Professor Chengfei Liu is a Chief Investigator at Swinburne University of Technology, where he leads the Web and Data Engineering research group and serves as the focus area leader for Knowledge and Data Intensive Systems within Swinburne’s tier-1 Centre for Computing and Engineering Software Systems (SUCCESS). His research focuses on web data management (keyword queries, uncertain data, stream data processing), advanced database systems (big data management, graph data management, RDF databases), and workflow systems (artifact-centric models, collaborative business processes). These areas address critical challenges in data integration, query optimization, and system scalability.
Dr. Jeffrey Kwan is a Lecturer in Statistics at the School of Mathematics and Statistics, University of New South Wales (UNSW Sydney). His research focuses on probability theory and stochastic processes, particularly Hawkes processes and their asymptotic behavior. He completed his PhD in 2023, specializing in ergodicity and applications for non-stationary and non-exponential Hawkes models. PhD (UNSW Sydney, 2023): Ergodicity of Hawkes processes Jeffrey's research spans probability theory, stochastic processes, financial data modeling, and data-driven legal analysis. He has published extensively on Hawkes processes, including parametric inference, ergodicity, and applications in terrorism modeling, crime analysis, and public policy. His scientific awards include the Excellence in Postgraduate Research (Statistical Society of Australia, NSW Branch, 2022), University Medal (UNSW Sydney, 2017), and multiple Dean's List recognitions. He has taught undergraduate and postgraduate courses in statistics, probability, and data science, including roles in the Business School and Faculty of Science. 2025: Chair, School of Mathematics and Statistics EDI Committee 2024: Secretary, Statistical Society of Australia (NSW Branch) 2023: Statistical Consultant at Stats Central (Mark Wainwright Analytical Centre)
Dr. Matheus Manzatto de Castro is a Researcher at the School of Mathematics and Statistics at the University of New South Wales (UNSW Sydney), Australia. He is affiliated with the Anita B. Lawrence Centre within the university's Science faculty. His research spans multiple areas of mathematical sciences, with particular focus on Pure Mathematics, Applied Mathematics, Statistics, and Computational Mathematics. As part of UNSW's research-intensive environment, his work contributes to the university's strong mathematical tradition and interdisciplinary research initiatives. UNSW Sydney, ranked among the top 20 global universities (QS Rankings 2025), provides Dr. Manzatto de Castro with access to world-class research infrastructure and collaborative opportunities across various disciplines including quantum computing, cybersecurity, and data analytics where mathematical approaches are essential. As a member of the School of Mathematics and Statistics, he participates in UNSW's research ecosystem that emphasizes both fundamental mathematical inquiry and practical applications addressing real-world challenges in climate resilience, emerging technologies, and health science.
Professor Ashley Craig is a Professor of Rehabilitation Studies (Psychosocial Health) at the University of Sydney's School of Health Sciences. His academic career includes roles as Professor of Behavioural Sciences at the University of Technology Sydney (1999–2007) and leadership positions in research ethics and administration. He specializes in psychosocial aspects of spinal cord injury (SCI), neurological disorders, and assistive technologies like the Mind Switch. His work focuses on psychological adjustment, chronic pain management, and cognitive-behavioral interventions. Craig has authored over 180 publications, including books such as *Adversity after the Crash* (2019) and *Guide for Health Professionals on the Psychosocial Care of Adults with Spinal Cord Injury* (2014). He has secured over $6M in research grants and graduated 20+ postgraduate students. Research Interests: Craig's research integrates neuroscience and clinical psychology to address SCI-related challenges. Key areas include brain wave activity changes post-SCI, efficacy of cognitive-behavioral therapy, and EEG-based assistive technologies. His work on the Mind Switch, a hands-free brain-computer interface, has advanced disability technology. He also investigates post-traumatic stress and pain management in motor vehicle crash survivors. Publications Trends: Recent articles emphasize neurorehabilitation strategies, psychological resilience, and systemic reviews of interventions for SCI patients. His work bridges clinical practice and innovation, with studies on neurofeedback for chronic pain and autonomic regulation therapies. Awards: Honorary Doctorate (SWU, 2002), Editor-in-Chief (Elsevier Journal, 2007–2011) Grants: Over $6M from ARC; $3M+ from NSW Government and Motor Accident Authority (MAA) Key Projects: StoPain Trial (EEG neurofeedback for neuropathic pain), Aus-InSCI community survey (quality of life metrics) Lab/Teams: Leads the John Walsh Centre for Rehabilitation Research and collaborates with interdisciplinary teams on spinal cord injury rehabilitation and assistive technology development.
