جست‌وجوی استاد و پژوهشگر

Simon Langمشاهده پروفایل

استاد

• Sedimentology
• Stratigraphy
• Petroleum Geology
• +۶ مورد دیگر

Professor Simon Lang is a Professor of Practice in Energy Geoscience and Director of the Centre for Energy Geoscience at the University of Western Australia's School of Earth Sciences. He holds a PhD in Geology and Mineralogy from the University of Queensland. His career spans over 40 years across academia, industry, and government, focusing on sedimentology, stratigraphy, petroleum geology, and carbon sequestration. Education: PhD (1994, University of Queensland), BSc Honours (completed during his time at the Geological Survey of Queensland). Research Interests Sedimentology of modern and ancient depositional systems Seismic stratigraphy and reservoir characterization Basin analysis and CO2 sequestration Quantitative reservoir analogues (QRA) Article Trends His recent publications emphasize advanced seismic stratigraphic techniques, bathymetry mapping, and the integration of 3D seismic data to understand sedimentary architecture. Key themes include shelf-margin dynamics, fault timing uncertainties, and the application of geological analogues to reservoir modeling. Awards & Honors Barry Goldstein Medal (2024) for Innovation in Geoscience Australian National Geoscience Champion (2023) PESA Distinguished Lecturer (2010) Grants & Advising He leads industry-funded consortia such as the QRA-Conoco project and has contributed to ARC grants on Proterozoic rift basins. His advising spans institutions like QUT, University of Adelaide, and UWA. Labs & Teams Directs the Centre for Energy Geoscience, focusing on quantitative seismic stratigraphy and reservoir analogues. Collaborates globally through initiatives like the National Seismic Derived Bathymetry Asset.

John Ormerodمشاهده پروفایل

دانشیار

• Statistics
• Bayesian Inference
• Data Mining
• +۴ مورد دیگر

Associate Professor John Ormerod is affiliated with the Statistics Research Group at the School of Mathematics and Statistics , University of Sydney . His research focuses on advanced statistical methodologies, including Variational Bayes , Generalized Linear Mixed Models , Splines , and Missing Data analysis. Current research students: Rajan Shankar and Jackson Zhou Key research strengths: Precision and Digital Health , Data and Decisions , National Security His work spans computational statistics, bioinformatics, and applications in health and biological data. Recent publications emphasize scalable Bayesian inference, variable selection, and single-cell data analysis frameworks. Grants include multiple Australian Research Council (ARC) Discovery Projects (2021, 2017, 2012, 2010) supporting research in feature selection, network modeling, and computational efficiency. He has supervised projects on modern regularization techniques and fast expectation propagation , contributing to BMC Bioinformatics , Bioinformatics , and Journal of Computational and Graphical Statistics .

Matthew Tigheمشاهده پروفایل

استاد

• Environmental Modelling
• Pollution Science
• Chemometrics

Matthew Tighe is a Professor of Ecosystem Modelling in the School of Environmental and Rural Science at the University of New England. With expertise in environmental chemistry and statistical analysis, his research addresses pollution dynamics in terrestrial and aquatic systems. Key research areas include: Microplastic pollution pathways in protected environments Antimony and arsenic speciation in contaminated ecosystems Chemometric applications in environmental forensics His publications demonstrate advanced techniques in pollution tracking, including microplastic source identification in recreational areas and metal transformation kinetics in soils. Recent work examines contaminant interactions with climate extremes and innovative sensing technologies for soil characterization. Honors include multiple university teaching awards and editorial roles for scientific journals.

Annalie Dorphمشاهده پروفایل

پژوهشگر ارشد

• Wildlife Management
• Quantitative Ecology
• Invasive Species Ecology
• +۴ مورد دیگر

