Find Academic Supervisors

• Climate change impacts in Antarctic terrestrial ecosystems
• Biological consequences of extreme climate events
• Remote biological monitoring technology development
• +7 more

Dr. Krystal Randall is a Research Fellow at the University of Wollongong's School of Earth, Atmospheric and Life Sciences (SEALS), specializing in Antarctic terrestrial ecosystems. Her work integrates spatial biology, microclimate modeling, and field monitoring to study plant-climate interactions at ultra-fine scales. Her research focuses on climate change impacts in Antarctic ecosystems , particularly how extreme events affect moss communities. She develops novel technologies including drone-based remote sensing systems, MossCam, and smart sensors for remote biological monitoring. Her fieldwork spans Australia's alpine regions and multiple Antarctic locations, collecting critical data on physical-biological interactions in polar environments. Key research trends from her publications include the application of drone hyperspectral imaging and AI for Antarctic vegetation monitoring , microclimate modeling at unprecedented scales, and physiological studies of moss survival in extreme conditions. Her work bridges spatial biology, climate science, and technology development. Scientific recognition includes: Antarctic Science Foundation Ambassador (2023) She coordinates courses including BIOL241 (Biodiversity of Terrestrial Organisms) and BIOL362 (Ecophysiology), and supervises PhD research on Antarctic moss responses to extreme climate events. Her funded projects include the ECO-ANTARCTICA observing system and internal grants for technology development. Randall leads field campaigns developing new monitoring methodologies while contributing to global datasets like SoilTemp.

• Computational Neuroscience
• Neuroimaging
• Connectomics
• +10 more

Professor Michael Breakspear is an internationally recognized leader in computational neuroscience, brain imaging, and translational neurotechnology at the University of Newcastle's School of Psychological Sciences. His research bridges complex systems theory, mathematical modeling, and clinical neuroscience to advance understanding of brain dynamics in health and disease through interdisciplinary collaboration across mathematics, physics, neuroimaging, psychiatry, and artificial intelligence. Professor Breakspear holds a Doctor of Philosophy from the University of Sydney, along with multiple undergraduate degrees including a Bachelor of Medicine and Bachelor of Surgery. His academic journey includes professorial appointments at the University of Sydney (School of Physics), University of Queensland (School of Psychiatry), and University of Western Sydney (School of Psychiatry), where he progressed from Post-doctoral Research Fellow to Associate Professor. Current: Professor, University of Newcastle, School of Psychological Sciences 2017-present: Principal Research Fellow, National Health & Medical Research Council 2017-present: Senior Scientist and Head, QIMR Berghofer Medical Research Institute 2012-2017: Professor (adjunct), University of Sydney, School of Physics 2011-present: Professor (adjunct), University of Queensland, School of Psychiatry 2007-2012: Associate Professor, University of Western Sydney, School of Psychiatry Professor Breakspear's research program integrates expertise across mathematics, physics, neuroimaging, psychiatry, and artificial intelligence. His core expertise includes computational neuroscience (modeling brain dynamics using nonlinear systems theory), neuroimaging and connectomics (pioneering methods to analyze brain networks), brain disorders and mental health (applying computational models to disorders like schizophrenia and bipolar disorder), and neurotechnology and AI (developing machine learning techniques for imaging biomarkers). His recent publications demonstrate a strong focus on brain dynamics, neuroimaging techniques, and applications to psychiatric and neurological disorders. His work spans theoretical frameworks to clinical applications, with particular emphasis on understanding the neural basis of mood disorders, Alzheimer's disease, and psychosis, employing advanced computational approaches to uncover fundamental principles of brain organization and dysfunction. Senior Researcher Award (2017) Principal Research Fellow, National Health & Medical Research Council (2017-present) Professor Breakspear actively collaborates with clinical researchers, engineers, and technology developers to translate theoretical frameworks into practical diagnostic and therapeutic innovations. He provides leadership in training programs at the nexus of neuroscience, mathematics, and data science, fostering the next generation of interdisciplinary researchers through mentorship and collaborative projects that bridge theoretical and clinical domains.

