جست‌وجوی استاد و پژوهشگر

• Digital Transformation
• Cybersecurity Management
• Business Analytics
• +۵ مورد دیگر

Dr Michael Lane is a Senior Lecturer in Information Systems at the University of Southern Queensland (USQ), School of Business. He serves as Vice-Chair of the ACS Downs and South West Chapter and Chair of the USQ ICT Programs Leadership and Governance Committee. With over 20 years of experience in teaching, research, and service, his expertise spans Digital Transformation, Business Analytics/AI, and Cybersecurity at organizational and societal levels. He supervises multiple PhD/DBAR students and has published extensively in high-impact journals and conferences. Educations: ADipMC (University of Southern Queensland) BIT(Hons) (University of Southern Queensland) PhD (University of Southern Queensland) Research Interests: Digital Transformation of Organizations Cybersecurity Management (Risk, Governance, Compliance) Business Analytics and Artificial Intelligence His research bridges theory and practice, addressing real-world challenges through rigorous methodologies. Articles Trends: Recent works focus on AI-driven educational design, healthcare supply chain safety, and digital transformation maturity models. Notable contributions include frameworks for ERP system effectiveness and cross-cultural innovation analysis. Awards: Best Conference Paper Award (2021) ACPHIS Kit Dampney Best Paper Award (2013) Advising & Grants: Supervises over a dozen PhD/DBAR students, including projects on healthcare app development and ICT strategic investment. Active in grants like the USQ CRN Project on broadband ecosystems. Labs & Affiliations: Affiliated with the Institute for Resilient Regions (IRR), Rural Economies Centre of Excellence (RECE), and Centre for Health Research (CHR). Active in collaborative research on rural ICT impacts and health informatics.

• Climate Finance
• Sustainable Finance
• ESG Investing
• +۳ مورد دیگر

Jenny Wang is Senior Lecturer in Finance at the University of Southern Queensland's School of Business, with multidisciplinary expertise in engineering, accounting, and finance. She holds a Ph.D. from the National University of Singapore and Queensland University, complemented by industry experience in banking and real estate. Research focuses on climate/sustainable finance, ESG integration, and innovative risk-transfer mechanisms like weather index insurance. Current projects examine sustainable finance taxonomies and climate disclosure frameworks. She secured the ARC Early Career Industry Fellowship ($431,000) in 2023 and contributed to Australia's sustainable finance taxonomy development as Technical Advisory Group member at the Australian Sustainable Finance Institute. Industry collaborations include work with Rio Tinto, SunWater, and government agencies. She holds the CFA Institute's Certificate in ESG Investing and memberships in CPA Australia and AFAANZ.

• Soil Science
• Environmental Engineering
• Sensor Development
• +۵ مورد دیگر

Waqas Afridi is a part-time academic at the School of Engineering , Macquarie University , specializing in sensor systems for environmental monitoring. His work integrates IoT , machine learning , and electromagnetic sensor design to address challenges in soil science and water resource management . University: Macquarie University School: School of Engineering Rank: PartTime Lecturer His research focuses on smart sensor nodes for soil quality assessment , organic carbon measurement , and evapotranspiration prediction , with applications in sustainable agriculture and water treatment systems . Recent publications highlight the use of Support Vector Machines and electromagnetic sensing in environmental data analysis. Email: waqas.afridi@mq.edu.au | waqas.afridi@hdr.mq.edu.au

Nazanin Ghahreman-Falconerمشاهده پروفایل

مدرس ارشد

• Risk prediction modelling
• Medication safety
• Clinical informatics
• +۵ مورد دیگر

