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.

Jiyuan Tuمشاهده پروفایل

استاد

• Computational Fluid Dynamics (CFD)
• Multiphase Flows
• Thermal Sciences
• +۴ مورد دیگر

Professor Jiyuan Tu is a Professor in the Department of Mechanical and Automotive Engineering at RMIT University's School of Engineering. He specializes in computational fluid dynamics (CFD), multiphase flows, and their applications in renewable/nuclear energy, biomedical engineering, and built environment systems. His research has led to over 500 peer-reviewed articles, 9 books, and $10M+ in ARC grants. He has supervised over 50 postgraduate students and received prestigious awards such as the RMIT Research Excellence Award (2012) and Fulbright Senior Scholar Award (2008). Research interests include CFD modelling of bioaerosol transport, drug delivery systems, and thermal energy storage. He pioneered numerical models for multiphase flows, contributing to software implementations in industries. Notable works include books on CFD and multiphase flow analysis, and leadership in international conferences like COBEE 2018. He holds honorary professorships at Tsinghua University and is Editor-in-Chief of the Experimental and Computational of Multiphase Flow journal. Industry experience includes roles at ANSTO (1996-2001). Awards span fellowships from JSPS, KOSEF, and Fulbright programs. Grants include ARC Discovery, Linkage, and LIEF projects. His work ranks him among the world’s top researchers in pebble bed reactors and airborne infection studies (SciVal 2016-2025).

• Natural Language Processing
• Knowledge Graphs
• Machine Learning
• +۵ مورد دیگر

Dr. Sirui Li is a Lecturer at Murdoch University's School of Information Technology within the College of Science, Technology, Engineering and Mathematics. Her research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Learning, Knowledge Graphs, Data Analysis, Temporal Data, and Multi-modal Models, with applications in medicine, agriculture, and mining. She collaborates with industry partners like BHP and has published in journals such as Food Chemistry and Knowledge and Information Systems , as well as conferences like ICSME and IJCNN. Education: Bachelor of Advanced Computing (Honours) in Computer Science at Australian National University Master of Computing (Specialising in AI) at ANU Ph.D. in Information Technology (AI) at Murdoch University Research interests include interdisciplinary applications of AI, such as clinical coding privacy solutions, disease spread modeling, and drug repurposing for pandemics. Her work emphasizes practical industry integration, demonstrated through awards like the 2024 EMNLP Best Demo Award and the 2023 Iron Ore Circuit Hackathon innovation prize. Professional roles include IEEE Western Australia Section committee membership, conference chair positions, and peer review for top journals. She actively mentors students pursuing Honours, Master's, or PhD projects in her areas of expertise.

• Operations Research
• Management Science
• Optimization Algorithms
• +۶ مورد دیگر

Dr. Dmytro Matsypura is an Associate Professor in the Discipline of Business Analytics at the University of Sydney Business School. He holds a BA (Hons) from Kyiv Polytechnic Institute (KPI), an MS (Hons) from KPI, and a PhD from the University of Massachusetts Amherst. His research focuses on optimization methodologies, network science, and their applications in finance, transportation, ecology, and graph theory. He is a recipient of multiple teaching awards, including the Wayne Lonergan Outstanding Teaching Award (Early Career) in 2010. Education: PhD in Management Science, University of Massachusetts Amherst (2006) MS (Hons) in Information Systems, Kyiv Polytechnic Institute (2000) BA (Hons) in Business Administration, Kyiv Polytechnic Institute (1998) Research Interests: Dr. Matsypura’s work spans operations research and management science, with a focus on mathematical optimization and network science. His methodological contributions include developing efficient optimization algorithms, while his applied research addresses real-world challenges in finance, engineering, and ecology. Notable applications include wildfire fuel management, portfolio margining, and credit card fraud detection via graph-based models. Awards and Recognition: Teaching Excellence Award (2008, 2013, 2018) Wayne Lonergan Outstanding Teaching Award (Early Career) (2010) Grants and Projects: Current projects include Bushfire Analytics: Optimization of Fuel Reduction (2023, ARC Discovery Project). His research frequently integrates interdisciplinary collaborations, such as applying graph theory to biomedical problems and cybersecurity. Labs/Teams: Active in the Sydney Environment Institute, contributing to projects at the intersection of analytics and sustainability. Collaborates with industry on fraud detection and supply chain optimization.

• 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.

