جست‌وجوی استاد و پژوهشگر

Ajmal Mianمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۸ مورد دیگر

Ajmal Mian is a Professor of Computer Science at the University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing. He holds an Australian Research Council Future Fellowship (2022) and leads research in Artificial Intelligence, Computer Vision, and Machine Learning. His work focuses on 3D computer vision, adversarial AI defense, and explainable AI. His research interests include 3D point cloud analysis, face recognition, human action recognition, and remote sensing. He has published over 300 papers and secured major grants from ARC, NHMRC, and DARPA, totaling millions in funding. He has supervised 29 PhD students and mentored 12 postdoctoral researchers. Key projects include 3D diffusion models for scene generation, robust 3D vision systems, and defense against AI deception attacks. He serves as a fellow of IAPR, an ACM Distinguished Speaker, and has editorial roles at IEEE Transactions on Neural Networks and Pattern Recognition. Research Awards: HBF Mid-Career Scientist of the Year, West Australian Early Career Scientist of the Year, IAPR Best Scientific Paper Award. Grants: ARC Discovery Projects, National Intelligence & Security Discovery grants, DARPA grants for AI security. His teaching spans computer vision, machine learning, and programming courses. Collaborations include defense, medical, and agricultural applications.

• Robotics
• Mechatronics
• Human-Robot Interaction
• +۳ مورد دیگر

Mr. Richardo Khonasty is a Senior Research Engineer at the School of Mechanical and Mechatronic Engineering, part of the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). He has held appointments at UTS since 2019, including roles at the Centre for Autonomous Systems and Robotics Institute. He also serves as a Tutor since 2016. PhD in Robotics (2020), UTS B.Eng. in Mechanical and Mechatronic Engineering (2014), UTS Khonasty's research focuses on robotics and human-robot collaboration, with applications in surgical robotics (total hip replacement), industrial automation (abrasive blasting), and green wall inspection systems. His work emphasizes kinematic accuracy, adaptive control schemes, and cost-effective robotic solutions. His recent publications explore robotic-assisted burring for orthopedic surgery, damping strategies for singularity management, and exoskeleton design frameworks. Khonasty is currently involved in funded research related to hydraulic tooling safety under the BTP - Stage 2 - IntelliForce Tooling grant.

• Medical Imaging
• Computed Tomography
• Inverse Problems
• +۳ مورد دیگر

Dr. Owen Dillon is a Research Fellow in the Discipline of Medical Imaging Sciences at the University of Sydney's Faculty of Medicine and Health. He holds affiliations with the ACRF Image X Institute and the Dodd-Walls Centre for Photonic and Quantum Technologies. His work focuses on advanced imaging techniques for medical applications, particularly computed tomography (CT) and motion compensation in radiation therapy. He completed his PhD in Mathematics at the University of Auckland, specializing in probabilistic compression algorithms for inverse problems. Education: B.Sc. Physics & Applied Mathematics (2013, University of Auckland), First Class Honours in Mathematics (2015), PhD Mathematics (2018). Research interests include inverse problems, Bayesian statistics, CT image reconstruction, and real-time imaging systems. Current projects involve optimizing CT acquisition geometries, motion-compensated 4D imaging, and anatomical motion estimation. His contributions have led to clinical trials reducing radiation dose and scan times. He advises two PhD students and collaborates on grants like the Quantum CT project. Grants: 'Quantum CT for Cancer Diagnosis' (2024), 'Functional Imaging in Lung Cancer' (2024). His work bridges mathematical theory with clinical applications in oncology and interventional radiology.

Yang Songمشاهده پروفایل

دانشیار

• Computer Vision
• Deep Learning
• Multimodal AI
• +۷ مورد دیگر

Yang Song is an ARC Future Fellow and Scientia Associate Professor at the School of Computer Science and Engineering , University of New South Wales (UNSW) . She serves as Associate Head of School (Research) and Co-Director of iCinema , focusing on AI and Computer Vision applications for social good. Education: BEng in Computer Engineering (Nanyang Technological University, Singapore), PhD in Computer Science (UNSW, 2013) Research Areas: Biomedical image analysis, human-centred AI, graph data modeling, neuro-symbolic learning, and AI trustworthiness. Her work develops domain-specific deep learning models for radiological segmentation, histopathology cancer analysis, and 3D reconstruction. Recent projects address explainability in LLMs, fairness in AI, and human-robot interaction frameworks. With over 200 peer-reviewed publications in top venues like CVPR , MICCAI , and NeurIPS , her research spans biomedical imaging, robotics, and general multimodal AI. Scientific Awards include: 2024: ARC Industrial Transformation Research Hub for Human-Robot Teaming 2023: Google Inclusion Research Award 2022: NHMRC Ideas Grant for computational brain imaging 2021: UNSW Engineering Research Excellence Award 2020: Scientia Fellowship (UNSW) 2019: ARC Future Fellowship She supervises 24 current PhD/MPhil students and has graduated 15 advisees, including placements at Harvard University and Siemens Healthineers. Her grants include collaborations with Surf Life Saving Australia and industry partnerships for AI-driven solutions.

