site experiential training and site reviews to empower mine staff to upgrade the productivity and their skills. This is supplemented with formal training workshops on liner design, comminution and Advanced Mine to Mill. Malcolm’s research vision is of integrated total process simulation as a tool for innovation – linking geology, mining, energy and size reduction, gangue rejection and recovery into flexible process design and process optimisation.

Malcolm supervises research students and runs three companies dedicated to advancing cutting edge technology into the mining industry. These focus around operation-relevant training; advanced mill liner design using DEM modelling; mechanistic mill modelling; introducing the latest tools into daily process control; operationalising advanced mine-to-mill implementation; and development of step-change reduction in comminution energy.

Recent News

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).

Prof. Hongzhi Yin works as an ARC Future Fellow and Professor and director of the Responsible Big Data Intelligence Lab (RBDI) at The University of Queensland, Australia. He has made notable contributions to predictive analytics, recommendation systems, graph learning, social media analytics, and decentralized and edge intelligence. He has received numerous awards and recognition for his research achievements. He has been named to IEEE Computer Society’s AI’s 10 to Watch 2022 and Field Leader of Data Mining & Analysis in The Australian's Research 2020 magazine. In addition, he has received the prestigious 2023 Young Tall Poppy Science Awards, Australian Research Council Future Fellowship 2021, the Discovery Early Career Researcher Award 2016, UQ Foundation Research Excellence Award 2019, Rising Star of Science Award (2022-2024) and 2024 Computer Science in Australia Leader Award, AI 2000 Most Influential Scholar Honorable Mention in Data Mining (2022-2024). His research has won 8 international and national Best Paper Awards, including Best Student Full Paper Award at CIKM 2024, Best Paper Award - Honorable Mention at WSDM 2023, Best Paper Award at ICDE 2019, Best Student Paper Award at DASFAA 2020, Best Paper Award Nomination at ICDM 2018, ACM Computing Reviews' 21 Annual Best of Computing Notable Books and Articles, Best Paper Award at ADC 2018 and 2016. His Ph.D. thesis won Peking University Outstanding Ph.D. Dissertation Award 2014 and CCF Outstanding Ph.D. Dissertation Award (Nomination) 2014. He has ten conference papers recognized as the Most Influential Papers in Paper Digest, including KDD 2021 and 2013, AAAI 2021, SIGIR 2022, WWW 2023 and 2021, CIKM 2021, 2019, 2016, and 2015. He has published over 300 papers with an H-index of 80, including 210+ CCF A/CORE A* and 80+ CCF B/CORE A, such as KDD, SIGIR, WWW, WSDM, SIGMOD, VLDB, ICDE, AAAI, IJCAI, ACM Multimedia, ECCV, IEEE TKDE, TNNL, VLDB Journal, and ACM TOIS. He has been the leading author (first/co-first author or corresponding author) for 200+. He has been an SPC/PC member for many top conferences, such as AAAI, IJCAI, KDD, ICML, ICLR, NeurIPS, SIGIR, WWW, WSDM, VLDB, ICDE, ICDM, and CIKM. He has been serving as Associate Editor/Guest Editor/Editorial Board for Neural Networks (JCR Q1, Chinese Academy of Sciences ranking Q1, and CCF B), Science China Information Sciences (JCR Q1, Chinese Academy of Sciences ranking Q1, and CCF A), Data Science and Engineering (DSE, JCR Q1, Chinese Academy of Sciences ranking Q2), Journal of Computer Science and Technology (JCST, CCF B), Journal of Social Computing, ACM Transactions on Information Systems 2022-2023 (TOIS, CCF A), ACM Transactions on Intelligent Systems and Technology 2020-2021 (TIST, Q1), Information Systems 2020-2021 (CORE A*), and World Wide Web 2020-2021 and 2017-2018 (CORE A, CCF B). Dr. Yin has also been attracting wide media coverage, such as The Australian, SBS Radio Interviews, UQ News, Sohu.com, Faculty News of EAIT, IEEE Computer Society, ACM Computing Reviews.

I am now looking for highly motivated Ph.D. students. The University of Queensland ranks in the top 50 as measured by the Performance Ranking of Scientific Papers for World Universities. The University also ranks 40 in the QS World University Rankings and 41 in the US News Best Global Universities Rankings. The University of Queensland is the best in Australia according to the Australian Financial Review (AFR), which has now ranked UQ in the #1 position for 2 consecutive years. Please find the following two PhD scholarships.

• https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/building-trustworthy-information-recommendation-system

• https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/build-trustworthy-information-recommendation-system

Latest News

1. [5 December 2024] Our tutorial "Graph Condensation: Foundations, Methods and Prospects" has been accepted for presentation at The Web Conference 2025.

2. [30 November 2024] I have been invited to serve as SPC for IJCAI 2025 and DASFAA 2025.

3. [29 November 2024] I was honored with The Faculty Higher Degree Research Supervision Excellence Award.

4. [19 November 2024] Congratulations to Dr. Liang Qu on being awarded his PhD degree by The University of Queensland.

