جست‌وجوی استاد و پژوهشگر

• Biomedical Imaging
• Neuroimaging
• Neurodegenerative Diseases
• +۳ مورد دیگر

Professor Gary Egan is a leading neuroscientist at Monash University's Monash Biomedical Imaging department. He specializes in neurodegenerative diseases such as Huntington's and Friedreich's ataxia, using advanced imaging techniques like MRI and X-ray synchrotron imaging to map disease progression. His research focuses on early detection of brain changes to enable preventive treatments, leveraging cutting-edge technologies such as deep learning for medical image analysis. Research Interests: Biomedical imaging and neuroimaging techniques Neurodegenerative disease mechanisms Early biomarker identification for neurodegenerative conditions Medical imaging technology development (MRI, PET-MR, synchrotron imaging) Projects: Leading studies on Huntington's disease using MRI to track brain changes Mouse model studies at the Australian Synchrotron to investigate cellular-level disease progression Cross-disciplinary collaborations in AI-driven medical image reconstruction (e.g., CL-MRI, Co-Manifold learning) Grants & Collaborations: Chief investigator on NHMRC-funded projects studying brain structure/function impacts Collaborations in AI-based image analysis frameworks International partnerships in neuroimaging and metabolic connectivity research Labs/Teams: Leads the Monash Biomedical Imaging team, collaborating with institutions like the Victorian Heart Institute (VHI) and Australian Synchrotron. Active in global initiatives like ENIGMA-Ataxia for coordinated neuroimaging research.

• Artificial Intelligence
• Machine Learning
• Cloud Computing
• +۴ مورد دیگر

Cheng-Hao Cai serves as an Adjunct Lecturer in the Department of Data Science & AI at Monash University. His research focuses on interdisciplinary applications of AI, including cloud computing, software engineering, and industrial process optimization. He collaborates with the Monash Suzhou Research Institute on patents related to smart manufacturing and data-driven methodologies. Key research interests include AI-driven modeling for quality prediction in cokemaking, service-oriented cloud scheduling, and advanced NLP techniques like Chinese named entity recognition. His work integrates deep learning frameworks with domain-specific challenges, such as lattice-transformer-graph models for language processing and automated refactoring of state transition models. Cai has contributed to 23 research outputs since 2014, with recent publications emphasizing practical AI solutions for industry and computational systems. His patents highlight collaboration between academia and industry, particularly in Suzhou.

• Control Theory
• Fault Detection
• State Estimation
• +۶ مورد دیگر

Tan Chee Pin is an Associate Professor and Head of the Mechatronics Engineering program at Monash University Malaysia. His research focuses on observer design for system state estimation, with applications in robotics, traffic management, and energy systems. He has published extensively in top journals like IEEE Transactions on Automation Science and Engineering, and secured RM1.5m in research funding. His teaching emphasizes student-centric approaches, earning him internal awards and a national educator award nomination. Research interests include model-based observer configurations for minimizing sensor usage, condition monitoring, and predictive maintenance. Applications span soft robotics, traffic congestion reduction, and energy optimization. He collaborates on projects like IoT-based predictive maintenance systems and solar technology for Orang Asli communities. Editorial roles include associate editorships at IEEE Transactions on Cybernetics and the Journal of the Franklin Institute. Awards include finalist status for the 2018 National Outstanding Educator’s Award. Advising includes supervising 7 PhD completions and 13 current students. Projects include smart drone trash monitoring and control systems for soft robots using few-shot learning.

• Computer Vision
• Robotics
• Remote Sensing
• +۳ مورد دیگر

Boying Li is a Research Fellow in the Department of Data Science & AI at Monash University. Their research focuses on advancing computer vision, robotics, and remote sensing technologies. Key contributions include developing SLAM algorithms using semantic planar text features, self-supervised depth estimation systems, and SAR datasets for ship interpretation. Research interests span neuro-symbolic AI frameworks, autonomous navigation, and sensor data fusion. Their work contributes to the UN Sustainable Development Goals through applications in maritime surveillance and autonomous systems. Collaborations involve structural regularities in indoor environments and satellite imagery analysis. Notable outputs include the OpenSARShip dataset (2017–2018) and recent advancements in Hier-SLAM++ (2025). Awards and grants are not explicitly listed in available texts. No lab affiliations or future works are detailed.