Shoaib Akram is a Lecturer at the ANU School of Computing, Australian National University. He holds a Ph.D. in Computer Science and Engineering from Ghent University (Belgium) and an M.S. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign. He has received prestigious awards such as the Fulbright Scholarship (2007-2009) and a Marie Curie Fellowship (2010-2012). His research focuses on optimizing storage-intensive applications, computer architecture, and hardware-software interfaces, particularly for modern data-centric systems. He leads the Vertically Integrated Computer Systems (VICS) research group and has published extensively in top-tier conferences like PLDI, ASPLOS, and ISPASS. He teaches foundational computer architecture courses to over 400 students annually and restructured ANU’s computer systems curriculum. Education: Ph.D. in Computer Science and Engineering, Ghent University (Belgium) M.S. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (USA) Research Interests: Storage-Intensive Applications Non-Volatile Memory Systems Garbage Collection Algorithms Big Data Framework Optimization Performance Analysis Hardware-Software Co-Design Awards: NVMW Memorable Paper Award (2019) HiPEAC Paper Awards (ASPLOS 2023, PLDI 2018) Marie Curie Fellowship (2010-2012) Fulbright Scholarship (2007-2009) Teaching & Service: Introductory and Advanced Computer Architecture Courses Program Committee Member for ISCA, MICRO, HPCA, and ASPLOS Artifact Evaluation Committee for OOPSLA and PLDI Labs/Groups: He leads the ANU's Vertically Integrated Computer Systems (VICS) research group, focusing on interdisciplinary system-level research.
Dr. Tenielle Porter is a Strategic Research Fellow and Lecturer at Edith Cowan University (ECU), affiliated with the School of Medical and Health Sciences. She serves as Deputy Lead of the Collaborative Genomics and Translation Group and Deputy Neurological conditions Program Lead at ECU's Centre for Precision Health. Holding a PhD from ECU (2018), her research focuses on the interplay between genetics, lifestyle, and Alzheimer’s disease biomarkers, aiming to identify predictive patterns of cognitive decline and brain changes. Her work emphasizes the influence of lifestyle factors on genetic and epigenetic markers linked to neurodegenerative diseases. Her professional memberships include the Australian Society for Medical Research (ASMR) and Alzheimer’s Association International Society to Advance Alzheimer's Research and Treatment (ISTAART). She has received notable awards such as the 2019 BioinfoSummer MATHS Award and the ECR Collaboration Scheme grant. Her teaching includes courses like SCH2235 Applied Microbiology and MMS2102 Medical Microbiology. Dr. Porter’s research spans genetic and epigenetic analyses, biomarker development, and cross-trait genetic studies linking Alzheimer’s disease with other conditions. She has contributed to high-impact journals, including Nature Communications , Alzheimer’s and Dementia , and Biological Psychiatry . Her projects include validating Alzheimer’s risk genes using imaging endpoints and exploring genetic-lifestyle interactions in neurodegeneration. Grant activities include the Lilly Research Award Program (2024–2026) and Department of Health WA grants. She supervises research students in areas like genetic-physical activity relationships and Alzheimer’s genomic signatures. Her labs focus on precision health, translational genomics, and multi-omics approaches to neurodegenerative diseases.
Ehsan Shareghi Nojehdeh is an Assistant Professor in the Department of Data Science and Artificial Intelligence at Monash University and an affiliated lecturer at the University of Cambridge. He leads a research team focused on predictive models for language (text and speech), with a background in postdoctoral work at Cambridge and prior roles at UCL. His research interests include probing and augmenting Large Language Models (LLMs), reasoning in legal contexts, safety of multimodal models, speech/text translation, and self-supervised learning. Education: PhD in Computer Science (Scalable Non-Markovian Sequential Modelling) from Monash University (2017). Professional roles include Deputy Course Director for the Master of AI program at Monash, service on academic committees (ECA Committee, 2022–2023), and senior reviewing roles at major conferences (ACL2025, EMNLP2023). He teaches units like FIT5217 Natural Language Processing and FIT5212 Data Analysis for Semi-structured Data. Key projects include a Paul Ramsay Foundation-funded study on media narratives around disadvantage in Australia (2022–2023). His work addresses UN SDGs through advancing education and AI ethics. Research collaborations span global institutions, with a focus on knowledge-intensive tasks like biomedical domain applications, graph-to-text generation, and generative model disentanglement. Publications emphasize safety, multimodal capabilities, and logical reasoning with LLMs, with recent work appearing in ACL, EMNLP, and NAACL venues. His team investigates LLM shortcomings, including alignment with human judgment, speech-specific vulnerabilities, and tool-based reasoning strategies.
