جست‌وجوی استاد و پژوهشگر

Cheryl McCarthyمشاهده پروفایل

دانشیار

• Agricultural Engineering
• Machine Vision
• Robotics
• +۵ مورد دیگر

Dr. Cheryl McCarthy is an Associate Professor in Mechatronic Engineering and Senior Research Fellow at the University of Southern Queensland, focusing on automation and machine vision technologies in agriculture. She has been a full-time researcher since completing her PhD in 2009, with expertise in machine vision, robotics, and precision agriculture. Education: BEng (2005) and PhD (2004) in Mechatronic Engineering from the University of Southern Queensland. Research interests include crop disease detection (e.g., wheat root rot using NIR spectroscopy and machine learning), automation in farming operations, and robotic systems for precision agriculture. Her work spans orchard mapping, UAV-based irrigation monitoring, and livestock welfare assessment via machine vision. She has led projects on weed detection, fruit load estimation, and robotic navigation in agricultural environments. Key contributions include developing the 'MangoYOLO' deep learning model for fruit detection and advancing non-destructive crop sensing technologies. Her research integrates robotics, computer vision, and environmental sensing to address challenges in sustainable agriculture. Current and completed supervisions include projects on machine learning applications in meat processing, precision agriculture, and robotic localization in orchards. Major grants include farm trials for chicken welfare monitoring (2023), precision weed detection systems (2016), and harvester loss assessment (2019). Labs/Teams: Works within the Centre for Agricultural Engineering, collaborating on projects like space agriculture sensing and crop disease diagnostics.

• Surveying
• LiDAR Technology
• Cadastral Systems
• +۴ مورد دیگر

Glenn Campbell is an Associate Professor (Surveying) at the University of Southern Queensland's School of Surveying and Built Environment. His research spans spatial data law, LiDAR applications, cadastral systems, and remote sensing of water resources. Campbell employs advanced techniques including machine learning for topographic feature extraction and matrix inversion methods for water quality assessment. Research Focus: Geospatial law and indigenous land boundaries LiDAR processing for urban feature extraction Water quality remote sensing techniques Cadastral system modernization His publications demonstrate consistent focus on measurement accuracy, spatial data governance, and advanced geospatial analysis techniques. Recent work shows increasing emphasis on digital copyright issues in spatial data and machine learning applications for LiDAR processing. Awards & Recognition: No major scientific awards reported. Student Advising: No advisee information available.

Frits de Nijsمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Renewable Energy Systems
• Reinforcement Learning
• +۳ مورد دیگر

Frits de Nijs is a Research Fellow in the Department of Data Science & AI at Monash University. His work focuses on advancing artificial intelligence techniques for energy systems optimization, multi-agent decision-making, and sustainable infrastructure. He has contributed to projects such as the Human-in-the-loop Microgrid Project and RACE for 2030 CRC, addressing challenges in renewable energy integration and smart grid management. Key research areas include reinforcement learning applications for energy curtailment, HVAC control systems, and resource-constrained multi-agent planning. His projects often bridge AI methodologies with real-world energy challenges, aiming to enhance grid reliability, carbon efficiency, and fair resource allocation. Notable collaborations involve researchers in machine learning, sustainable energy, and building automation. He has actively participated in 6 major research projects since 2020, including initiatives on AI-ready buildings and probabilistic multi-agent learning environments. His publications span conferences like AAAI, NeurIPS, and IEEE Power & Energy Society events, emphasizing peer-reviewed contributions to energy-AI intersections.