Dr Nazanin Ghahreman-Falconer serves as a Senior Lecturer at The University of Queensland's School of Pharmacy and Pharmaceutical Sciences, while maintaining a clinical research role at Princess Alexandra Hospital. She chairs the Pharmacy Research in Metro South (PRIMS) committee and holds affiliate status with the Centre for Health Service Research UQ, actively contributing to the Society of Hospital Pharmacists of Australia's Research Leadership Committee. Her educational foundation includes a PhD from The University of Queensland (2020) titled Prioritising patients at high-risk of medication harm: development and validation of risk prediction models , building upon 20 years of clinical pharmacy experience across community and hospital settings. Dr Ghahreman-Falconer's research centers on medication safety innovation through risk prediction modeling, clinical informatics, and machine learning applications. She investigates extended scope pharmacy services in acute care while developing tools like the AIME-Frail model to identify patients vulnerable to medication harm. Her work bridges clinical practice and data science to optimize patient care pathways and prevent adverse drug events. Analysis of her 43 journal publications reveals strong thematic focus on predictive analytics for medication safety, antimicrobial stewardship in aged care, and digital health integration. Recent work demonstrates increasing application of machine learning to clinical pharmacy problems, particularly in geriatric and cardiovascular populations, with significant contributions to risk modeling and transition-of-care services. She actively supervises Higher Degree Research students on machine learning applications in clinical practice and provides academic oversight for the RECARD Study (Medical Research Futures Fund: MRFMMIP000044), targeting preventable medication-related hospitalizations in high-risk cardiovascular patients. This $1.2 million MRFF-funded project exemplifies her commitment to translating research into practice. Through the PRIMS committee, she cultivates research capacity across Metro South Health by mentoring hospital pharmacists and facilitating collaborative projects. Her leadership connects academic research with frontline clinical needs, ensuring relevance to evolving healthcare challenges including digital hospital transformations and complex patient care requirements.

Zubair Abdullah-Vetterمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Renewable Energy Engineering
• Solar Cell Technology
• +۳ مورد دیگر

Dr. Zubair Abdullah-Vetter is a Research Fellow at the University of New South Wales (UNSW) , affiliated with the College of Engineering and the Photovoltaic and Renewable Energy Engineering department. His work focuses on integrating advanced machine learning techniques with photovoltaic device analysis to enhance solar energy system quality and reliability. PhD in Photovoltaic Engineering Specializes in AI-driven solar cell diagnostics Active in both journal publications and conference presentations Research interests center on machine learning for renewable energy systems , particularly: Deep learning for defect analysis in solar cells Predictive modeling of photovoltaic degradation Accelerated testing protocols using AI Quantum efficiency measurement automation Luminescence image interpretation Time-series analysis of PV performance Recent publications demonstrate expertise in applying neural networks and regression techniques to photovoltaic diagnostics. The work has significant implications for climate change mitigation through improved solar technology efficiency. Scientific recognition includes: BT Imaging Photovoltaic Thesis Prize (2020) Best Poster Award at IEEE PVSC (2022) ACAP Best Student Paper Award (2024) Collaborates with leading researchers in photovoltaic materials and device reliability while contributing to practical applications in Australian solar infrastructure projects.

Arash Shaghaghiمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Internet of Things (IoT) Security
• Zero Trust Architecture
• +۴ مورد دیگر

Arash Shaghaghi is a Senior Lecturer in Cyber Security and Acting Director of Online Education at the School of Computer Science and Engineering (CSE) at UNSW Sydney. Previously affiliated with RMIT University, Deakin University, Data61 CSIRO, The University of Melbourne, and The University of Texas at Dallas, he holds a PhD in Computer Science and Engineering from UNSW Sydney, an MSc in Information Security from University College London, and a BSc with Distinction from Heriot-Watt University. His research spans cybersecurity with emphasis on IoT security, zero trust architecture, blockchain applications, and posthumous data management. With over 1.7 million AUD in research funding as Lead CI/CI, his work addresses critical challenges in intelligent transport systems, quantum-safe security, and digital legacy solutions. He serves as Associate Editor for the Journal of Ad Hoc Networks and reviews for top conferences including NDSS and IEEE S&P. His 15 most recent publications demonstrate expertise in IoT security frameworks, digital will solutions, encrypted traffic analysis, and vulnerability prediction models. These works appear in premier venues like IEEE TDSC, IEEE S&P, and ACM WWW, reflecting his leadership in solving practical security challenges for emerging technologies. Early Career Academic Excellence Award (Research), UNSW Engineering, 2024 Educational Excellence & Innovation Award, UNSW Engineering, 2023 Heidelberg Laureate Forum Selection (Top 200 young scientists), 2023 Best Demo Award, IEEE LCN Conference, 2020 As an award-winning educator, Shaghaghi leads UNSW's Master of Cyber Security online programs and previously directed Deakin University's Graduate Certificate in Information Technology. His research team includes postdocs, software developers, and 3 current PhD students. He actively engages with media outlets including ABC and The Guardian on cybersecurity topics, particularly digital legacy management and IoT security.

