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Alina BialkowskiView profile

Senior Lecturer

• Medical Imaging
• Biomedical Engineering
• Computer Vision
• +6 more

Dr Alina Bialkowski is a Senior Lecturer at the School of Electrical Engineering and Computer Science , part of the Faculty of Engineering, Architecture and Information Technology at The University of Queensland. Her research focuses on interpretable machine learning and computer vision to enhance AI transparency and solve real-world challenges. Prior to joining UQ in late 2017, she held postdoctoral positions at University College London (2015–2017), where she studied human perception in driving, and Disney Research Pittsburgh (2014), analyzing team sports using spatiotemporal data. Dr Bialkowski earned her PhD and Bachelor of Engineering (Electrical Engineering) from Queensland University of Technology, Australia. Her doctoral research centered on group behavior analysis from visual and spatiotemporal data, with applications in sports analytics and intelligent surveillance systems. Her research interests span medical imaging (especially electromagnetic imaging of strokes), human attention modeling in driving, intelligent transport systems , surveillance systems , and sports analytics . She emphasizes explainable AI to bridge the gap between technical systems and human understanding, employing methods like feature visualization and attribution. Her work also explores sensors for non-invasive imaging and machine learning frameworks to ensure ethical AI. Dr Bialkowski has received significant recognition, including the Best Paper Prize at the 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) . Her research has led to 6 international patents with collaborators such as Disney Research, Toyota Motor Europe, and The University of Queensland, focusing on electromagnetic imaging and AI-driven solutions. She actively contributes to interdisciplinary projects like The Lanyard Project (traffic sensor fusion) and co-authored a SmartSat CRC-funded research report on machine learning for satellites. Dr Bialkowski is available for supervision and advocates for AI systems that integrate human-centric principles into their design and evaluation.

Shovanur HaqueView profile

Lecturer

• Bayesian Statistical Modelling
• Spatial Data Analysis
• Machine Learning
• +3 more

Dr. Shovanur Haque is an Associate Lecturer in the School of Mathematical Sciences and a Postdoctoral Research Fellow in the School of Public Health & Social Work at Queensland University of Technology (QUT). She holds a PhD in Statistics (2018) from QUT, focusing on developing the MaCSim method for evaluating record linkage accuracy. Her work spans academia and government, including roles at the Australian Bureau of Statistics and Queensland Department of Environment and Science. Currently, she leads a Centre for Data Science (CDS) project investigating spatial data aggregation effects on medical decision-making. Her research interests include Bayesian modeling, spatial data analysis, machine learning, and record linkage. Key research projects involve assessing Modifiable Areal Unit Problem (MAUP) impacts on epidemiological inference, modeling infectious disease transmission dynamics, and developing climate-driven early warning systems for public health. She contributes to interdisciplinary collaborations, combining statistical methods with health, environmental, and social sciences. Education: PhD in Statistics (QUT, 2018) Research Focus: Spatial epidemiology, Bayesian methods, record linkage, and MAUP analysis Affiliations: Centre for Data Science, Centre for Immunology and Infection Control Her recent publications (2021–2025) emphasize Bayesian structural time series modeling, spatial aggregation effects in health data, and cross-border disease surveillance networks. She actively engages in methodological advancements for public health analytics and data-driven policy decisions.

• Planetary geology
• Structural geology and tectonics
• Geophysics
• +5 more

Claire Orlov is a Lecturer in Earth Science at the University of Wollongong, affiliated with the Faculty of Science, Medicine and Health and the School of Science. She has been in this academic role since 2024, bringing extensive experience from her prior position as a Geoscientist at Geoscience Australia (2014–2024). Research Interests: Her expertise lies in planetary geology, particularly structural geology and tectonics on Mars. She employs remote sensing, photogrammetry, and 3D seismic data analysis to study crustal deformation, faulting, and magmatic processes on planetary surfaces. Her work bridges Earth-based geological methods with extraterrestrial applications. The recent articles highlight a strong focus on Martian tectonics, especially in the Tempe Terra region, analyzing extensional structures, dyke-induced grabens, and magmatic influences using high-resolution data. Her research integrates field-scale geological interpretation with planetary remote sensing, contributing to understanding the tectonic evolution of Mars. Scientific Awards: No awards mentioned. Advising and Grants: There is no mention of student supervision or grant funding in the provided text. Labs, Teams, and Research Output: Claire Orlov contributes to collaborative planetary science research, often working with co-authors from various institutions. Her open-access dataset, the 'Tempe Terra Fault Catalogue,' hosted on Zenodo, supports reproducible science and has been referenced in Mendeley and Wikipedia, indicating impact in both academic and public domains.