Dr. Annalie Dorph serves as a Postdoctoral Research Fellow in Predator Ecology within the School of Environmental and Rural Science at the University of New England's Faculty of Science, Agriculture, Business and Law. Based at the Armidale campus, she conducts research through the Practical Ecology, Science and Technology (PEST) Research Group, focusing on statistical approaches to complex ecological challenges. Her educational background includes a BSc (Honors) in Zoology from the University of New England and a PhD in Science from the University of Melbourne. These qualifications underpin her expertise in quantitative ecological methods and wildlife management. Dorph's research centers on invasive species ecology, particularly developing improved detection and management strategies for feral cats and European red foxes across Australian landscapes. She integrates statistical modeling with expert knowledge to create practical decision-support tools for land managers. Her work spans fire ecology, wildlife conservation, and the intersection of human activities with ecosystem dynamics, emphasizing multi-scale landscape patterns and their impacts on biodiversity. Her publication record demonstrates consistent output in high-impact journals, with recent work focusing on feral predator management, wildfire dynamics, and mammal community ecology. The research shows strong thematic continuity in applying quantitative methods to conservation challenges, particularly in fire-prone Australian ecosystems. Dorph actively supervises Honours and PhD students in native and invasive species management. Her research is supported through significant grants including the National Environmental Science Program – Resilient Landscapes Hub and NSW Environmental Trust Major Grants, reflecting the practical relevance of her work to environmental management. She maintains active participation in professional organizations including the Ecological Society of Australia, Australian Wildlife Management Society, Bayesian Network Modelling Association, and the National Environmental Science Program – Resilient Landscapes Hub, demonstrating strong engagement with both academic and applied conservation communities.

Matthias Boerمشاهده پروفایل

دانشیار

• Landscape Ecology
• Fire Regimes
• Climate Change Impacts
• +۵ مورد دیگر

Matthias Boer is an Associate Professor and Director of the NSW Bushfire and Natural Hazards Research Centre at the Hawkesbury Institute for the Environment (HIE), Western Sydney University. He holds a PhD in Physical Geography (1999) and MSc in Physical Geography and Landscape Ecology (1986) from Utrecht University. His research focuses on fire regimes, climate change impacts on ecosystems, and spatial ecology in fire-prone environments. Affiliations: NSW Bushfire Risk Management Research Hub, Terrestrial Ecosystems Research Network Education: PhD (1999), MSc (1986) from Utrecht University Research interests include fire ecology, hydrology of arid environments, and the interplay between climate change and vegetation dynamics. He has led over 30 grants since 2018, including projects on eucalypt dieback, lightning detection systems, and fire risk prediction. Notable awards include the 2021 Eureka Prize and 2023 Excellence in Research Impact Award. Recent work explores machine learning for fire prediction, carbon dynamics in forests, and the physiological underpinnings of plant resilience. Collaborates extensively with institutions like the NSW Department of Planning and Environment, ARC, and international universities.

Keith Pembletonمشاهده پروفایل

استاد

• Agricultural Systems Modelling
• Crop Modelling
• Agronomy
• +۷ مورد دیگر

Professor Keith Pembleton is the Director of the Centre for Sustainable Agricultural Systems at the University of Southern Queensland (USQ), affiliated with the Institute for Life Sciences and the Environment. He holds a BAgSc(Hons) from the University of Queensland (2005) and a PhD from the University of Tasmania (2010). His career includes roles as Professor (2024–present), Associate Professor (2019–2023), and Senior Lecturer (2017–2019) at USQ, with prior experience as a Senior Research Fellow and Research Fellow. His research focuses on integrating computational tools like APSIM and AI into agricultural decision-making, addressing challenges in crop modeling, catchment systems, and climate adaptation. Research interests span agricultural systems modeling, crop and pasture agronomy, and climate resilience. He has led over 15 grants, including projects on sesame adoption in farming systems, soil constraint management, and drought resilience. Awards include the 2011 Minister for Agriculture award and Fulbright Scholarships. Professor Pembleton supervises doctoral and master's research on topics like farming systems modeling and ICT adoption. His 100+ publications include work on APSIM validation, tropical pasture growth, and machine learning applications in agriculture. He is a Fellow of the Higher Education Academy and active in professional organizations like the Australian Society of Agronomy.