Ye Luمشاهده پروفایل

دانشیار

• Structural Health Monitoring
• Smart Materials and Structures
• Advanced Signal Processing
• +۵ مورد دیگر

Ye Lu is an Associate Professor in Structural Engineering at Monash University's Department of Civil and Environmental Engineering, leading the Civil Master Program. He holds a PhD in Mechanical Engineering from the University of Sydney (2007) and has been awarded an Australian Research Council (ARC) Discovery Project and ARC Australian Postdoctoral Fellowship (2008). His research focuses on structural health monitoring, smart materials, and artificial intelligence applications in civil engineering infrastructure. Dr. Lu leads projects such as the ARC Research Hub for Smart Next Generation Transport Pavements and the Non-contact Integrity Assessment of High-rise Building Facades. Education: PhD in Mechanical Engineering, University of Sydney, Australia (2007) Research Interests: Structural health monitoring Smart materials and structures Advanced signal processing and AI Infrastructure durability Projects: SPARC: ARC Research Hub for Smart Transport Pavements (2019–2025) Non-contact Façade Panel Integrity Assessment (2020–2025) Smart Sensing for Construction Monitoring (2019–2024) Awards: ARC Australian Postdoctoral Fellowship (2008) ARC Discovery Project Grant (2008) Teaching & Advising: PhD supervision in structural engineering and smart materials Courses: CIV3294, CIV5135 (Advanced Structural Design), CIV5887 (Infrastructure Monitoring) Labs/Teams: Leader of the Civil Master Program, collaborator in interdisciplinary projects across Monash and industry partners like Transurban and EON Reality.

Sandra Rodriguesمشاهده پروفایل

پژوهشگر ارشد

• Coal Petrology
• Carbon Materials
• Geochemistry
• +۴ مورد دیگر

Dr Sandra Rodrigues is an Honorary Senior Research Fellow at the School of the Environment, University of Queensland. Her research focuses on coal petrology, carbon materials, and geochemistry, with emphasis on thermal maturation, organic geochemistry, and coal seam gas potential. She has authored over 60 peer-reviewed articles, contributing to global understanding of coal structure, hydrocarbon generation pathways, and applications in energy and environmental sectors. Her work spans coal characterization via hyperspectral imaging, coking behavior analysis, and high-temperature material transformation studies. Key projects include investigations into the Toolebuc Formation’s unconventional gas potential and thermal evolution in Mozambique’s Moatize Basin. Rodrigues collaborates internationally on coal classification systems (e.g., ICCP Working Groups) and has pioneered deep learning applications in coal reflectance measurement. Recent research highlights include studies on lithium-enriched coals in China, Jurassic fluid events in Australian basins, and carbon isotope evidence of methane clathrate release during deglaciation. Her interdisciplinary approach bridges geology, chemistry, and engineering, addressing challenges in resource characterization, environmental management, and energy sustainability.

• Medical Imaging
• MRI Technology
• Superconductivity
• +۵ مورد دیگر

Professor Feng Liu is a faculty member at the University of Queensland's School of Electrical Engineering and Computer Science. His expertise spans cutting-edge research in medical imaging technologies, superconductivity applications, and biomedical engineering. He specializes in MRI system design, including cryogen-free superconducting magnet development and advanced imaging techniques like quantitative susceptibility mapping. His work integrates artificial intelligence and deep learning to enhance medical diagnostics and imaging precision. Liu has authored over 500 publications, focusing on topics such as magnetic resonance fingerprinting, sensor technology for energy storage, and genetic studies in population biology. His contributions bridge electrical engineering, physics, and healthcare, with a strong emphasis on translating research into practical medical solutions.

• Geospatial Information Systems
• 3D GIS
• BIM/GIS Integration
• +۷ مورد دیگر

Professor Sisi Zlatanova is a Professor at the University of New South Wales (UNSW), affiliated with the School of Arts, Design & Architecture. She holds a PhD in 3D GIS for Urban Development from Graz University of Technology and has held academic positions globally, including at ITC (Netherlands) and Delft University of Technology. Her research focuses on 3D spatial modeling, BIM/GIS integration, emergency response systems, and indoor navigation. Key projects include UNSW precinct modeling, indoor scanning for emergency response, and voxel-based visibility analysis for safety. Her research activities span over 300 publications and 23 edited books, with notable works on 3D GIS applications and disaster management. She leads international initiatives like ISPRS TC IV (Spatial Information Science) and OGC SWG IndoorGML. Her work emphasizes practical applications in urban resilience, sustainable design, and crisis management. Professor Zlatanova's contributions include developing frameworks for smart indoor models, integrating BIM with GIS for emergency response, and leveraging LiDAR and UAV technologies for urban analysis. She collaborates extensively with global organizations, advancing geospatial solutions for urban challenges.