Richard Thomasمشاهده پروفایل

مدرس ارشد

• Software Engineering
• Cyber Security
• Curriculum and Pedagogy
• +۴ مورد دیگر

Richard Thomas is a Senior Lecturer and Director of International at the School of Electrical Engineering and Computer Science, part of the Faculty of Engineering, Architecture and Information Technology at The University of Queensland. His academic career spans over three decades, focusing on software engineering education and innovative teaching methodologies. He has held roles including Director of International and has contributed to curriculum design, assessment frameworks, and interdisciplinary collaboration in computing education. His research interests bridge software engineering and pedagogy, emphasizing practical industry integration, student engagement, and global education models. Notable contributions include frameworks for software development education, fault prediction systems, and the use of agile methodologies in teaching. He has published extensively in journals like IEEE Transactions and conferences such as ACM Transactions on Computing Education. Thomas has authored textbooks on software architecture, with editions published in 2022 and 2023, reflecting his commitment to modernizing educational resources. His work on 'Haery' (a Hadoop-based big data system) and energy efficiency optimization highlights his technical contributions to software systems research. He has presented globally, including a 2024 talk on AI-driven entrepreneurship education for sustainability. His research consistently integrates technology advancements with educational innovation, aiming to enhance both student outcomes and industry relevance.

Marcus Gallagherمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Optimization
• +۶ مورد دیگر

Associate Professor Marcus Gallagher is part of the School of Electrical Engineering and Computer Science at The University of Queensland. His research focuses on artificial intelligence, optimization, and machine learning, with an emphasis on algorithm performance benchmarking and cross-disciplinary applications such as healthcare and cybersecurity. He holds a PhD from The University of Queensland (2000) and degrees from the University of New England (BCompSc, 1994; GradDipSc, 1995), as well as a GradCert in Higher Education (2010). His work involves collaborations across domains like network intrusion detection, opioid prescribing analysis, and evolutionary algorithms for game AI. He has published extensively in journals and conferences, including IEEE Transactions on Games, Information Security and Applications, and Evolutionary Computation. His research explores topics such as clustering optimization, data-driven problem benchmarking, and interpretable machine learning policies. Recent studies include analyzing synthetic vs real-world network intrusion datasets and developing graph neural networks for Android malware classification. He also leads initiatives like the IJCNN 2023 Competition on Reproducibility and Loss Landscape Mapping in Neural Networks. His contributions span theoretical advancements and practical applications in AI-driven problem-solving.

Hui Maمشاهده پروفایل

مدرس ارشد

• Electrical Asset Management
• Power Systems
• High Voltage Engineering
• +۵ مورد دیگر

Dr. Hui Ma is a Senior Lecturer in Power & Energy Systems at the University of Queensland, affiliated with the School of Electrical Engineering and Computer Science. His expertise spans Electrical Asset Management, Power Systems, and High Voltage Engineering. He holds a PhD from the University of Adelaide and has been at UQ since 2008. Education: B.Eng and M.Eng from Xi'an Jiaotong University; M.Eng (Research) from Nanyang Technological University; PhD from the University of Adelaide. Research focuses on improving electricity network visibility through modeling, sensing, and signal processing, alongside data mining for renewable-integrated grids. Key areas include transformer condition monitoring, insulation diagnostics, and smart grid technologies. He edits IEEE Transactions on Power Delivery and participates in IEEE Smart Grid initiatives. Recent work addresses PV forecasting, low-frequency grid instability, and transformer aging analysis. His publications emphasize machine learning applications in energy systems and fault diagnosis. Collaborations involve Australian utilities and industry partners.