Conrad SandersonView profile

Researcher

• Artificial Intelligence
• Machine Learning
• AI Ethics
• +7 more

Dr. Conrad Sanderson is a Researcher and Team Leader at the Data61 division of CSIRO , focusing on artificial intelligence, machine learning, AI ethics, and high-performance numerical computing. He is also an Adjunct Professor at Griffith University . With over 150 publications and 11,000+ citations, he is renowned for developing influential open-source libraries like Armadillo and RcppArmadillo . Research Interests Artificial Intelligence & Deep Learning Responsible AI, Safe AI, and Ethical Trade-offs Numerical Linear Algebra and High-Performance Computing Recent Publications highlight advancements in: Dynamic graph anomaly detection via extreme value theory Fire propagation uncertainty estimation using neural emulators Resolving ethical tensions in AI implementation GPU-accelerated machine learning Scientific Awards Most cited paper award for thesis-based article Armadillo framework: 30+ million downloads Collaborations include researchers from Facebook, NASA, Boeing, and institutions like MIT and Stanford. His work bridges academia and industry through open-source contributions and interdisciplinary applications.

Khandakar AhmedView profile

Associate Professor

• Artificial Intelligence
• Cyber Security
• Digital Health
• +8 more

Khandakar Ahmed is an Associate Professor of Information Technology at Victoria University's College of Arts, Business, Law, Education & IT (CoABLEIT) and Discipline Leader for Emerging Trends in Science, IT & Engineering at the Institute for Sustainable Industries and Liveable Cities (ISILC). His career spans roles at Victoria University (2017–present), RMIT University (2015–2017), and Shahjalal University of Science and Technology (2007–2015). Education: PhD in Electrical and Computer Engineering (RMIT University, 2014), MSc in Networking and e-Business Centered Computing (University of Reading, 2009), BSc in Computer Science and Engineering (Shahjalal University of Science and Technology, 2007) His research expertise includes Artificial Intelligence, Cyber Security, Digital Health, Federated Learning, Quantum Computing, and the Internet of Things . He has published over 100 refereed papers with 4,200+ citations (h-index 32) and secured $3.4 million+ in funding since 2018 from partners like Australia's Economic Accelerator and Western Health. His recent work focuses on AI-driven mental health analysis , blockchain security frameworks , and edge computing optimizations . He serves as lead supervisor for 6 PhD and 1 Master of Research student and has mentored over 100 students through industry-linked projects. Dr Ahmed actively contributes to editorial roles for leading journals such as Scientific Reports , IEEE Transactions , and ACM Computing Surveys . His research aligns with UN Sustainable Development Goals 3 (Good Health), 9 (Industry Innovation), and 11 (Sustainable Cities).

Hassan Al RaziView profile

Researcher

• Primate behavioural ecology
• Primate morphology and evolution
• Primates conservation biology and biodiversity
• +5 more

Hassan Al Razi is a Bangladeshi zoologist and biodiversity conservationist currently pursuing his Doctor of Philosophy at the School of Human Sciences, University of Western Australia. His research focuses on primate behavioral ecology, with particular emphasis on endangered species in Bangladesh including Bengal slow lorises, hoolock gibbons, and Phayre's langurs. Affiliated with the university's research programs, he contributes to multiple international conservation initiatives addressing primate conservation challenges. His educational background includes a Master of Science in Wildlife and Biodiversity Conservation (2017) and a Bachelor of Science in Zoology (2016), both from Jagannath University in Bangladesh. His thesis work examined Population Status, Habitat Preference and Threats of Phayre's Leaf Monkey in Satchari National Park. Al Razi's research interests span primate behavioral ecology, primate morphology and evolution, conservation biology, and biodiversity management. His work particularly emphasizes loris and chimpanzee conservation, with field studies conducted in Bangladesh's tropical forests. His fingerprint analysis reveals significant contributions to National Parks management, Lorisidae conservation, Anura studies, New Species discovery, Hylobatidae research, Nycticebus conservation, Sciuridae studies, and Tropical Forest ecology. Analysis of his 15 most recent publications (2021-2025) reveals a strong focus on primate conservation challenges in Bangladesh, with particular attention to road infrastructure impacts, wildlife trafficking, habitat fragmentation, and community-based conservation strategies. His work spans multiple primate species including hoolock gibbons, slow lorises, and langurs, with increasing emphasis on digital monitoring of wildlife trade and climate change adaptation strategies. His scientific recognition includes the award for Population Status, Threats, and Conservation of Bengal Slow Loris (Nycticebus bengalensis) in Northeast Bangladesh (2017), which received significant media attention with coverage from 9 news outlets, mentions by 3 X users, and 5 readers on Mendeley. Al Razi actively collaborates with international researchers across multiple countries, contributing to global conservation initiatives including the Global Primate Roadkill Database. His work aligns with UN Sustainable Development Goals related to biodiversity conservation and environmental protection. While specific lab affiliations aren't detailed in the provided text, his research involves extensive fieldwork in Bangladesh's forest ecosystems and collaboration with international conservation networks.