• Agricultural Climate Risk Modeling
• Environmental Finance
• Geospatial Intelligence
• +۷ مورد دیگر

Dr. Thong Nguyen-Huy is a Senior Research Fellow at the University of Southern Queensland's Centre for Applied Climate Sciences, specializing in agricultural climate risk management. He holds a PhD from USQ and has held roles including Postdoctoral Research Fellow (Future Drought Fund Hub, 2021–2022), Lecturer (School of Business, 2023), and Research Fellow (2023–2024). Education: BEng, Vietnam National University-HCMC (2009) MSpatSciTech, University of Southern Queensland (2013) PhD, University of Southern Queensland (2019) Research Interests: Dr. Nguyen-Huy focuses on agricultural climate risk modeling, environmental finance, geospatial intelligence, and disaster risk management. He develops statistical algorithms, copula-based models, and GIS technologies to support decision-making. Key areas include renewable energy forecasting, decarbonization, and precision agriculture. Articles & Trends: His recent work emphasizes data-driven approaches for flood prediction, crop yield forecasting, and climate adaptation strategies. Publications highlight applications in Australia, Vietnam, and India, addressing challenges like index insurance, soil moisture modeling, and flood risk analysis. Awards & Grants: 2021 Allianz Climate Risk Research Award (Top 10 Globally) 2025 InsuResilience Solutions Fund project (Coffee Climate Insurance) 2024 Aus4Innovation grant (Crop Monitoring in Vietnam) Supervision & Grants: He supervises PhD/Master’s research on topics like GIS-based pavement management and soil moisture prediction. Current grants focus on climate resilience, satellite data applications, and flood risk reduction. Labs & Teams: He collaborates with the Centre for Applied Climate Sciences, APN Collaborative Research Programme, and industry partners to advance climate risk solutions.

Sreeni Chadalavadaمشاهده پروفایل

مدرس ارشد

• Water Resources Engineering
• Environmental Engineering
• Hydrology
• +۳ مورد دیگر

Sreeni Chadalavada is a Senior Lecturer in Water Engineering at the University of Southern Queensland, where he focuses on teaching and research in hydrology, water resources, and environmental engineering. Previously, he served as Principal Hydrogeologist and Research Manager at CRC CARE (University of Newcastle) and Senior Scientist at the University of South Australia. His expertise spans hydrology, environmental risk assessment, contaminated land management, and optimization techniques. Education: BTech (Pondicherry University, 2003), MTech (Indian Institute of Technology, 2005), PhD (University of South Australia, 2009). Research interests include water resources engineering, waste management, environmental monitoring, and the application of AI in environmental systems. He has supervised numerous doctoral and master’s students on topics like groundwater remediation, climate change impacts on hydrology, and machine learning in water quality management. Key affiliations include the Centre for Applied Climate Sciences and the Institute for Life Sciences and the Environment. His recent work emphasizes AI-driven solutions for air and water quality, climate change adaptation, and sustainable remediation strategies.

• FinTech
• Cyber Security
• Data Science
• +۴ مورد دیگر

Dr. KC Chan is a Senior Lecturer at the University of Southern Queensland (USQ) in the School of Business, specializing in Information Systems. He holds academic affiliations as an Honorary Senior Research Fellow at La Trobe University and a Visiting Fellow at the University of New South Wales (UNSW). With over 30 years of professional experience, his career spans academia, industry, and research. He has published over 100 refereed papers focusing on FinTech, Cyber Security, AI/ML applications, and data science. Dr. Chan's educational background includes a BASc and MASc from the University of Toronto and a PhD in Manufacturing Engineering from UNSW. His research interests emphasize the intersection of technology and business, particularly in financial systems security, blockchain applications, and data-driven decision-making. He has supervised numerous doctoral and master's students, including projects on quantum computing risk management, intrusion detection in web systems, and cognitive approaches to cryptocurrency frameworks. Dr. Chan's work bridges academia and industry, with notable contributions to smart building AI integration, manufacturing big data ecosystems, and healthcare informatics. His recent publications (2023-2025) address cryptocurrency trading analysis, mental health monitoring systems, and sustainable corporate strategies. He actively contributes to teaching advanced cybersecurity topics like CIS8500 and CIS8711.