Xiaoyang WangView profile

Senior Lecturer

• Graph Processing
• Graph Neural Networks
• Spatial Data Processing
• +10 more

Xiaoyang Wang is a Senior Lecturer in the School of Computer Science and Engineering (CSE) at the University of New South Wales (UNSW). He holds a Bachelor's and Master's degree in Computer Science from Northeastern University, China, and earned his PhD from CSE UNSW. Dr. Wang's research focuses on database systems with a special emphasis on query processing and data mining on large-scale graph, spatial, and streaming data. His expertise extends to data-driven machine learning, smart contract analysis on blockchain, and FinTech with financial network analysis. His work spans Graph Processing, Graph Neural Networks, Spatial Data Processing, AI for Databases (AI4DB), Database for AI (DB4AI), and FinTech applications. His publication record shows significant contributions to the field with 7 book chapters, 56 journal articles, 61 conference papers, 7 edited conference proceedings, and 4 conference abstracts. Recent publications (2022-2025) demonstrate his strong research trajectory in advanced graph processing techniques, neural network applications, and innovative database approaches. Key themes include hierarchical contrastive learning, robust attack frameworks, temporal graph processing, influence maximization, knowledge graph-enhanced reasoning, and rumor mitigation. Dr. Wang actively recruits PhD students interested in pursuing research in related fields and encourages current undergraduate and master's students at UNSW to contact him about research opportunities. He maintains an active research agenda with practical implications for industries dealing with large-scale network data, financial technology applications, and data-intensive systems. He can be reached at xiaoyang.wang1@unsw.edu.au and is located in Engineering building K17-501D at UNSW.

Grant MontgomeryView profile

Professor

• Genetics
• Genomics
• Reproductive Disorders
• +4 more

Professor Grant Montgomery is a leading academic at the University of Queensland (UQ), serving as Director of the UQ Genome Innovation Hub and Group Leader of the Genomics of Reproductive Disorders at the Institute for Molecular Bioscience (IMB). His primary focus is on understanding the genetic and epigenetic basis of reproductive disorders, particularly endometriosis, through large-scale genomic studies and functional analyses. His work integrates multi-omics data to identify disease mechanisms and develop translational solutions. Research Interests: Genetic and epigenetic regulation of endometrial function Systems genetics approaches to study complex diseases Functional validation of genomic risk variants Development of clinical tools like eQTL/mQTL browsers Multi-omics integration for disease biomarker discovery Recent Articles: Highlighting endometriosis genetics, comorbidity mechanisms, and novel diagnostic approaches. Key themes include genetic risk stratification, epigenetic dysregulation, and translational applications of genomic data. Collaborations: Active partnerships with institutions globally, including University of California, San Francisco, Oxford Endometriosis CaRe Centre, and Monash University. Major consortia include International Endometriosis Genetics Consortium and Reprogen Consortium. Advising & Training: Supervises PhD students focusing on endometrial cell biology, epigenetic regulation, and computational genomics. Provides training opportunities in functional genomics and systems biology. Labs/Teams: Leads a multidisciplinary team with expertise in molecular biology, bioinformatics, and clinical research. Maintains cell culture facilities and single-cell sequencing capabilities.

• Database Management
• Spatial-Textual Data Processing
• Heterogeneous Data Usability
• +6 more

Professor Zhifeng Bao is a faculty member at RMIT University's School of Computing Technologies. His research focuses on enhancing data usability across heterogeneous domains, including structured, unstructured, and spatial-temporal data. His work spans database management, keyword search optimization, social network analysis, and spatio-textual data processing. He coordinates the course COSC1169: Intranet and Internet Data Engineering and supervises PhD/Masters students in projects such as trajectory data processing, data asset valuation, and edge computing optimization. Research interests emphasize improving data accessibility and efficiency through methodologies like query relaxation, visual analytics, and provenance tracking. His recent projects include cost-effective edge node placement, traffic accident risk prediction, and differentially private federated learning. Teaching and supervision activities highlight a commitment to bridging theory and practical data engineering challenges.