• Extreme Environmental Physiology
• Human Adaptation to Stressful Environments
• Environmental Health
• +۳ مورد دیگر

Edward Ashworth is a Postdoctoral Research Associate at the Sydney School of Health Sciences, University of Sydney. He is affiliated with the Thermal Ergonomics Laboratory and the Heat and Health Research Incubator. His research focuses on human adaptations to extreme environments, including heat, altitude, hyperbaric conditions, and space-related stressors. Key projects include improving sleep quality in hot environments and enhancing physical work capacity for outdoor workers. Edward's research interests span environmental physiology, with a focus on thermal tolerance, radiation injury mitigation, and the physiological effects of extreme conditions. He has contributed to studies involving nitrogen kinetics tracking using PET imaging, hyperbaric oxygen therapy, and robotic surgery applications. Awards: Young Investigator Award (2023), Art of Science Contest 1st Prize (2024), Australia Space Biology Summit 1st Place (2022), and Sporting Blue (Auckland University of Technology). Associations: The Physiological Society and American Physiological Society. His work integrates clinical trials, statistical research design, and translational approaches to address challenges in environmental health, cardiovascular disease, and healthy ageing. Current projects aim to optimize thermal tolerance strategies for military and occupational settings.

Ivan Coleمشاهده پروفایل

استاد مدعو

• Corrosion Science
• Multiscale Modelling
• Additive Manufacturing
• +۷ مورد دیگر

Prof. Ivan Cole is an Adjunct Professor at RMIT University's School of Engineering, specializing in rapid materials discovery for corrosion protection, nanostructures, and additive manufacturing. His work integrates computational modeling with high-throughput experimentation, focusing on corrosion inhibitors, biocompatible surfaces, and additive manufacturing process optimization. With over 30 years of experience across academia and industry (including leadership roles at CSIRO and Centro-Svilluppo Materiali), he leads the Rapid Discovery & Fabrication Team (RDF) to advance these research areas. Research Interests: Corrosion science, microbially induced corrosion (MIC), additive manufacturing surfaces, nanostructure sensing, multiscale modeling, and green materials discovery. His team addresses challenges in corrosion protection, biomedical implants, and environmental remediation through innovative methodologies. Awards: 2019 Australian Corrosion Medal 2016 CSIRO Lifetime Achievement Award 2013 Best Paper in NACE Corrosion Supervision & Projects: Active in mentoring PhD/Master’s students across corrosion inhibition, additive manufacturing, and nanostructure design. Notable projects include developing quorum sensing inhibitors for biofilm control, in-situ monitoring for metal AM, and eco-friendly corrosion inhibitors. Labs & Collaborations: Leads the Rapid Discovery & Fabrication Team and collaborates with industry partners to translate research into practical solutions for materials durability and sustainability.

Thanh Nho Doمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Surgical Robotics
• Soft Robotics
• +۵ مورد دیگر

Dr. Thanh Nho Do is a Scientia Senior Lecturer at the Graduate School of Biomedical Engineering (GSBmE), UNSW Sydney, and Director of the UNSW Medical Robotics Lab. He holds a PhD in Mechanical Engineering (Surgical Robotics) from Nanyang Technological University (NTU), Singapore, and a B.Eng. in Manufacturing Engineering from Ho Chi Minh City University of Technology, Vietnam. His research focuses on soft robotics, wearable technologies, and biomedical devices, including flexible surgical systems, soft actuators, and haptic interfaces. Education PhD in Mechanical Engineering (Surgical Robotics), NTU Singapore, 2015 B.Eng. in Manufacturing Engineering, Ho Chi Minh City University of Technology, Vietnam Research Interests Soft robotics for medical applications (e.g., NOTES systems, wearable haptics) Functional materials for biomedical devices Cardiovascular engineering and assistive devices Advanced control algorithms for medical robotics Key Contributions His work spans bioprinting, motor-free robotic systems, and soft wearable technologies. Recent studies include self-deploying cardiac compression devices and bioinspired artificial muscles. Awards 2025: CINSW Career Development Fellow 2024: NSW Young Tall Poppy Science Award 2023: Best Poster Awards at EMBC and ICRA Grants & Funding Includes NHMRC Ideas Grant (Lead CI), Cancer Institute NSW Fellowship, and UNSW Scientia Grant. Active projects address cardiovascular interventions and wearable robotics. Labs & Teams Leads the UNSW Medical Robotics Lab, collaborating on devices like soft robotic catheters and textile-driven exosuits.