• Hydrogeology
• Groundwater Hydrology
• Environmental Engineering
• +۳ مورد دیگر

Dr. Gabriel Rau is a Senior Lecturer at the University of Newcastle's School of Environmental and Life Sciences. He holds a PhD from the University of New South Wales and a Master's in Environmental Engineering from Universitat Stuttgart. His expertise spans geo-environmental science, hydrogeology, and advanced data analysis using Python. Rau's research focuses on subsurface processes, groundwater flow dynamics, and sustainable resource management. Education: Doctor of Philosophy (PhD), University of New South Wales Master of Environmental Engineering, Universitat Stuttgart Research Interests: Quantification of subsurface processes in coastal and arid environments Heat and solute transport in porous media Impact of climate change on groundwater systems Application of geophysical and numerical methods for hydrogeological analysis Collaborations and Grants: International projects with institutions like Karlsruhe Institute of Technology (KIT) and the University of New South Wales Focus on interdisciplinary approaches to hydrogeological challenges Development of novel analytical techniques for tidal and thermal groundwater responses Labs/Teams: Active in the University of Newcastle's hydrogeology research group, leading experimental and field-based studies.

Saiful Islamمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Big Data
• Data Analytics
• +۵ مورد دیگر

Dr. Saiful Islam is a Senior Lecturer in the School of Information and Physical Sciences at the University of Newcastle, Australia. His expertise spans Artificial Intelligence, Big Data, Predictive Analytics, and Medical Informatics. He has held academic roles at Griffith University (2017–2022) and postdoctoral positions at Swinburne University of Technology and La Trobe University. With an H-index of 22 and over 1,800 citations, his research focuses on solving real-world challenges in healthcare, cybersecurity, and environmental sustainability through data-driven methodologies. Notable contributions include AI solutions for defect detection in sports cards, predictive analytics for osteoarthritis therapy, and ethical AI frameworks. Education: PhD in Computer Science (Swinburne University), Master of Science and Bachelor of Science with Honors (University of Dhaka). Research Interests: Leveraging AI and big data for healthcare informatics, causal discovery from text, and secure data-sharing frameworks. His recent work includes developing algorithms for breast cancer biomarker analysis and ethical AI in health insurance risk assessment. Grants & Awards: Secured $615,951 in grants, including projects on AI tutoring systems and resilient transport logistics. Recognitions include IEEE Senior Membership (2021) and Fellow of the Higher Education Academy (2020). Advisory & Partnerships: Collaborates with industry partners like Honeysuckle Health and Media8, focusing on AI-driven solutions for compliance, traceability, and risk assessment. Supervises 9 current PhD/Master’s students exploring topics like uncertainty calibration in AI and federated learning for robotics. Labs/Teams: Leads research in AI ethics, health informatics, and graph-based data engineering within the University of Newcastle’s Data Science and Statistics team.

Simon McMullanمشاهده پروفایل

دانشیار

• Autonomic Nervous System
• Neuroscience
• Cardiovascular Physiology
• +۳ مورد دیگر

Simon McMullan is an Associate Professor in the Faculty of Medicine & Health Sciences at Macquarie University, Sydney. He holds a PhD in Physiology (2002, University of Bristol) and a BSc (Hons) in Physiology (1998, University of Manchester). His research focuses on autonomic nervous system circuits regulating blood pressure and respiration, with implications for conditions like sleep apnea, hypertension, and affective disorders. He leads projects on neural control of airway protection, optogenetic therapies for sleep disorders, and cardiovascular connectivity. Education: PhD (Physiology), University of Bristol, UK (2002) BSc (Hons) Physiology, University of Manchester, UK (1998) His research integrates viral tracing, optogenetics, and electrophysiology to study brain circuits. He has supervised 1 Honours, 9 MRes, and 8 PhD students, many of whom received awards. Notable achievements include the 2018 Australian Neuroscience Society Paxinos-Watson Prize. Labs/Teams: Leader of the Neurobiology of Vital Systems research node at Macquarie Medical School Data Horizons Research Centre, collaborating with global teams on projects like DeepSlice and neural circuit mapping.