Greg Stuartمشاهده پروفایل

استاد

• Neuroscience
• Dendritic Integration
• Neuronal Signaling
• +۲ مورد دیگر

Professor Greg Stuart leads the Neuronal Signalling Group at Australian National University's John Curtin School of Medical Research. His research investigates information processing in cortical neurons using electrophysiological and imaging techniques to study dendritic integration mechanisms. With over 90 publications on dendritic signaling and neural computation, his work combines experimental approaches with computational modeling to understand neuronal function in learning, visual processing, and decision-making.

Chengxin Jiangمشاهده پروفایل

پژوهشگر ارشد

• Seismology
• Tectonic Processes
• Magmatic Systems
• +۳ مورد دیگر

Dr. Chengxin Jiang is an ARC DECRA Research Fellow in Geophysics at the Research School of Earth Sciences (RSES), ANU. He holds affiliations with Harvard University and the University of Tokyo, where he has conducted visiting research. His work focuses on seismology, particularly tectonic and magmatic processes, employing techniques like ambient noise interferometry and seismic tomography. Education: Ph.D. in Geophysics, Macquarie University (2012–2016) M.Sc. in Geology, China University of Geosciences (2010–2012) B.Sc. in Geology (Honor Class), China University of Geosciences (2006–2010) Research Interests: Jiang’s research explores shallow Earth imaging, volcanic and groundwater monitoring, lithosphere deformation, and machine learning applications in geophysics. He develops novel techniques for seismic detection and utilizes dense seismic arrays to study subsurface structures. Recent projects include imaging Zealandia’s lithosphere and monitoring groundwater variations in Australia’s Great Artesian Basin. Teaching: Leads courses in Structural Geology and Tectonics (EMSC3002), Special Topics (EMSC3050), and Research Proposal and Presentation (EMSC8032) at ANU. Advising & Grants: Supervises multiple PhD, Master’s, and Honors students. Leads projects funded by ARC DECRA and industry partnerships, focusing on energy resource exploration and environmental monitoring. Labs & Collaborations: Collaborates with international teams on seismic imaging and hosts datasets like the Eyre Peninsula Nodal Array (DOI:10.7914/ac1p-7y35). Active in editorial roles, including Journal of Earth, Planets and Space .

• Machine Learning
• Planning with Machine Learning
• Weakly Supervised Learning
• +۳ مورد دیگر

Yingbin Bai is a Research Fellow at Australian National University's School of Computing, collaborating with Professor Sylvie Thiebaux. His research focuses on machine learning applications in planning, weakly supervised learning, and unsupervised representation learning. He holds a PhD supervised by Professors Tongliang Liu and Dadong Wang. His work emphasizes addressing challenges in noisy label environments, early stopping techniques, and biomedical image analysis. Key contributions include QUBIQ (uncertainty quantification in medical imaging) and frameworks for robust representation learning under imperfect data conditions. Publications span topics like symmetry breaking in learning systems, semantic shift mitigation in self-supervised learning, and analysis of biomedical image competition practices. Collaborations involve cross-disciplinary teams tackling both theoretical and applied machine learning problems.

Meghan Millerمشاهده پروفایل

استاد

• Geophysics
• Tectonics
• Subduction Zones
• +۵ مورد دیگر

Prof. Meghan Miller is a Professor in the Research School of Earth Sciences at The Australian National University (ANU), specializing in geophysics with a focus on tectonic plate boundaries and subduction zones. Her research integrates seismic imaging and cutting-edge technologies like Distributed Acoustic Sensing (DAS) to explore Earth's subsurface dynamics, particularly in regions of active tectonics such as Indonesia and Alaska. She holds a PhD in Geophysics from ANU (2006) and has held academic appointments at institutions including the University of Southern California and Rice University. Her research interests include the evolution of continental lithosphere, the interplay between surface geology and deep mantle processes, and the application of DAS to monitor seismic activity and crustal deformation. Notable projects include the ARC Future Fellowship (2022–2026) advancing DAS technology for high-resolution subsurface imaging. Key areas of exploration include subduction zone dynamics, crustal structure in stable continents, and the geodynamics of collision zones. Her work bridges field observations with advanced computational models, contributing to understanding processes like the opening of the North Atlantic Ocean and the uplift of Scandinavian mountains. Grants include leadership in the ARC Centre of Excellence in Optical Microcombs and projects on seismic anisotropy and mantle flow deflection. Prof. Miller’s contributions span over 100 peer-reviewed publications, with recent work emphasizing DAS applications (e.g., SISSLE experiment in New Zealand), seismic imaging of urban environments, and interdisciplinary collaborations in geophysics and tectonics.