• Medical Microwave Imaging
• Microwave Engineering
• Millimeter-wave Engineering
• +۳ مورد دیگر

Professor Amin Abbosh is a faculty member at the School of Electrical Engineering and Computer Science, University of Queensland. His research focuses on Medical Microwave Imaging and Millimeter-wave Engineering, with contributions to advanced imaging systems, antenna design, and communication technologies. He leads projects in electromagnetic medical sensing, including portable brain scanners and wearable diagnostic systems. His work integrates applied electromagnetics with AI-driven algorithms, addressing challenges in stroke detection, liver health monitoring, and deep vein thrombosis diagnosis. With over 16 patents and collaborations across biomedical and engineering domains, his research bridges clinical needs with cutting-edge electromagnetic techniques. Key projects include the development of low-cost healthcare monitoring systems and reconfigurable antennas for satellite communications. Research interests span medical imaging systems, antenna array design, and signal processing for healthcare applications. His team innovates in areas like phased arrays, dielectric property analysis, and non-invasive diagnostics. Recent advancements include synthetic microwave focusing techniques and self-supervised deep learning models for clutter removal in imaging. Publications highlight contributions in IEEE journals and conferences, emphasizing clinical applications and device prototyping. Collaborations with institutions like the University of Queensland’s medical faculty and industry partners ensure practical implementation of his research.

Nhiem Tranمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Nanotechnology
• Nanomedicine
• +۱۲ مورد دیگر

Dr. Nhiem Tran is a Senior Lecturer in the Department of Applied Chemistry and Environmental Science at RMIT University's School of Science, part of the STEM College. He joined RMIT in 2015 as a Vice Chancellor's Research Fellow after completing his PhD in Physics at Brown University (USA, 2012) and postdoctoral research at Rhode Island Hospital (USA), CSIRO, and the Australian Synchrotron. His research focuses on developing biomaterials for drug delivery, gene therapy, and medical implants, particularly lipid nanoparticles and 3D-printed metallic implants. He leads the Biomaterial Interfaces group, investigating self-assembled lipid nanoparticles for cancer and autoimmune disease treatments. His work has resulted in over 65 high-impact publications and numerous awards, including the RMIT Vice Chancellor's Research Fellowship and the Stein/Bellet Foundation Fellowship. Tran's funding comes from grants such as the ARC Discovery Project, mRNA Victoria, and the CASS Foundation. His research interests span nanomedicine, biomedical engineering, and materials science, with a focus on applications in drug delivery, bacterial infection control, and orthopaedic implants. Education: PhD in Physics (Brown University, 2012) Key Projects: 3D-printed diamond-titanium implants, lipid nanoparticle drug carriers, and antimicrobial coatings. He actively supervises postgraduate research in areas like nanomaterials for drug delivery and biomedical applications.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +۱۲ مورد دیگر

Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.

• Audio Signal Processing
• Spatial Audio Technology
• Medical Engineering
• +۳ مورد دیگر

Craig Jin is an Associate Professor at the University of Sydney, leading the CARlab (Computing and Audio Research Laboratory) and Spatial Audio Research initiatives within the School of Electrical and Computer Engineering. He holds a BS from Stanford University, an MS from Caltech, and a PhD from the University of Sydney. His work focuses on immersive audio technologies, biomedical signal processing, and assistive technologies for sensory augmentation. Research interests include spatial audio reproduction, binaural processing, acoustic sensing for accessibility, and machine learning applications in signal processing. Key contributions span HRTF interpolation, noise reduction algorithms, and acoustic touch systems for the visually impaired. Recent projects include real-time MRI analysis of vocal tract dynamics and sparse recovery techniques for sound field reconstruction. His publications span over 150 peer-reviewed articles in journals like IEEE Transactions on Audio, Speech, and Language Processing, and conferences such as ICASSP. He advises four current PhD/Master’s students on projects like predictive gesture tracking, voice disorder classification, and magnetic resonance imaging techniques.

• Respiratory Drug Delivery
• Pulmonary Drug Delivery
• Inhalation Aerosols
• +۵ مورد دیگر