Houying Zhuمشاهده پروفایل

مدرس

• High-dimensional learning
• Statistical computing
• Modelling and visualisation
• +۴ مورد دیگر

Dr. Houying Zhu is a Lecturer in Statistics at Macquarie University's School of Mathematical and Physical Sciences. Her research focuses on high-dimensional learning, statistical computing, and modelling/visualization, with an emphasis on developing efficient methodologies for modern data analysis. She holds a PhD in Applied Mathematics from the University of New South Wales and has held research roles at City University of Hong Kong and the University of Melbourne as a Maurice Belz Research Fellow in Statistics. Dr. Zhu is Co-Director of the Statistical Modelling Research Group, providing mentorship to early-career researchers and HDR students through regular supervision and collaborative projects. She actively engages in academic leadership, serving on the Board of Directors for the IASC-ARS (2023-2027) and the SSA NSW branch council (2021-2023). Her teaching spans undergraduate and postgraduate units, including Bayesian Data Analysis, Generalized Linear Models, and Statistical Graphics. Research Highlights: Innovations in quasi-Monte Carlo methods, feature selection algorithms, and medical imaging applications. Awards: Includes the President’s Award for Leadership in Statistics (2022) and multiple funding grants (MATRIX Family Funding, SSA Fellowship). Community Engagement: Organized the MATRIX Computational Mathematics for High-Dimensional Data program (Feb 2023) and contributes to statistical education initiatives. Her interdisciplinary work bridges computational statistics and real-world applications, with recent projects addressing wildfire risk modelling, protein engineering, and 6G communication systems.

• Data Privacy
• Evolutionary Computing
• Recommendation Systems
• +۵ مورد دیگر

Dr. Jinli Cao is a full-time Associate Professor in the Department of Computer Science and Information Technology at La Trobe University. She holds a BSc from Hebei University, China, and a PhD from the University of Southern Queensland, Australia (1997). Her research focuses on evolutionary computing, data privacy, deep learning for vulnerability assessment, and decision support systems. She has published over 150 papers in top venues such as VLDB and IEEE Transactions series. Dr. Cao leads an ARC-funded project on software vulnerability risk discovery and has secured three ARC grants. She has supervised 11 PhD, 2 Master’s, and 57 Honours students, many of whom work in academia and industries like Oracle and Commonwealth Bank. Teaching contributions include developing courses in databases, data warehouses, and artificial intelligence. Research Interests: Privacy-preserving data publishing and optimization Evolutionary algorithms for dynamic data partitioning Deep learning applications in cybersecurity and healthcare Graph-based machine learning for access control and anomaly detection Decision support systems and top-k query processing Her recent articles explore cutting-edge topics like privacy-preserving spatial crowdsourcing tasks, graph neural networks for traffic prediction, and cybersecurity frameworks for vulnerability prioritization. Awards include competitive ARC grants totaling $450,000 (2023-2025). She actively serves as an Associate Editor for Health Information Science and Systems and has examined over 100 PhD theses across Australian universities. Teaching highlights: Developed 20+ courses including Database Management Systems, Data Warehousing, and Artificial Intelligence. Coordinates units like Decision Support Systems and Intermediate Programming in Java.

• Data Engineering
• Big Data Analytics
• Cybersecurity
• +۷ مورد دیگر

Prof. Wenny Rahayu is the current Dean of the School of Computing, Engineering & Mathematical Sciences (SCEMS) at La Trobe University, Australia. Previously, she held leadership roles including Head of the Department of Computer Science and Information Technology (2012–2014) and Head of School for Engineering and Mathematical Sciences (2015–2021). Her research focuses on data engineering, cybersecurity, IoT systems, and predictive analytics, with over 300 publications and 7,500+ citations. She has led major grants from the Australian Research Council (ARC), industry partners like Airservices Australia, and international collaborations. Prof. Rahayu has supervised 30 PhD students, now working globally in academia and industry. Her work spans IoT security frameworks, privacy preservation, and smart manufacturing solutions. Research Highlights: Data Integration & Optimization Cybersecurity for IoT and Cloud Environments Predictive Maintenance in Industry 4.0 Privacy-Preserving Technologies Adaptive Learning Systems Grants & Collaborations: ARC Industry Linkages and International Grants (Open Geospatial Consortium, Japan JSPS) Industry Partners: IPL, CSIRO, Army Research Victorian Government Technology Innovation Programs Awards & Roles: Appointed as Lead Assessor for New Zealand MBIE Endeavour Fund (2019–present). Recognized for contributions to data science and interdisciplinary research. Labs & Teams: Leads cross-disciplinary teams in SCEMS focusing on IoT, cybersecurity, and smart systems. Collaborates with global partners on industrial and health-related projects.