Todd RobinsonView profile

Associate Professor

• Remote Sensing
• Geospatial Data Analytics
• Species Distribution Modelling
• +5 more

Associate Professor Todd Robinson is affiliated with Curtin University's School of Earth and Planetary Sciences (EPS), part of the Faculty of Science and Engineering. His roles include lecturing on Geospatial Analysis, Spatial Modelling, Spatial Databases, and Algorithms, while serving in the Office of the Provost. His research focuses on remote sensing of vegetation, geospatial data analytics, and applications of airborne lidar, with emphasis on ecological hypothesis testing. Key areas include species distribution modeling (especially rare/invasive species), rangeland condition monitoring, geostatistics, and conservation strategies in biodiverse regions like south-western Australia. Recent work explores groundwater-dependent vegetation dynamics and mineral potential modeling via floristic surveys. Research interests span conservation biology, landscape genetics, and arid land ecology. Over 30 peer-reviewed articles since 2003 demonstrate his impact in remote sensing applications, spatial data analysis, and ecological restoration. His methodologies integrate UAV imagery, GIS tools, and genetic sequencing to address pressing environmental challenges such as invasive species control and climate adaptation. Publications highlight interdisciplinary approaches, combining field data with computational models to advance practical solutions in biodiversity conservation and sustainable land management. His work bridges ecological theory and applied conservation practices, particularly in vulnerable ecosystems like Mediterranean jarrah forests and Banded Iron Formation ranges.

• Forensic Science
• Drug Intelligence
• Organized Crime Analysis
• +6 more

Dr. Marie Morelato is a Senior Lecturer at the University of Technology Sydney (UTS), affiliated with the School of Mathematical and Physical Sciences and the Centre for Forensic Science. She holds a PhD in drug intelligence from UTS (2015) and a prestigious Chancellor’s Postdoctoral Research Fellowship (2015–2019). Her research focuses on forensic intelligence, illicit drug data analysis, and organized crime systems, emphasizing data triangulation from sources like cryptomarkets, seizures, and wastewater. She teaches courses such as Forensic Intelligence and serves as Course Director for the Bachelor of Forensic Science program. Marie has received awards including the UTS Teaching and Learning Award (2022) and recognition for contributions to student learning (2024). She leads grants on drug surveillance, including the Residue and Post Overdose Substance Testing (RePOST) project and studies on opioid-related harms. Her editorial roles include Associate Editor for Forensic Science International and contributions to the International Association of Forensic Sciences. Her work bridges forensic science with intelligence-led policing, advancing methodologies like machine learning for crime scene analysis and portable NIR drug detection. She collaborates with agencies like the Australian Federal Police and emphasizes interdisciplinary approaches to tackle complex criminal systems.

• Spectroscopy
• Atmospheric Chemistry
• Analytical Chemistry
• +3 more

Chris Medcraft is a Postdoctoral Researcher at the Faculty of Science and Engineering, Southern Cross University. He holds a PhD from Monash University. His research focuses on spectroscopic techniques (e.g., microwave, infrared, and rotational spectroscopy) applied to molecular systems, atmospheric chemistry, and astrochemical studies. Key interests include molecular interactions, aerosol dynamics, and chiral analysis. Medcraft collaborates with advanced facilities such as the Environmental Analysis Laboratory and utilizes cutting-edge methods like drone-based measurements for marine aerosol studies. His work spans diverse areas, including the decomposition of fluorinated compounds, hydrogen bonding in complex systems, and structural analysis of organic/inorganic complexes. Notable contributions include studies on the Great Barrier Reef’s atmospheric aerosols and the rotational spectroscopy of astrochemical candidates like vinyloxirane. Medcraft’s research integrates experimental and computational approaches to understand molecular behavior in environmental, atmospheric, and astrochemical contexts. He has contributed to interdisciplinary projects leveraging advanced analytical tools such as broadband rotational spectroscopy and synchrotron-based Fourier transform spectrometry.