Robert Anthonappaمشاهده پروفایل

استاد

• Dental Caries
• Pediatric Dentistry
• Traumatic Dental Injuries
• +۵ مورد دیگر

Robert Anthonappa is a Professor and Dean/Head of the Dental School at The University of Western Australia. His research focuses on pediatric dentistry, dental caries, traumatic injuries, and innovative diagnostic technologies. He actively contributes to UN Sustainable Development Goals through oral health research. Key Research Areas: Dental Caries, Traumatic Dental Injuries, Eye Tracking, Children's Oral Health, Artificial Intelligence in Dentistry, Remineralization Therapies. Recent Publications: Systematic reviews on mobile health apps for dental trauma, AI in caries detection, and studies on supernumerary teeth localization. Grants: Led projects on fluoride intake, eye-tracking technology, and remineralization potential of toothpastes using Micro-CT and Raman Spectroscopy. Awards: Recipient of the Dental School Mid-Career Research Award (2022). Collaborations: Works with international institutions on pediatric dental research, including projects in India and Australia. Editorial Roles: Associate Editor for the International Association of Paediatric Dentistry. His work emphasizes evidence-based practices, with a focus on improving diagnosis, prevention, and management of dental conditions in children through advanced imaging and behavioral studies.

Onkar Jadhavمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Computational Science
• Applied Mathematics
• +۵ مورد دیگر

Onkar Jadhav is a Research Fellow at the University of Western Australia's School of Earth and Oceans, specializing in developing machine learning frameworks for oceanography and computational science. His work focuses on statistical downscaling techniques for ocean temperature predictions and reduced-order modeling for financial risk analysis. Previously, he was a postdoctoral researcher at the University of Luxembourg, where he applied machine learning to wind engineering and computational fluid dynamics. Education: He holds a Doctorate in Applied Mathematics from the Technical University of Berlin (2018–2022), with a thesis on physics-assisted machine learning for high-dimensional partial differential equations. His academic background bridges mathematics, engineering, and computational science. Research Interests: Jadhav’s expertise spans machine learning, computational science, and applied mathematics, with applications in oceanography, wind engineering, and financial risk analysis. He emphasizes interdisciplinary approaches to solve complex, high-dimensional problems. Publications: His research includes advancements in model order reduction for parametric systems in finance, wind load assessments using machine learning, and thermoelectric generator design for biomedical implants. Labs/Teams: Affiliated with the Oceans Graduate School and previously with the University of Luxembourg’s wind engineering team.

• Biomedical Engineering
• Medical Imaging
• Optical Coherence Tomography
• +۳ مورد دیگر

Andrea Curatolo is an Adjunct Research Fellow at the School of Engineering, University of Western Australia, specializing in Electrical, Electronic and Computer Engineering. He holds a PhD from the same university, focusing on improving optical coherence tomography (OCT) and elastography through optical beam shaping and simulations. His research emphasizes biomedical applications, particularly in ophthalmology and cancer diagnostics, contributing to UN Sustainable Development Goals in health and innovation. Key areas include corneal biomechanics, retinal imaging, and telehealth technologies like smartphone-based optical palpation for skin and breast tissue analysis. Collaborations span global institutions, advancing non-invasive diagnostic methods. Education: PhD in Optical Imaging Technologies (UWA, 2017); BSc and MSc from Polytechnic of Milan. Research interests integrate OCT, elastography, and machine learning to address challenges in ophthalmic surgery, cancer margin assessment, and telemedicine. His work bridges engineering and clinical needs, with over 46 publications and 1503 citations, reflecting contributions to high-resolution imaging and biomechanical analysis. Recent articles highlight advancements in spatio-temporal OCT (STOC-T) for retinal hemodynamics, chirped flicker optoretinography, and cross-meridian air-puff OCT for keratoconus detection. Innovations in low-cost imaging systems and robotic tool tracking aim to democratize medical diagnostics. His lab develops handheld elastography probes and smartphone-integrated palpation tools, advancing point-of-care solutions. Awards: While no specific honors are listed, his high citation count and h-index (21) underscore peer recognition. Supervised work includes mentoring students on biomechanical and imaging projects.