Sarah Hegarty is a Data Scientist affiliated with the School of Business, Law and Entrepreneurship at Swinburne University of Technology , where she contributes to data analysis, software development, and research projects. Since 2017, she has been part of the Economics of Innovation research group , specializing in data-intensive astrophysics , economic databases , and data-driven agricultural economics .
Matthias Schlesewsky is a Professor at the University of South Australia (UniSA), affiliated with UniSA Justice and Society. His research focuses on cognitive neuroscience, neurophysiology, and language processing, with a particular emphasis on EEG analysis and mindfulness interventions. He leads studies on how mindfulness training impacts resting-state EEG parameters in high-demand cohorts, such as military personnel. His work also explores the neurobiological foundations of syntax processing, predictive mechanisms in memory, and the role of individual alpha frequency in cognitive tasks. Key affiliations include the Cognitive Neuroscience Laboratory and the Australian Research Centre for Interactive and Virtual Environments. His research integrates experimental psychology, neuroimaging, and computational modeling to investigate language comprehension, attention, and decision-making. Notable projects include studies on EEG-based cognitive workload monitoring in military training and the effects of mindfulness on dynamic task performance. His articles highlight interdisciplinary approaches, combining EEG, ERP, and behavioral data to understand neural mechanisms underlying language, memory, and attention. Collaborations span institutions like Georgetown University, the University of Miami, and the Defence Science and Technology Group.
Ian Gordon is a Professor of Statistics at the University of Melbourne, serving as Director of the Statistical Consulting Centre. With over 40 years of experience, his expertise spans applied statistical work, meta-analysis, and statistical education. He is an Accredited Statistician (AStat) and former President of the Statistical Society of Australia (2022–2024). His research focuses on statistical methodologies, including sample size determination and applications in health, cardiovascular research, and social epidemiology. Dr. Gordon has extensive experience as an expert witness in court cases across multiple jurisdictions, contributing to high-profile cases such as racial discrimination litigation and class actions involving medical devices. He has authored over 350 consulting reports and holds an h-index of 31. His teaching includes courses on statistical methods, R programming, and critical thinking with data. He co-developed innovative breadth subjects like Thinking Scientifically and contributes to the Master of Applied Data Analytics programs. His work emphasizes bridging statistical theory with practical applications in healthcare, justice, and education. Key Awards: C. Oswald Prize (2023), AStat accreditation. Grants: ARC Discovery, ARC Linkage, NHMRC grants as a Chief Investigator. Labs/Teams: Statistical Consulting Centre, collaborating on tailored short courses and industry partnerships.
Rajib Rana is a Professor of Computer Science at the University of Southern Queensland, affiliated with the School of Mathematics, Physics and Computing. He holds a PhD from the University of New South Wales (UNSW), completed in 2011. His research focuses on AI-driven solutions for mental health, speech emotion recognition, and healthcare informatics, with a strong emphasis on machine learning, deep learning, and domain adaptation techniques. His work spans clinical applications, wearable sensor systems, and mobile health technologies. Dr. Rana has supervised numerous doctoral candidates, including studies on AI tools for youth mental health interventions, adversarial attack robustness in speech emotion systems, and data analytics for school mental health monitoring. His research outputs include over 50 peer-reviewed articles, with notable contributions in IEEE Transactions on Affective Computing, Computers in Biology and Medicine, and other leading journals. His technical expertise includes federated learning, compressive sensing-based encryption for IoT, and context-aware affect sensing via smartphones. He collaborates widely with clinical partners and industry, addressing challenges like mental health triage prioritization and ICU admission prediction during pandemics. His work bridges computational methods with real-world healthcare and educational applications.
Alok Chowdhury is a researcher affiliated with Queensland University of Technology (QUT), specializing in sensor-based physical activity monitoring and machine learning applications in health. He completed his PhD in 2018 with a thesis titled Sensor-based prediction of physical activity and its impacts using machine learning . His research focuses on developing algorithms for energy expenditure estimation, physical activity recognition, and wearable sensor data analysis. Key contributions include studies on preschool children's activity patterns, ensemble learning for activity classification, and visualization tools for sensor data. He has published in journals like PLoS ONE , Medicine and Science in Sports and Exercise , and Sensors , and conference proceedings including IEEE and ACM events. His work intersects biomedical engineering, health informatics, and computer science.