• Building Information Modelling (BIM)
• Information & Communication Technologies in Built Environment
• Project Risk and Cost Modelling
• +4 more

Dr. Madhav Nepal is a Senior Lecturer at the School of Architecture & Built Environment, Faculty of Engineering at Queensland University of Technology (QUT). He holds a Ph.D. in Civil Engineering from the University of British Columbia and has extensive academic qualifications in construction engineering and project management. His research focuses on Building Information Modelling (BIM), sustainable construction practices, project lifecycle management, and infrastructure asset management. Dr. Nepal has supervised numerous postgraduate research projects, including work on BIM implementation, power plant risk assessment, and e-tendering readiness in construction. Education: Ph.D., Civil Engineering (Project & Construction Management), University of British Columbia (2011) M.Sc., Building (Project Management), National University of Singapore (2004) M.Eng., Civil Engineering (Construction Engineering & Management), Asian Institute of Technology (2001) His research interests span BIM integration in construction workflows, ICT applications for sustainability, and risk modeling in large infrastructure projects. Recent work emphasizes machine learning applications for urban sustainability and ontology-based risk management in public-private partnerships. Dr. Nepal actively contributes to teaching units like Project Management Principles (BEN610/PMN610) and Managing Project Cost (BEB113). His publications highlight innovations in BIM adoption frameworks, cost overrun risk assessment methodologies, and safety inspection technologies using mobile computing. Supervision highlights include doctoral work on BIM-GIS infrastructure frameworks and cost overrun modeling in power plants. He has collaborated on interdisciplinary projects addressing nonconformity in construction supply chains and smart building technologies for UAE prisons.

Tony BostonView profile

Senior Lecturer

• Geographic information systems
• Remote sensing
• Machine learning applied to environmental information
• +5 more

Tony Boston is an Honorary Senior Lecturer at the Fenner School of Environment & Society at the Australian National University. With extensive expertise in geographic information systems, remote sensing, and machine learning applications for environmental data, he contributes significantly to earth science research and environmental monitoring initiatives across Australia. His educational background includes: PhD from the Australian National University (awarded November 8, 2024) Graduate Diploma in Computing Studies from the University of Canberra (awarded April 22, 1993) Bachelor of Science (Honors) from the Australian National University (awarded May 9, 1984) Tony's research focuses on the application of earth observations, in situ data, and AI foundation models for environmental monitoring and prediction. His work particularly emphasizes water resources management, land cover mapping, and environmental change detection through advanced machine learning techniques. He has developed expertise in integrating diverse data sources to create comprehensive environmental information systems that support evidence-based decision making in natural resource management, with a strong emphasis on developing national and international data standards. His recent publications demonstrate a consistent focus on applying convolutional neural networks and other machine learning approaches to environmental remote sensing data, particularly Landsat imagery. These works show an evolution from basic plant identification experiments to sophisticated land cover and vegetation mapping systems with practical applications for environmental monitoring across Australia. His research bridges the gap between theoretical machine learning advancements and practical environmental management needs, with increasing emphasis on temporal stability and accuracy in land cover classification. Tony has extensive professional experience, having served over 25 years in executive roles within the Australian Public Service, including positions at the Department of the Environment, National Library of Australia, and Bureau of Meteorology. At the Bureau of Meteorology, he was responsible for developing a national database of surface and groundwater information that underpins the Water Information Program established under Part 7 of the Water Act 2007. As co-chair of the WMO/OGC Hydrology Domain Working Group from 2013 to 2024, he made significant contributions to the development of WaterML2 international standards for hydrological data exchange.