• Ultrafast Laser Physics
• Optics and Photonics
• Laser-Matter Interaction in Extreme Conditions
• +۷ مورد دیگر

Dr. Ludovic Rapp is a Senior Research Fellow at the Research School of Physics , Australian National University (ANU) , and leads the High-Power Laser group at the Laser Physics Centre (LPC) . His expertise spans ultrafast laser interaction with matter , beam shaping , and laser-induced microexplosions for synthesizing super-dense material phases , including novel silicon allotropes. He is also the Laser Safety Officer for the Research School of Physics.

Mahsa Baktashmotlaghمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Domain Adaptation
• +۳ مورد دیگر

Associate Professor Mahsa Baktashmotlagh is an ARC Future Fellow at the School of Electrical Engineering and Computer Science, University of Queensland. Her research focuses on machine learning techniques applied to visual data analysis, biomedical data (e.g., antibacterial activity prediction), and cybersecurity. She holds a PhD from the University of Queensland (2014) and has contributed to over 50 peer-reviewed publications. Her research interests include domain adaptation, deep learning, and robust generalization across domains. Notable contributions include the development of DI-NIDS (a domain-invariant network intrusion detection system) and advancements in open-set domain adaptation. Her work bridges theoretical machine learning with practical applications in healthcare and computer vision. Education: PhD in Machine Learning, The University of Queensland (2014) Awards: ARC Future Fellowship (202X) Research Themes: Domain Adaptation, Cybersecurity, Biomedical AI Her recent work explores challenges in cross-domain generalization, adversarial machine learning, and scalable 3D object detection. She is actively involved in supervising graduate students and collaborates on interdisciplinary projects involving robotics and medical imaging.

Mehrtash Tafazzoli Harandiمشاهده پروفایل

دانشیار

• Machine Learning
• Deep Learning
• Computer Vision
• +۳ مورد دیگر

Mehrtash Tafazzoli Harandi is an Associate Professor in the Department of Electrical and Computer Systems Engineering at Monash University, part of the Faculty of Engineering. His research focuses on machine learning and computer vision, particularly visual data analysis, with contributions to geometric deep learning, continual learning, and medical imaging. He holds editorial roles at IET Computer Vision , Frontiers in Imaging , and Journal of Imaging . Education & Previous Affiliations: Prior to Monash, he worked at NICTA (Canberra & Queensland Research Labs) and CSIRO-Data61. His Erdős number is 4 via a collaboration path through Richard Hartley. Research Interests: His work spans geometric learning, diffusion models, medical image analysis, and sustainable AI applications. Key areas include unlearning mechanisms in AI, 3D reconstruction compression, and robust MRI reconstruction using contrastive learning. Grants & Projects: He leads projects funded by ARC, US Air Force, and industry collaborations, including 'Can Machines Unlearn?' (ARC, A$790k) and 'Exploiting Geometries of Learning' (ARC, A$420k). His work addresses challenges in lifelong learning, model adaptation, and trustworthy AI from limited data. Awards: Recipient of Best Recognition Paper (IEEE DICTA 2013), NICTA Impact Award (2015), and multiple outstanding reviewer recognitions at top conferences. Teaching: Teaches courses on neural networks, computer vision, and advanced data analysis at Monash University. Supervises PhD students with a focus on mathematical and computational proficiency. Labs/Teams: Collaborates with the Australian Center for Robotic Vision (ACRV) and contributes to interdisciplinary projects at CSIRO-Data61. His research group explores cutting-edge AI applications in healthcare, manufacturing, and environmental sustainability.

• Biomedical Imaging
• Medical Imaging Physics
• Motion Compensation in Imaging
• +۵ مورد دیگر

Associate Professor Andre Kyme is an academic staff member in the School of Biomedical Engineering at The University of Sydney. His research focuses on developing enabling technologies for biomedical imaging, including motion compensation in MRI/PET, robotic platforms for image-guided therapy, and cross-disciplinary applications like plant salt uptake analysis using PET. He collaborates with institutions globally and advises students on projects like lameness detection in horses and AI-based motion correction. Research Interests: Kyme's work spans motion correction in medical imaging modalities, medical robotics integration with imaging systems, and innovative applications of imaging technologies in non-traditional fields. His team emphasizes leveraging advancements in computer vision, machine learning, and instrumentation to improve imaging performance and accessibility. Recent Projects: Current research includes MRI-compatible robotic platforms for therapy applications, AI-driven lameness detection in horses, and pediatric neuroimaging improvements. He leads the BREEZE initiative to enhance MRI accessibility for children with cerebral palsy through eye-gaze communication technology. Publications: His work spans 20+ years with over 50 peer-reviewed publications in journals like Physics in Medicine and Biology and IEEE Transactions. Key areas include PET/SPECT/CT motion correction algorithms, robotic systems for medical imaging, and novel imaging applications in plant science. Teaching: Kyme instructs core biomedical engineering courses including thesis supervision and capstone projects at both undergraduate and postgraduate levels. Labs/Teams: Active in the Brain and Mind Centre and Biomedical Imaging, Visualisation and Information Technologies groups at Sydney. Collaborates with industry partners like TeleMedVet and academic institutions including University of California Davis and Chinese University of Hong Kong.