Krishna Manaswi Digumartiمشاهده پروفایل

مدرس

• Soft Robotics
• Healthcare Robotics
• Medical Robotics
• +۷ مورد دیگر

Dr. Krishna Manaswi Digumarti is a Lecturer in Robotics at the School of Electrical Engineering and Robotics, QUT, leading the QUT Centre for Robotics. He holds a PhD in Robotics and Autonomous Systems from the University of Bristol (2019), an M.Sc. in Robotics, Systems, and Controls from ETH Zurich (2014), and a B.Tech. in Mechanical Engineering from IIT Hyderabad (2012). His research focuses on soft robotics, including shape morphing, variable stiffness mechanisms, and bio-inspired designs with applications in healthcare, automation, and haptics. He has pioneered technologies such as electro-adhesive clutches, self-healing robotic materials, and sensory feedback systems for prosthetics. Dr. Digumarti's work has been featured on the BBC, Channel 4, and French media, and he has secured grants including the Advanced Queensland Industry Research Fellowship. He actively engages in STEM outreach, including workshops and collaborations with industry partners like Disney Research and EPFL.

Nicolas Chapmanمشاهده پروفایل

پژوهشگر

• Robotics
• Machine Learning
• Uncertainty Modelling
• +۳ مورد دیگر

Nicolas Chapman is a PhD Researcher at the Queensland University of Technology (QUT) Centre for Robotics. His research focuses on uncertainty quantification in sensor-based systems and machine learning, particularly for agricultural and environmental robotics. He investigates how uncertainty in these systems can be modeled, quantified, and integrated into mission planning to improve outcomes in challenging environments. His work bridges robotics, machine learning, and environmental science, emphasizing practical applications in agriculture and autonomous systems. Recent publications explore embodied AI, domain adaptation in object detection, and deep learning for livestock heat stress prediction. Nicolas collaborates with the QUT Centre for Robotics, contributing to advancements in reliable robotic decision-making under uncertainty. He holds an email address at the Higher Degree Research (HDR) program.

• Medical Imaging Analysis
• Deep Learning
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Laith Alzubaidi is a postdoctoral researcher at the School of Mechanical, Medical and Process Engineering , Queensland University of Technology (QUT) , Australia. He earned his Ph.D. in 2022 in medical imaging analysis with deep learning from QUT and a master’s degree in computer science from the University of Missouri (2016), USA. His research interests span medical imaging analysis , deep learning , artificial intelligence , and computational mechanics . He has contributed to advancements in bone fracture detection , skin cancer classification , IoT security frameworks , and physics-informed neural networks , with a focus on data fusion , adversarial attack detection , and real-time diagnostic systems . Dr. Alzubaidi has published over 53 refereed papers, garnered more than 3,700 citations, and led two special issues in reputed journals. His work involves global collaborations and grants for deep learning in medical applications . He reviews for 53+ journals, including IEEE Transactions on Medical Imaging and Information Fusion . Scientific Awards : Scholarship during master’s degree (University of Missouri) QUT scholarship for Ph.D. His recent publications highlight trends in AI-driven medical imaging , secure IoT networks , and physics-informed computational models . He has also explored trustworthy AI , reinforcement learning in healthcare , and explainable machine learning frameworks .

Zahra Gharineiatمشاهده پروفایل

دانشیار

• UAV Applications
• LiDAR and Feature Extraction
• Digital Twins
• +۵ مورد دیگر

Associate Professor Zahra Gharineiat is a faculty member at the University of Southern Queensland's School of Surveying and Built Environment, specializing in Surveying and Positioning. She holds a PhD in Surveying and has over a decade of experience in academia and industry. Zahra serves as Associate Head of School (Research) and leads research in UAV applications, LiDAR, AI-enabled monitoring, and spatial data analytics. She has secured over $6 million in research funding and founded the nationally recognized 'Drones for STEM' initiative promoting STEM education through drone learning. Education: Bachelor of Surveying (BSurv) from Tabriz University Master of Engineering Management (MEngMgt) from University of Melbourne PhD in Surveying from University of Newcastle Research Interests: Unmanned Aerial Vehicles (UAVs) and Remote Sensing LIDAR and Feature Extraction Digital Twins and Spatial Data Analysis Machine Learning Applications in Geospatial Data Coastal Monitoring and Sea Level Analysis Satellite Altimetry and Geodesy Her work bridges geomatic engineering with environmental and civil applications, emphasizing innovation in surveying technologies. Awards & Recognition: Multiple awards for research, teaching, and innovation (specific names unspecified) Active member of international geospatial organizations including the International Federation of Surveyors (FIG) and IEEE Geoscience Society Grants & Collaboration: Secured over $6M in research funding Key roles in interdisciplinary projects with the Centre for Future Materials and Institute for Advanced Engineering and Space Sciences Labs & Initiatives: Founder of the 'Drones for STEM' education program Lead researcher in UAV-based monitoring and LiDAR applications