Professor Hak-Kim Chan of the Sydney Pharmacy School at the University of Sydney is a world-renowned expert in respiratory drug delivery, particularly pulmonary aerosols and inhalation therapies. With over 480 publications and 17,580+ Google Scholar citations, he has pioneered advancements in powder formulation , in silico modeling , and clinical applications of inhalation technologies. His work includes the development of FDA-approved diagnostics like Aridol™ (inhaled mannitol for asthma) and Bronchitol™ (for cystic fibrosis), and groundbreaking research on inhaled bacteriophage therapy to combat antibiotic-resistant respiratory infections. Education: BPharm (University Medal, 1983), PhD (1988), DSc (2009) from University of Sydney Professional Experience: Postdoc at University of Minnesota (1988–89), Scientist at Genentech Inc. (1992–95) Leadership: Executive Editor of Advanced Drug Delivery Reviews , Fellow of AAPS and RACI His research spans in vitro production methods, computational modeling of inhaler design, and in vivo imaging of aerosol deposition. Current projects focus on nanomedicine , phage therapy , and combating superbugs via inhalation routes. He has secured significant recognition for his work, including NHMRC case studies highlighting public health impacts. Professor Chan has supervised numerous researchers, including PhD student Grace YAU studying pulmonary probiotic delivery . His team's 10 patents (7 as first inventor) reflect practical innovations in dry powder inhalers , antimicrobial formulations , and drug stabilization technologies.

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.

• Machine Learning
• Computer Vision
• Medical Image Analysis
• +۷ مورد دیگر

Professor Arcot Sowmya is a distinguished academic at the University of New South Wales, serving as Professor in the School of Computer Science and Engineering. With a strong background in both computer science and mathematics, she has established herself as a leading researcher in machine learning and computer vision applications, particularly in medical imaging and diagnostics. Dr. Sowmya earned her PhD in Computer Science from the Indian Institute of Technology, Bombay, along with an MTech in Computer Science, MSc in Mathematics, and BSc in Mathematics from the same institution. Her academic journey has positioned her at the intersection of theoretical computer science and practical medical applications. Her research interests span multiple domains with a primary focus on Machine Learning for Computer Vision . She has made significant contributions to learning object models, feature extraction, segmentation, and recognition techniques. Her work extends into medical image analysis, computer-aided diagnostics, high-resolution remote sensing, and biomedical informatics. More recently, she has applied similar techniques to social sciences domains, developing improved forecasting models for genocide and politicide. Her earlier work also includes contributions to real-time, concurrent, and embedded systems. Analyzing her recent publications reveals a strong trend toward medical applications of computer vision and deep learning. Her work spans from OCT-based glaucoma diagnosis to tumor segmentation, lung disease detection, and breast cancer prognosis. She has successfully bridged computer science with clinical medicine, developing practical tools for disease diagnosis and prediction that incorporate explainable AI approaches. Professor Sowmya's collaborative approach is evident in her extensive publication record across multiple journals and conferences. She has worked with researchers from diverse fields including ophthalmology, oncology, neurology, and public health, demonstrating the interdisciplinary nature of her research. Her laboratory work focuses on developing robust deep learning architectures for medical image analysis, with particular attention to segmentation networks, transformer models, and multimodal data fusion techniques. Her team has developed specialized networks for lung segmentation, tumor detection, and disease classification that address specific challenges in medical imaging.

• Fluid Dynamics
• Renewable Energy Technologies
• Mechanical Engineering Education
• +۳ مورد دیگر

Buyung Kosasih is a Professor in the School of Mechanical, Materials, Mechatronic and Biomedical Engineering at the University of Wollongong. He has held this position since 2000 and focuses on teaching and research in mechanical engineering, including Machine Dynamics, Finite Element Methods, and Renewable Energy Technology. His research spans fluid dynamics in industrial processes, renewable energy systems, and aqueous lubrication. Key projects include 3D-printed surfboard fin optimization and steel coating dynamics. Research interests emphasize experimental and computational fluid dynamics, particularly in renewable energy turbines and tribological systems. Notable awards include the 2013 Outstanding Contribution to Teaching and Learning Award. He has supervised numerous students and led over 20 funded projects, including ARC grants for steel innovation and renewable energy. Collaborative work includes the Steel Research Hub and HVAC/cool roof efficiency studies.

Rajendra Acharyaمشاهده پروفایل

استاد

• Artificial Intelligence
• Healthcare
• Machine Learning
• +۵ مورد دیگر

Rajendra Acharya is a Professor (Artificial Intelligence in Health) at the University of Southern Queensland's School of Mathematics, Physics and Computing. He holds qualifications including BEng, MTech, two PhDs, and a DSc. His research focuses on AI applications in healthcare, pattern recognition, and medical diagnostics, with notable contributions to EEG analysis, deep learning, and disease detection. Awards include multiple Research.com Leader Awards in Computer Science for Australia and Singapore (2022–2025). His work spans over 650 publications, with high-impact studies on automated disease diagnosis via AI, including COVID-19 detection using X-rays and EEG-based seizure detection. His research interests integrate machine learning, signal processing, and healthcare technologies. He collaborates internationally and advises on AI-driven health solutions. No student list provided; however, his extensive supervision is implied through his research output.