Marnie CampbellView profile

Professor

• Marine Biosecurity
• Invasive Species Management
• Environmental Policy
• +3 more

Professor Marnie Campbell serves as the Executive Dean of the School of Science at Edith Cowan University (ECU), overseeing disciplines including Biology, Chemistry, Computing, Cyber Security, and Mathematics. She leads four research centers: the Centre for Artificial Intelligence and Machine Learning, the Centre for Marine Ecosystems Research, the Conservation and Biodiversity Research Centre, and the Centre for Securing Digital Futures. Her academic journey includes a BSc(Hons) and PhD from Murdoch University (2000). Marnie’s career spans 18 years in higher education, with 14 years in leadership roles, including Head of the School of Life and Environmental Sciences at Deakin University. She balances active research with policy translation, emphasizing stakeholder collaboration to address environmental challenges. With 12 years in non-academic roles (government, consultancy, CSIRO), she applies cross-sectoral insights to academic leadership. Her research focuses on marine biosecurity, invasive species management, and environmental policy. Notable contributions include frameworks integrating social, cultural, and ecological values in biosecurity and strategies to mitigate marine debris impacts. She has pioneered educational initiatives aligning academic programs with industry/community needs. Marnie’s honors include the 2007 Peter Morris Prize for maritime biosecurity contributions and a Queensland Smart Futures Fellowship (2012–2015). She advises international organizations like the UN and has led projects in the Galapagos Islands and Palau. Her work emphasizes bridging science and policy to address global challenges like biodiversity loss and climate change. Her leadership extends to strategic initiatives like ECU’s Centre for People, Place & Planet. She advocates for innovative education and adaptive governance models to prepare future environmental leaders. Current efforts focus on AI applications in ecological research and securing digital futures amid emerging threats.

• Urban and Regional Planning
• Housing Policy
• Human Geography
• +3 more

Dr. Margaret Reynolds serves as a Senior Research Fellow at Swinburne University of Technology's School of Social Sciences, Media, Film and Education. With ORCID identifier 0000-0003-2988-4279, she maintains an active research profile focused on critical housing issues affecting Australian communities, particularly older populations. Her work bridges academic research with practical policy applications through collaborations with government bodies and non-profit organizations. Reynolds' research interests center on urban and regional planning , housing policy , and human geography , with specific expertise in older people's housing security, homelessness dynamics, and sustainable urban development. Her work examines how housing precariousness affects vulnerable populations, particularly aging Australians navigating complex eligibility gaps in housing assistance programs. Through rigorous spatial analysis and longitudinal studies, she investigates the changing geography of homelessness and the structural drivers behind housing insecurity across Australian states and territories. Her recent publications reveal a strong focus on state-by-state analyses of older people's housing precariousness , examining regional variations in housing challenges from Queensland to Tasmania. Reynolds' work consistently connects housing issues with broader sustainable development goals, particularly SDG 11 (Sustainable Cities and Communities). Her research employs mixed methods including spatial analysis, policy evaluation, and demographic studies to understand housing market dynamics and their social impacts. Reynolds actively secures competitive research funding, currently leading multiple projects including Measuring Climate Change Vulnerability in Australia's Housing System (2025-2027) and Housing futures: ideal models for private rental systems beyond 2025 (2025-2026). Her grant portfolio demonstrates sustained funding from the Australian Housing and Urban Research Institute and Housing for the Aged Action Group, reflecting the policy relevance of her work. Though currently unavailable for supervision, her collaborative approach is evident through numerous co-authored publications with researchers like Wendy Stone, Phillipa Veeroja, and Shaun Parkinson.

• Child Health and Development
• Epidemiology
• Public Health Surveillance
• +3 more

Associate Professor Catherine Chittleborough is an epidemiologist and Deputy Head of the School of Public Health at the University of Adelaide, affiliated with the BetterStart Health and Development Research initiative. She holds a joint appointment in the Faculty of Health and Medical Sciences. Previously, she worked at SA Health for a decade and completed a postdoctoral position at the University of Bristol. Her research focuses on reducing health inequalities in child development, leveraging causal epidemiological methods and population data from longitudinal cohorts. She teaches undergraduate public health and epidemiology courses. Education: Postdoctoral training at the University of Bristol (2009-2011) Extensive prior experience at SA Health (1990s-2010) Research Interests: Child health equity, causal epidemiology, data linkage studies, early childhood development, and interventions targeting family support programs. Her work emphasizes identifying at-risk children to improve preventive strategies. Grants & Funding: EMPOWER Project (NHMRC AUD 2.4M, 2016-2020) SA Health Data Linkage Studies (NHMRC AUD 453K, 2013-2016) Child Maltreatment and School Outcomes (Channel 7 AUD 69K, 2016-2018) Teaching: Coordinator for PUB HLTH 1001, HLTH SC 3103, and other public health modules. Active in curriculum design and delivery across undergraduate programs. Professional Activities: Chair, School of Public Health Learning and Teaching Committee Member of multiple advisory boards and review panels Labs/Teams: Lead researcher in BetterStart Health and Development Research, collaborating on interdisciplinary projects to improve child health outcomes through policy and practice.