• Epidemiology
• Mathematical Biology
• Infectious Disease Modeling
• +۶ مورد دیگر

Roslyn I. Hickson is a Researcher at James Cook University, specializing in mathematical biology and epidemiology. Her work bridges computational methods with public health challenges, focusing on infectious diseases like malaria, dengue, and tuberculosis. Key collaborations with institutions such as the University of Melbourne, Burnet Institute, and Australian National University. Active in interdisciplinary research, including One Health and behavioral disease transmission models. Roslyn's research centers on modeling disease dynamics, integrating factors like population heterogeneity, stigma, and environmental variables. Her studies address zoonotic spillover risks, optimal intervention strategies, and reproducibility in epidemic modeling. Recent publications highlight trends in computational epidemiology, particularly for diseases with complex transmission cycles (e.g., P. vivax malaria, Japanese Encephalitis) and societal impacts (e.g., stigma-driven mental health trends). She employs machine learning and spatial modeling for pathogen prediction. Her contributions include frameworks for health worker allocation, tuberculosis control cost-effectiveness, and Wolbachia's role in dengue suppression, reflecting a broad application of mathematical models to global health security.

• Meniere's Disease
• Neurosciences
• Genetics
• +۳ مورد دیگر

Professor Jose Antonio Lopez-Escamez is a leading researcher in Meniere's disease and neurosciences at the University of Sydney's School of Medical Sciences. He established the Otology and Neurotology Research Group in Spain and leads the Meniere’s disease Neuroscience Research Program at Sydney, with a laboratory at The Kolling Research Institute. Established international research group (2002) Recipient of Frontiers Spotlight Award (2018) Stanford World Top 2% Scientists (2021-22) Supervised 12 PhD and 27 Master's students Secured >7 million in competitive European funding Research Focus: Genetics and immune mechanisms of Meniere’s disease and severe tinnitus, using multi-omic data, cellular models, and animal studies to uncover molecular pathways and develop cures. His work bridges genomic medicine with clinical neurotology. Recent Article Trends: 2025 publications emphasize genetic variants (ANK2, KIF1B), immune profiling (cytokines, NK cells), and machine learning for disease classification. Translational studies link mitochondrial dysfunction to familial Meniere’s and explore AI-driven treatment recommenders. Scientific Awards: Frontiers Spotlight Award (2018) Global Otology Research Forum Prize (2018) Bronze Medal - Spanish Society of Otolaryngology (2009) Outstanding PhD Award - University of Granada (1998) Supervision & Grants: Mentored over 39 students. Secured substantial funding for Meniere’s disease research. Collaborates with institutions like Universidad de Granada, Genyo, and top universities in Europe and Australia.

• Power Systems
• Renewable Energy
• Estimation Theory
• +۳ مورد دیگر

Tyrone Fernando is a Professor at the University of Western Australia (UWA), Department of Electrical, Electronic and Computer Engineering (EECE) within the School of Engineering. He joined UWA in 1996 after earning his BE (Honours) in 1990 and PhD in 1996 from the University of Melbourne. His professional roles include Deputy Head of School (2009–2010) and editorial leadership for journals like IEEE Transactions on Circuits and Systems II and IEEE Access. He is a Senior Member of IEEE and former Chair of the IEEE Circuits and Systems Society’s Power and Energy Technical Committee. Education: Bachelor of Engineering with Honours (1990), University of Melbourne Doctor of Philosophy (1996), University of Melbourne Research Interests: His work focuses on power systems, renewable energy integration, and estimation theory applications. Key emphases include DC microgrid control, advanced battery technologies (e.g., vanadium redox, lithium-ion), model predictive control (MPC) strategies, and sensorless control methods for motor drives. He also investigates stability criteria for power systems with high penetration of power electronics and energy storage optimization. Grants & Projects: He leads grants such as: Seeding marine innovation in SW WA with a WEC deployment in Albany (Blue Economy CRC, 2021–2025) Mine Electrification (CRC for Future Battery Industry FBI, 2022–2024) Project Symphony (Western Power, 2021–2023) These initiatives address grid resilience, battery-electric vehicle infrastructure, and renewable energy integration challenges. Awards: Outstanding Engineer award, IEEE PES WA Chapter (2019) Collaborations: His research involves interdisciplinary teams and industry partners, including Western Power and the Department of Industry, Science and Resources (Australia). He contributes to projects like DC-link capacitance estimation and stability analysis of offshore wind farms.