Shyh Wei TengView profile

Associate Professor

• Image Processing
• Machine Learning
• Bioinformatics
• +3 more

Assoc Prof Shyh Wei Teng is an Associate Professor and Deputy Dean at Federation University Australia's Institute of Innovation, Science and Sustainability (IISS). He holds a Bachelor of Computing (First-class Honours) and PhD in Information Technology from Monash University (2004), and a Graduate Certificate in Higher Education (2008). His research focuses on image processing, machine learning, bioinformatics, and computer vision, with notable contributions to LiDAR-based building extraction, SIFT algorithm optimization, and multimodal image registration. He has secured significant grants, including an Australian Research Council (ARC) Discovery Project (2013). Prof Teng has supervised numerous PhD and master’s students, contributing to advancements in image retrieval, clustering algorithms, and biomedical applications. His work has been published in top-tier journals like Pattern Recognition and Neurocomputing , and he actively reviews for IEEE conferences. He taught courses in database systems, project management, and systems analysis, receiving teaching and community engagement nominations. Research interests span computational techniques for medical imaging, contour-based corner detection, and machine learning applications in remote sensing. His labs and collaborations include projects on augmented reality for education and ecological data analysis.

• Plant Physiology
• Ecology
• Drought Tolerance
• +7 more

Brendan Choat is a researcher at James Cook University , focusing on plant physiological responses to environmental stressors, particularly drought and hydraulic failure in woody species. His work spans tropical and temperate forests, emphasizing ecosystem vulnerability to climate change . Key Research Areas : Drought tolerance, xylem hydraulics, carbon-water coupling in trees, and global forest resilience. Collaborative Networks : Extensive partnerships across Australia and internationally, including institutions like Western Sydney University and CSIRO. Publications : Major contributions to journals such as New Phytologist , Global Change Biology , and Nature , addressing forest mortality risk, hydraulic traits, and climate adaptation.

• Biosurveillance of communicable diseases
• Infectious disease informatics
• Genomic epidemiology
• +3 more

Professor Vitali Sintchenko is a public health microbiologist and informatician at The University of Sydney, affiliated with the School of Medical Sciences , Sydney Infectious Diseases Institute , and Westmead Institute for Medical Research . As a Clinical Microbiologist with NSW Health Pathology , he develops genomic epidemiology tools for communicable disease surveillance, focusing on tuberculosis, pertussis, and Salmonella. His work integrates pathogen genomics with clinical data to improve outbreak detection and control. MBBS, PhD, FRCPA, FACHI Member, Commonwealth Public Health Laboratory Network and Communicable Diseases Genomics Network Leadership in Mycobacterium Reference Laboratory and Enteric & Pneumococcal Reference Laboratories Research spans: Genomic surveillance of epidemic bacterial pathogens Development of decision support systems for outbreak response Integration of syndromic surveillance with molecular epidemiology Microbiome analysis in respiratory infections Antimicrobial resistance genomics Machine learning applications in pathogen tracking Recent publications demonstrate leadership in Salmonella and Tuberculosis genomic epidemiology, with Nature , Lancet , and PLoS contributions. His team's work on SARS-CoV-2 variants and Shigella sonnei evolution highlights real-time surveillance applications. Scientific contributions include: World's first book on Infectious Disease Informatics (Springer, 2010) Development of MGTdb genomic database Creation of DODGE outbreak detection algorithm Advancements in CRISPR-based diagnostics Key role in Australian Pathogen Genomics Program As an academic leader, he supervises students working on: Ellen Donnan : TB control strategies in NSW David Pham : Metagenomic pathogen detection Sarah Smith : Pneumococcal disease genomics Michael Wehrhahn : Dientamoeba fragilis epidemiology His laboratory at Westmead Hospital develops: Genomic outbreak detection systems AI-driven surveillance tools Pathogen transmission mapping Drug resistance prediction models

• Geoinformatics
• Intelligence Informatics
• Geospatial Data Mining
• +7 more

Ickjai Lee is an Associate Professor at the School of IT, James Cook University, specializing in geoinformatics and intelligence informatics. He leads the Information Technology department and has held roles including Senior Lecturer and Lecturer since 2003. He obtained his PhD in 2002 from the University of Newcastle, Australia. Research Interests: Geospatial data mining, trajectory analysis, Voronoi tessellations, mobile AR, and IoT applications. Projects: Includes VR healthcare trials, AI-driven vehicle damage assessment, and environmental monitoring systems. His work focuses on applying machine learning and geospatial techniques to solve real-world problems in health, environmental, and urban domains. Notable achievements include best paper awards at international conferences and faculty citations for teaching excellence. He collaborates on interdisciplinary projects, such as using AR for marine growth monitoring and developing tools for crime pattern analysis. His research also involves large-scale ecoacoustic data analysis and VR-based education platforms. Lee has supervised numerous PhD students exploring topics like differential privacy in biokinetics, spatio-temporal anomaly detection, and VR in cultural heritage preservation.