• Predictive Analytics
• Recommendation Systems
• Graph Learning
• +۴ مورد دیگر

Professor Hongzhi Yin is a leading academic at The University of Queensland, Australia, serving as a Professor and director of the Responsible Big Data Intelligence Lab (RBDI). His research focuses on predictive analytics, recommendation systems, graph learning, and decentralized intelligence. He holds an ARC Future Fellowship and has received numerous awards, including the 2023 Young Tall Poppy Science Award and multiple best paper awards. His work spans machine learning, data mining, and social media analysis, with over 350 publications and an H-index of 83. He advises PhD students and leads collaborative projects in trustworthy AI, federated learning, and privacy-preserving systems. Education: Completed his PhD at Peking University, receiving recognition for his thesis. Research contributions include foundational work on graph condensation, federated recommendation systems, and generative AI trustworthiness. He serves as an editor for top journals like IEEE Transactions on Knowledge and Data Engineering and ACM Transactions on Information Systems . Awards and Honors: ARC Future Fellowship, Young Tall Poppy Science Award (2023), AI 2000 Most Influential Scholar Honorable Mention (2022-2024), and eight international best paper awards. He is also a recognized leader in data mining and computer science, ranked #52 in Australia's Best Scientists 2025. Research Interests: Trustworthy recommendation systems, graph neural networks, federated learning, and privacy-preserving AI. His lab develops methods for robust graph condensation, secure decentralized systems, and ethical AI applications. Recent work includes surveys on point-of-interest recommendation and graph condensation techniques. Labs/Teams: Leads the Responsible Big Data Intelligence Lab (RBDI), fostering innovation in data science and AI ethics. Collaborates globally with institutions like MIT, Stanford, and Carnegie Mellon on foundational AI research.

• Medical Devices and Sensors
• Medical Imaging
• Medical Signal Processing
• +۳ مورد دیگر

Professor Juha Toyras is a Professorial Research Fellow in the School of Electrical Engineering and Computer Science at The University of Queensland, Australia. He also serves as the Head of Research and Innovation at Kuopio University Hospital and Wellbeing Services County of North Savo, and as Professor of Medical Physics and Engineering at the University of Eastern Finland. His research spans biomedical engineering with a focus on medical devices, sensors, imaging, signal processing, and connective tissue biomechanics. He is particularly known for his work in sleep technology and analytics, as well as cartilage biomechanics and medical diagnostics. Since 2004, he has been Vice/Co-Head of the Biophysics of Bone and Cartilage research group and Co-Head of the Sleep Technology and Analytics group at the University of Eastern Finland, leading substantial research teams comprising three professors, approximately 20 research fellows and postdocs, and over 50 PhD students. Professor Toyras has published over 320 peer-reviewed scientific papers with more than 14,000 citations and an H-index of 63. His recent research demonstrates a strong interdisciplinary approach combining biomedical engineering, sleep medicine, and orthopedics, with particular emphasis on developing novel diagnostic tools using advanced imaging techniques, signal processing, and machine learning algorithms for clinical applications. He has successfully supervised 52 PhD students and currently oversees approximately 20 PhD students across institutions. His research has been supported by various European and Australian funding sources. Notably, his work has led to practical medical innovations including the patented Bittium BrainStatus EEG-electrode set for emergency medicine, which is CE-approved and currently in global use.

• Soil Science
• Environmental Engineering
• Data Analytics
• +۳ مورد دیگر

Wartini Ng is a Research Fellow at the School of Life and Environmental Sciences, University of Sydney. Her expertise lies in soil sensing, data analytics, and machine learning applications in environmental science. She holds a BS (cum laude) in Environmental Engineering from the University of California, Riverside, and a PhD in Soil Science from the University of Sydney. Her doctoral research focused on integrating novel data analytics and proximal sensing to analyze soil conditions, particularly using machine learning techniques like deep learning to enhance soil property predictions. Her research interests include soil security, spectral transfer functions for global soil property prediction, and the development of frameworks for soil policy and carbon sequestration. She is a member of the Sydney Institute of Agriculture and contributes to interdisciplinary projects such as spatial evaluation of soil carbon storage potential across Australia and optimizing fertiliser recommendations using mid-infrared spectroscopy. Ng has secured grants including the 2024 'An integrated schema for soil carbon stock estimation and crediting' funded by the National Soil Carbon Innovation Challenge. Her work emphasizes bridging technological advancements (e.g., spectroscopy) with environmental policy to address soil degradation and resource management challenges. She collaborates extensively with international teams, leveraging global datasets to improve soil assessment methodologies. Her lab and fieldwork focus on innovative solutions for soil monitoring, including the redesign of the Tea Bag Index methodology for citizen science in Australia and developing numerical soil classification systems. These efforts aim to democratize soil science while advancing sustainable land management practices.