• Artificial Intelligence
• Machine Learning
• Spatial Reasoning
• +3 more

Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.

• Biosecurity
• Veterinary Epidemiology
• Statistical Modeling
• +4 more

Dr. Devindri Perera is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) within the Faculty of Science and Engineering. He is also affiliated with the Office of the Provost, demonstrating administrative and academic leadership roles. His research focuses on interdisciplinary areas including biosecurity systems, veterinary epidemiology, statistical modeling, and genomics. Dr. Perera's work spans environmental science (biosecurity border management), veterinary medicine (equine health and endocrinology), and computational methods (data clustering, statistical algorithms). His biosecurity research emphasizes risk assessment and spatial-temporal analysis of non-indigenous species, while his veterinary studies investigate equine physiology and disease mechanisms. In genomics, he contributes to identifying genetic markers for neurological disorders like multiple sclerosis. His publications from 2006–2023 reflect a strong focus on statistical methodologies in interdisciplinary contexts, including genome-wide association studies, algorithm validation for genotyping, and applied econometric models. This demonstrates a blend of theoretical rigor and practical problem-solving across diverse domains. Though no specific awards or grants are listed in this profile, his prolific publication record and cross-disciplinary approach highlight sustained academic engagement. His research collaborations span institutions globally, addressing both environmental and biomedical challenges.

• Applied Econometrics
• Applied Statistics
• Housing Economics
• +3 more

Ranjodh Singh is a Senior Lecturer at the School of Accounting, Economics and Finance within the Faculty of Business and Law at Curtin University. He holds a BSc (Hons) and PhD in disciplines relevant to his research focus. His teaching responsibilities include undergraduate and postgraduate courses in Data Analytics and Econometrics, and he supervises Honours, Masters, and PhD students in these areas. Ranjodh’s research interests center on Applied Econometrics , Applied Statistics , and Housing Economics . His work explores topics such as housing market dynamics, policy impacts on mental wellbeing, Indigenous mobility, and nonlinear econometric modeling. Recent studies include analyzing rental subsidy effectiveness, cannabis-tobacco consumption linkages, and post-pandemic housing demand shifts. His publications span leading journals like Housing Studies , International Journal of Housing Policy , and Journal of Population Economics . He frequently collaborates with researchers across disciplines, including economists, statisticians, and sociologists. His research has addressed policy-relevant issues such as rental affordability, remote infrastructure planning, and pandemic-driven economic shifts. Ranjodh’s contributions extend to major research initiatives like the AHURI Final Reports series, focusing on housing stress and Indigenous community needs. His methodologies blend traditional econometrics with machine learning advancements, as seen in his work on nonlinear models and forecast combinations.

• Computer Vision
• Metric Learning
• Image Generation
• +3 more

Dr. Xinyu Zhang is a Research Fellow at the Australian Institute for Machine Learning (AIML), University of Adelaide's Faculty of Sciences, Engineering and Technology. Her research bridges computer vision and machine learning, focusing on image/video generation, self-supervised learning, and multimodal retrieval for human-centric AI applications. Zhang's current investigations include: Causal representation learning and multimodal integration Bayesian deep learning frameworks Video generation with temporal consistency Lightweight detection transformers Unsupervised person re-identification Analysis of recent publications reveals strong emphases on generative modeling innovations (especially video synthesis), efficient transformer architectures for real-time applications, and self-supervised representation learning. Her work frequently addresses the alignment between latent representations and human perception across vision-language tasks. Dr. Zhang co-supervises graduate students on projects involving multi-agent 3D scene generation and knowledge transfer in low-supervision learning. She serves as conference reviewer for premier venues including CVPR, ICCV, and NeurIPS, contributing to the advancement of computer vision research.