Michael Stevensمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Advanced Manufacturing
• Digital Manufacturing
• +۶ مورد دیگر

Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.

Maryam Ghahramaniمشاهده پروفایل

مدرس ارشد

• Human Motion Analysis
• Machine Learning
• Rehabilitation Engineering
• +۵ مورد دیگر

Dr. Maryam Ghahramani is a Senior Lecturer in AI & Robotics at the Faculty of Science & Technology, University of Canberra, Australia. She holds a BSc in Electrical Engineering from Shiraz University, Iran, and a PhD in Biometric Gait Analysis from the University of Wollongong, Australia. Biomedical Engineering Researcher Machine Learning Specialist Human Motion Analysis Expert Her research focuses on applying machine learning to human motion analysis for rehabilitation purposes, particularly in three key areas: Parkinson's Disease: Using fNIRS and machine learning for disease detection and motor function assessment Fall Prevention: Analyzing postural sway and risk of falls in older adults Spatial Disorientation: Studying balance in hypoxic aviation environments Recent publications demonstrate her work at the intersection of biomedical engineering, machine learning, and clinical rehabilitation. Current projects include: Young Onset Dementia Detection with 12-week Home-Based Exercise Programs Mild Hypoxia Analysis for Aviation Safety Balancing Mat Performance Evaluation

Clinton Fookesمشاهده پروفایل

استاد

• Computer Vision
• Artificial Intelligence
• Human Behavior Analysis
• +۷ مورد دیگر

Professor Clinton Fookes is a faculty member at the Queensland University of Technology (QUT) within the School of Electrical Engineering & Robotics . His research focuses on leveraging computer vision and artificial intelligence to develop automated systems that understand, anticipate, and interact with human behaviors, with applications in medical diagnostics, autonomous vehicles, defense, and industrial efficiency . Research areas include AI adaptability, multimodal biosignal analysis, and human-machine interaction Collaborates with CSIRO Data61, Defence Science and Technology Group, Orica, Airbus, and Sentient Vision Systems Develops systems for human action detection, infrastructure monitoring, and stress response prediction His work addresses critical challenges in AI deployment, such as environmental adaptability and reducing diagnostic errors in medical and autonomous systems. Recent publications highlight trends in self-supervised learning, zero-shot knowledge transfer, multimodal integration , and 3D reconstruction for healthcare , while exploring ethical AI use in sectors like mining and defense . Professor Fookes emphasizes interdisciplinary collaboration, bridging engineering, medicine, and social sciences to advance AI systems capable of real-world impact. His research agenda includes improving AI memory capabilities and explainability for safer, more reliable automation.

Glen Tianمشاهده پروفایل

استاد

• Big Data Computing
• Cloud Computing
• Computer Networks
• +۱۱ مورد دیگر

Professor Glen Tian is a Professor at the School of Computer Science , Queensland University of Technology . He holds two PhDs: one in computer and software engineering from the University of Sydney (2009) and another in industrial automation from Zhejiang University (1993) . His academic career spans institutions including Hong Kong University of Science and Technology, Curtin University, and the University of Maryland at College Park. Editor-in-Chief of the Handbook of Real-Time Computing (Springer) Associate Editor for Information Sciences (Elsevier) and Asia-Pacific Journal of Chemical Engineering (Wiley) His research focuses on big data computing , cloud computing , computer networks , smart grid communication and control , networked control systems , and cyber-physical system security . Applications include power systems , medical big data , vehicular networks , and transport systems . Recent publications highlight advancements in smart grid communications , distributed optimization , secure multi-agent systems , and medical imaging analysis . He has led QUT's Big Data Lab and served as Leader of QUT's Networks and Communications Discipline . Scientific achievements include Over 20 research grants totaling >$6M 6 Australian Research Council (ARC) grants 1 MRFF-TTRA grant ($745,623) 1 ATN-DAAD Australia-Germany Collaborative Grant 1 DEST International Science Linkage grant He supervises PhD students in big data bioinformatics , smart grid optimization , and cyber-physical security , while mentoring 30+ postdocs and research fellows. Current projects include mitigating cyberattacks on power systems and developing AI-based atheroma diagnostic tools .