• Hydrology
• Catchment Management
• Sustainable Water Management
• +۴ مورد دیگر

Willem Vervoort is a Professor in Hydrology and Catchment Management and Director of the ARC Training Centre in Data Analytics for Resources and Environments (DARE) at the University of Sydney. He holds academic affiliations with the School of Life and Environmental Sciences and is a member of the Sydney Environment Institute, Sydney Institute of Agriculture, Sydney Southeast Asia Centre, and The Net Zero Institute. His expertise lies in quantitative hydrology, sustainable water management, and climate change impacts. Vervoort earned a PhD in field hydrology from the University of Georgia and an Agricultural Engineering degree from Wageningen University in Soil Conservation. His research focuses on developing sustainable water management strategies, particularly in agricultural contexts, leveraging interdisciplinary approaches. Key areas include groundwater dynamics, catchment functionality, and the integration of remote sensing and machine learning for hydrological modeling. Recent work emphasizes climate adaptation, afforestation impacts, and water market functionality in Australia and globally. Grants : Includes leadership in Horizon 2020-funded projects on remote sensing for agricultural water management and GRDC-funded initiatives on frost and heat management analytics. Labs/Teams : Directs the DARE Centre and collaborates with international teams in Uruguay, Fiji, and Italy, advancing SWAT model applications and hydrological forecasting. Publications span hydrological processes, climate extremes, and eco-hydrological interactions, with a focus on scaling models for policy and decision-making. His work bridges academic research with practical solutions for environmental sustainability and resource management.

Melinda Hodkiewiczمشاهده پروفایل

استاد

• Maintenance Engineering
• Asset Management
• Data Science
• +۶ مورد دیگر

Professor Melinda Hodkiewicz is a leading academic at the University of Western Australia (UWA), affiliated with the School of Engineering's Mechanical Engineering department. Her work focuses on advancing maintenance, asset management, and safety practices through data-driven approaches, particularly in Technical Language Processing (TLP) and industrial ontologies. She has held significant roles such as the BHP Fellow for Engineering for Remote Operations (2015–2022) and leadership in the $8.8M Australian Government-funded Training Centre for Transforming Maintenance through Data Science. Research interests include applying TLP to maintenance and safety texts, ontology development for industrial interoperability, and advancing standards like ISO 23726. Awards include the MESA Medal (Lifetime Achievement in Asset Management) and Fellow of the Australian Academy of Technology and Engineering (ATSE). She has contributed to international standards (ISO 55000 series) and served on boards of organizations like NOPSEMA and MRIWA. Her work aligns with UN SDG 4 (Quality Education) and SDG 9 (Industry, Innovation & Infrastructure). Key contributions include developing the Industrial Ontology Foundry's Maintenance Working Group, creating open-source tools like OpenBoltRF for wind turbine analysis, and advancing semantic quality assurance frameworks for maintenance procedures. Her research bridges technical language processing with industrial applications, enhancing safety and operational efficiency in sectors like mining, energy, and offshore engineering. Education: BA(Hons) in Metallurgy (University of Oxford, 1985), PhD in Engineering (UWA, 2014) Grants: ARC Training Centre for Transforming Maintenance (2019–2025), ARC Hub for Offshore Floating Facilities (2014–2021) Advisory Roles: Standards Australia EL-069 (Automation Systems), ISO TC184/SC4 (Industrial Data)

• Computer Vision
• Machine Learning
• Object Detection
• +۷ مورد دیگر

Du Huynh is an Associate Professor at the School of Physics, Mathematics and Computing, Department of Computer Science and Software Engineering, The University of Western Australia (UWA). She holds a 0.8 FTE appointment and has served as Graduate Research Coordinator since 2013. Her research focuses on Computer Vision, Machine Learning, Object Detection, and Video Analytics with applications in mineral processing, intelligent transportation systems, and medical imaging. She has secured over $3M in ARC grants and is a Chief Investigator in the Australian Centre for Quantum Growth ($18M funding). Education: BSc (Hons) and PhD in Computer Science from UWA. Prior to UWA, she lectured at Murdoch University for five years. Research Highlights Developed algorithms for automated mineral ore analysis, pedestrian trajectory prediction, and surgical instrument detection. Received three Best Paper Awards (ICPR2014, Kenneth Clarke Journal 2019, AusDM2022) and multiple award nominations. Editorial roles include PLOS One, Journal on Artificial Intelligence, and guest editorships for special issues in CVIU and Electronics. Grants & Projects Lead investigator in quantum computing algorithms for real-time optimization ($3M ARC funding). Collaborations with industry (e.g., Main Roads WA) on traffic video analytics and drone-based prediction systems. Academic Contributions Developed courses in Computer Vision, Machine Learning, and Java Programming. Supervised numerous HDR students and served on technical committees for WACV, ICCV, and DICTA conferences.