Bryan BoruffView profile

Associate Professor

• Environmental Geography
• Geographic Information Systems (GIS)
• Remote Sensing
• +4 more

Associate Professor Bryan Boruff is affiliated with the University of Western Australia (UWA), specifically within the School of Agriculture and Environment. His roles include Specialisation Coordinator for Sensing and Spatial Data Science in the Master of Environmental Science program. He holds a PhD from the University of South Carolina and has expertise in Geographic Information Systems (GIS), Remote Sensing, and environmental hazard analysis. Education: BA, MA Flor.At. PhD from University of South Carolina His research focuses on applying GIS and Remote Sensing to environmental hazards, agriculture, renewable energy, population health, and urban planning. Recent work includes studies on the impact of green spaces on children’s health and the development of spatial tools for environmental management. Recent articles explore topics such as the association between coastal proximity and child development, land use mapping in Fiji, and the role of urban vegetation in mitigating heat. These studies highlight his interdisciplinary approach, blending geospatial technologies with public health and environmental sustainability. He has secured significant funding, including over $1.6 million from ACIAR for climate-smart landscapes research and a $1.7 million National Environmental Science Program grant. Collaborations span international projects in Fiji, Cambodia, and Pakistan, addressing disaster recovery and climate resilience. Boruff is involved in initiatives like the UWA Oceans Institute and the Institute of Agriculture. His teaching includes advanced GIS and remote sensing courses, contributing to the next generation of spatial data scientists.

Shixun HuangView profile

Lecturer

• Data Mining
• Machine Learning
• Algorithm Design
• +3 more

Dr. Shixun Huang is a Lecturer in the School of Computing and Information Technology at the University of Wollongong, Australia. He holds a PhD from RMIT University and specializes in data mining, machine learning, and optimization algorithms for high-dimensional data problems. His research develops efficient algorithms for data discovery, similarity search, and network analysis. Current projects focus on optimized data acquisition strategies for machine learning, cost-effective labeling for graph neural networks, and cardinality estimation in high-dimensional databases. Methodologically, he combines combinatorial optimization with machine learning techniques. Dr. Huang supervises graduate research on diffusion models for medical imaging, graph prompt learning, and image captioning systems. His honors include multiple best paper awards at top database conferences and recognition for teaching excellence (College Top Course Award at RMIT). Recent publications address dataset distinctiveness maximization (WWW 2025), high-dimensional similarity search (VLDB 2025), and edge computing optimization (2024). Earlier foundational work established new approaches for influence maximization in social networks and temporal graph representation learning.

Daniel IerodiaconouView profile

Professor

• Marine Ecology
• Environmental Management
• Geology
• +6 more

Professor Daniel Ierodiaconou is a marine ecologist at Deakin University, where he serves as Professor in Marine Science and leads the Deakin Marine Mapping Group. He acts as Victorian Node Leader for the Integrated Marine Observing System (IMOS), Board Director for the Great Ocean Road Coast and Parks Authority, and Coastal Lead Scientist for the CoastRI Initiative. His work combines multi-disciplinary approaches to advance marine ecosystem-based management. Doctor of Philosophy, Deakin University Bachelor of Science (Aquatic Science), Deakin University Bachelor of Science (Fisheries Management & Aquaculture), Deakin University Daniel's research focuses on Benthic Habitat Mapping , Marine Protected Areas , and Coastal Process Monitoring . His work integrates Remote Sensing , Image Classification , and Change Detection techniques to inform marine conservation and climate adaptation strategies. Recent publications highlight advancements in Seafloor Habitat Classification , Coastal Erosion Modeling , and Seagrass Restoration . Scientific awards include: 2020 Eureka Prize for Innovation in Citizen Science 2020 Victorian Coastal Award for Innovative Applied Research 2018 Victorian Coastal Award for Partnership Research 2009 Tall Poppy Award Daniel supervises 10 current doctoral students and has advised 16 PhD completions. His grants portfolio exceeds $7 million, including a $5 million NCRIS-funded CoastRI Coastal Monitoring Network. He specializes in integrating Geospatial Technologies with Marine Conservation through his leadership in citizen science drone programs and Victoria's first wave buoy network.