Alan Herschtal is a Senior Biostatistician and Research Fellow at Monash University's Clinical Trials Centre. He specializes in clinical trials methodology across Oncology and Cardiovascular disease. His key responsibilities include statistical design, analysis, reporting, and grant preparation. He holds leadership roles in two active research projects: 'Co-design and evaluation of a resource to improve patient-clinician communication in rural chronic disease settings' (2024–2027) and 'Flexible Modelling of Count Outcomes in Clinical Trials' (2024). His research focuses on Flexible parametric survival modelling and Modelling of zero-inflated data , with notable contributions to imaging advancements in prostate cancer (PSMA PET-CT) and lung cancer therapies (SABR vs. standard radiotherapy). His work aligns with UN Sustainable Development Goals related to health equity and innovation. Recent articles highlight advancements in trial design for eating disorders, pulmonary function post-radiotherapy, and cardiovascular risk screening. Projects emphasize improving rural healthcare communication and statistical methodologies for count data in clinical research. He collaborates internationally and leads grant applications, with a focus on translational research linking statistical innovation to clinical outcomes. His expertise bridges biostatistics, clinical oncology, and public health initiatives.
Mohammed Eunus Ali is a Senior Lecturer in the Department of Software Systems & Cybersecurity within the Faculty of Information Technology at Monash University, Australia. He holds a PhD in Computer Science and Software Engineering from the University of Melbourne and has previously served as a Professor at the Bangladesh University of Engineering and Technology (BUET), where he led a research group in Data Science and Engineering for over a decade. He has also held research positions at Monash University, Swinburne University, the University of Melbourne, and RMIT University. PhD : Computer Science and Software Engineering, University of Melbourne (2010) M.Sc. Engg. : Computer Science and Engineering, Bangladesh University of Engineering and Technology (2002) B.Sc. Engg. : Computer Science and Engineering, Bangladesh University of Engineering and Technology (1999) Dr. Ali’s research spans data management, analytics, and learning , with a strong focus on spatio-temporal data, geo-social networks, and multimodal high-dimensional data . His work enables applications in urban computing, intelligent transportation systems, and smart, sustainable cities . In recent years, he has expanded into Generative AI and large language models (LLMs) , exploring their role in enhancing geo-spatial query processing, SQL generation, and data engineering tasks. His publications appear in top-tier venues such as ACL, TKDE, VLDB, ICDE, SIGSPATIAL, and IEEE Access . His recent publications reflect a strong trend toward AI-driven solutions for real-world spatial and health problems , including blood glucose prediction for diabetics, seismic intensity forecasting, eco-friendly route planning, and LLM-based code generation. These works demonstrate a convergence of deep learning, spatio-temporal analytics, and real-world system design . Scientific Awards: Bangladesh University Grants Commission Award (2012) ADC Best Poster Award (2016) SSTD Best Demo Award (2017) ADC Best Paper Award (2022) Dr. Ali actively contributes to the research community as a Program Committee Member for premier conferences including SIGMOD, VLDB, ICDE, and SIGSPATIAL . He is a Senior Member of the ACM and currently supervises PhD students, focusing on cutting-edge topics in data science and AI. His collaborative research network spans institutions in Australia and Bangladesh, contributing to advancements in both academic and applied domains. His work aligns with the UN Sustainable Development Goals , particularly in the areas of sustainable cities, innovation, and quality education.
Dr. Hugh Davies is a Senior Research Fellow at the University of New England's School of Environmental and Rural Science. His research focuses on biodiversity conservation, feral animal management, and fire ecology in Australian ecosystems. He holds a PhD from the University of Melbourne and a Bachelor of Environmental Science (First Class Honours) from Monash University. His research interests include: Biodiversity conservation in northern Australian savannas Impacts of feral cats and foxes on native mammals Fire regime optimization for ecosystem health Indigenous engagement in land management He leads major grants including: ARC Linkage Grant: 'Cat management guided by Country' ($578,317) ARC Discovery Grant: 'Is dispersal the key to maximising threatened species conservation under contemporary fire regimes?' ($417,000) Resilient Landscapes NESP Hub: 'Best practice fox control in Booderee National Park' ($691,600) His publications primarily focus on conservation biology, fire ecology, and invasive species management, utilizing field studies, genetic analysis, and simulation modeling to address mammal declines in northern Australia. He currently supervises 4 PhD students.