Shaokoon Chengمشاهده پروفایل

دانشیار

• Biomechanics
• Aerosol Diagnostics
• Biomedical Devices
• +۵ مورد دیگر

Shaokoon Cheng is an Associate Professor in Mechanical Engineering at Macquarie University, serving as Program Director for the Mechanical Engineering undergraduate and Master's programs. He pioneered the establishment of these programs and has led over 140 peer-reviewed publications, six patents, and significant research funding, including ARC and NHMRC grants. As Chief Technology Officer of ASKSCIENTIA, he translates research into medical technologies like aerosol diagnostics and biomedical devices. He currently supervises 9 HDR students and has guided 18 to completion, emphasizing mentorship in innovation and translation. His research focuses on biomechanics, aerosol systems, organ-on-chip technology, and thermal management. Key projects include drug delivery mechanics, organ-on-chip development, and advanced manufacturing. He holds equipment such as stereoscopic PIV, high-speed imaging systems, and optical coherence tomography. He is actively involved in professional societies like the Australian Rheological Society and Australian and New Zealand Society of Biomechanics. Education: PhD in Biomedical Engineering (UNSW), BEng (Mechanical Engineering) with First Class Honors (University of Sydney). Research Interests: Biomechanics of drug delivery, organ-on-chip devices, 3D printing for bio-applications, and aerosol flow characterization. His lab equipment includes advanced imaging and testing systems, supporting interdisciplinary projects in biomedical engineering and mechanical design. Awards: Australian Postgraduate Award (2003), Engineering Postgraduate Award (2003), International Grant (2008), Travel Awards (2009, 2011). Teaching: Focuses on improving student employability and entrepreneurship through innovative pedagogies. Projects include developing digital reality modules for fluid mechanics education.

Brian Ballsun-Stantonمشاهده پروفایل

پژوهشگر

• Digital Humanities
• Generative AI
• Natural Language Processing
• +۴ مورد دیگر

Dr Brian Ballsun-Stanton is a Solutions Architect (Digital Humanities) at Macquarie University's Faculty of Arts. He specializes in AI integration in higher education, leading initiatives such as the university's 'Guidance Note: Using Generative AI in Research' and winning the 2024 Faculty of Arts Educational Leadership Award. His work spans AI policy, pedagogy, and interdisciplinary applications across languages, security studies, and law. With over 15 years' experience as a data scientist, he has pioneered open-source tools like FAIMS Mobile for field research and led AUD$3.5M+ in grants focused on big data analysis of violent extremism and archaeological projects. Education: PhD in Philosophy of Data (not explicitly stated, inferred from biography). Research Interests: Generative AI ethics, digital humanities, social network analysis, and the intersection of technology with humanities scholarship. He focuses on AI-enhanced learning, critical evaluation of large language models, and FAIR data principles in epigraphy and archaeology. Articles Trends: Recent work emphasizes AI policy frameworks, generative AI applications in education, and computational methods in archaeology. Earlier publications explore far-right online ecosystems and social media analysis. Awards: 2018 DataApp Prize (environmental data transparency), 2024 Educational Leadership Award. Grants/Projects: Led projects on violent extremism (AUD$3.5M+), FAIMS Mobile development, and Roman Dalmatia military communities. Technical Director of FAIMS Project since 2013. Labs/Teams: Technical lead for the FAIMS Project, collaborating internationally on archaeological digital tools and open-source field data systems.