5. [17 November 2024] Our research paper "Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation" was accepted by the top conference KDD 2025 (CCF A, CORE A*). Congratulations to Hechuan.

6. [24 October 2024] Our research paper "Physics-guided Active Sample Reweighting for Urban Flow Prediction" won the Best Student Full Paper Award at the top conference CIKM 2024. Congratulations to Wei!

7. [18 October 2024] We have published two survey papers in top-tier journals: ACM Computing Surveys and Science China Information Sciences. Additionally, we have recently released two new survey papers on arXiv.

   • Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures (ACM Computing Surveys 2024)

   • A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures (SCIENCE CHINA - Information Science 2024)

   • Graph Condensation: A Survey (arXiv)

   • A Survey on Point-of-Interest Recommendation: Models, Architectures, and Security (arXiv)

8. [17 October 2024] We have two research papers "PUMA: Efficient Continual Graph Learning with Graph Condensation" and "Handling Low Homophily in Recommender Systems with Partitioned Graph Transformer" accepted by the top journal TKDE.

9. [26 September 2024] We have one research paper "Distribution-Aware Data Expansion with Diffusion Models" accepted by NeurIPS 2024 (CCF A, CORE A*).

10. [23 September 2024] We have three journal papers recognized as ESI Hot and Highly Cited papers.

    • Self-Supervised Learning for Recommender Systems: A Survey (Hot and Highly Cited)

    • XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation (Highly Cited)

    • Enhancing Social Recommendation With Adversarial Graph Convolutional Networks (Highly Cited)

11. [10 September 2024] I have been recognized with the 2024 Rising Star of Science Award in Research.com and ranked #8 in Australia among Rising Stars for 2024.

12. [24 August 2024] Two of my PhD graduates have been awarded the competitive ARC DECRA Fellowship. Congratulations to Weiqing and Junliang.

13. [23 July 2024] Recently, we have released 3 comprehensive survey papers.

    • Graph Condensation: A Survey

    • Poisoning Attacks and Defenses in Recommender Systems: A Survey

    • A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures

14. [2 July 2024] I have been invited to serve as area chair at KDD 2025.

15. [27 June 2024] Our ARC Linkage Project "Building an Aussie Information Recommendation System You Can Trust" has been granted and funded.

16. [16 June 2024] I have been invited to co-chair the User modeling, personalization and recommendation track at The Web Conference 2025.

17. [6 June 2024] Recently, we have released 2 comprehensive survey papers.

    • Poisoning Attacks and Defenses in Recommender Systems: A Survey

    • A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures

18. [23 May 2024] Our project Personalized On-Device Large Language Models was shortlisted as a finalist for the 2024 iAwards.

19. [22 May 2024] Our research paper "Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion" has been accepted by the top journal TOIS 2024 (CORE A and CCF A).

20. [17 May 2024] We have 4 full research research papers accepted by the prestigious conference KDD 2024 (CORE A*, CCF A).

    • Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations

    • Graph Condensation for Open-World Graph Learning

    • Hate Speech Detection with Generalizable Topic-aware Fairness

    • Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks

Professor Justin Cooper-White is a global leader in using engineering to solve problems in biology. In addition to holding the position of Head of School and Professor of Bioengineering in the School of Chemical Engineering, he is Affiliate Professor in the AIBN, Director of the Australian National Fabrication Facility-Queensland Node, Research Director of the Herston Biofabrication Institute (a partnership between UQ and MNHHS) and co-Director of the Australian Organoid Facility at UQ. Professor Cooper-White is a past President of both the Australasian Society for Biomaterials and Tissue Engineering and the Australian Society of Rheology and held the position of CSIRO Office of the Chief Executive (OCE) Science Leader. He has previously held a Visiting Professor Fellowships at ETH Zurich (2007) and Politecnico di Milano (2012-2013). Professor Cooper-White is the Australian representative and Past President of the Asian Biomaterials Federation; an elected Fellow of and Australian representative on the International Union of Societies for Biomaterials Science and Engineering (IUSBE), and an elected Fellow and past vice President of the Queensland Academy of Arts and Sciences.

Professor Cooper-White has many past and currently active international collaborations with world leading research groups at MIT (US); Stanford (USA); ETH (Switzerland); EPFL (Switzerland); SNU (Korea); University Of Grenoble (France); Politecnico di Milano (Italy); UCL (UK); and the Max Planck Institute (Germany). He has performed contract research and consultancy work for many multinational companies, including Unilever in the UK; Nestle International, Switzerland; Rhodia, US; Inion, Finland, Syngenta, UK; and NuFarm, AU since 2001.

He is the Editor-in-Chief of APL Bioengineering (American Institute of Physics Publishing); serves or has served on the editorial boards of Rheological Acta, Soft Materials, Biomicrofluidics and the Open Biomedical Engineering Journal; and is a reviewer of major international journals, including Nature Materials, Nature Methods, Advanced Materials, Lab on a Chip, Stem Cells, Stem Cells and Development, Biomacromolecules, Tissue Engineering, Langmuir, Biomaterials and Journal of Non-Newtonian Fluid Mechanics.