Nyoman Kurniawanمشاهده پروفایل

پژوهشگر ارشد

• Magnetic Resonance Imaging (MRI)
• Neuroanatomy
• Medical Imaging
• +۴ مورد دیگر

Dr Nyoman Kurniawan is a Senior Research Fellow at the Centre for Advanced Imaging and Facility Manager for the Preclinical 16.4T Microimaging 9.4T MRI scanners at the Queensland Brain Institute, University of Queensland. His research focuses on advanced MRI techniques, including diffusion MRI in neurological disease models, 3D brain atlases, and applications in nephron and agricultural imaging. He holds a PhD in structural biology from The University of Queensland (2002). His expertise spans neuroimaging, developmental neurobiology, and translational MRI methodologies. Key contributions include developing MRI protocols for small animal studies, investigating spinal cord pathologies, and applying imaging to study brain connectivity in mouse models. His work bridges clinical and basic science, with applications in neurodegenerative diseases, trauma, and marine biology. Dr Kurniawan collaborates internationally on spinal cord MRI standards and has pioneered studies on octopus brain structure and octopus mating behavior. He also explores the effects of vitamin D deficiency on neuroanatomy and leverages deep learning for motion correction in kidney imaging. His lab contributes to open-access neuroimaging data and collaborates with institutions globally to advance imaging reproducibility.

Dilki Jayasingheمشاهده پروفایل

پژوهشگر

• Dermatology
• Medical Imaging
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

Dilki Jayasinghe is a Postdoctoral Researcher at the Centre for Health Services Research, The University of Queensland. Their work focuses on melanoma diagnosis, medical imaging technologies, and applications of artificial intelligence in healthcare. They lead research projects involving 3D total-body photography for early melanoma detection and have contributed to studies analyzing the impact of the pandemic on cancer diagnosis patterns. Research interests include dermatological risk assessment, automated lesion detection, and population health surveillance. Their interdisciplinary approach combines clinical data with advanced imaging and machine learning techniques to improve early cancer detection methods. Key projects include randomized clinical trials evaluating 3D photography efficacy and systematic reviews of nevus-counting methodologies. Publications highlight innovations in automated skin surface phenotyping, BMI estimation from 3D imagery, and statistical modeling of naevus distribution. This work bridges clinical practice with technological advancements, aiming to enhance diagnostic accuracy and reduce melanoma mortality rates. No scientific awards are listed, but their contributions to melanoma imaging research are recognized through collaborative projects with the Australian Centre of Excellence in Melanoma Imaging & Diagnosis (ACEMID). Grant-funded research includes ACEMID initiatives and a 2021 study on melanoma risk factors using 3D photography. Advising activities are not explicitly documented, though their work involves supervising research teams in imaging and data analysis projects. Laboratory affiliations include the Centre for Health Services Research facilities at UQ, focusing on translational medical imaging research.

Aaron S.W. Wongمشاهده پروفایل

مدرس پاره‌وقت

• Computer Science
• Artificial Intelligence
• Robotics
• +۱۶ مورد دیگر

Dr Aaron Wong is an Honorary Lecturer at the School of Psychology , University of Newcastle , with dual affiliations in Computer Science and Software Engineering . His career spans interdisciplinary research in robotics, cognitive neuroscience, and neuroimaging, supported by roles in the Functional Neuroimaging Laboratory and Priority Research Centre for Stroke and Brain Injury . Education: PhD in Computer Science, University of Newcastle Bachelor of Engineering (Computer Engineering) with Honours Bachelor of Computer Science Research Focus: Dr Wong's work bridges machine learning , humanoid emotion modeling , and multimodal neuroimaging (MRI/EEG). Key projects include developing brain-computer interfaces , acoustic localization systems for rescue robots, and semi-supervised manifold alignment techniques. Publication Trends: Recent articles emphasize theta oscillations in cognitive control , EEG-MRI joint modeling , and deep learning for speech emotion recognition . Collaborative themes span neurodevelopmental studies , stroke research , and urban robotics . Scientific Awards: 2008 RoboCup SPL World Champion 2011 RoboCup Australian Open Champion 2014 Global Leader of Innovation (UON) 2011 Best Student Paper (ANZAScA) Supervision & Grants: Served as co-supervisor for two PhD students. Secured $23,775 in grants including a 2018 Hunter Medical Research Institute award for EEG-MRI predictive modeling and 2016 Keats Endowment funding for cognitive flexibility research . Labs & Teams: Central to the Functional Neuroimaging Laboratory and PRC Stroke and Brain Injury , with global RoboCup collaborations and contributions to the Age-ility Project data repository.