جستجوی استاد راهنمای دانشگاهی

Glen Lichtwarkمشاهده پروفایل

استاد

• Biomechanics
• Muscle-Tendon Mechanics
• Human Movement Science
• +۷ مورد دیگر

Glen Lichtwark serves as an Honorary Professor and Director of HDR Students at the School of Human Movement and Nutrition Sciences at the University of Queensland. He is also an Affiliate of the Centre for Sensorimotor Performance. With over 150 journal articles to his name, Professor Lichtwark is a leading researcher in biomechanics and human movement science. His research focuses on muscle-tendon mechanics, neuromuscular function, and human movement analysis. Using advanced techniques including ultrasound imaging, motion capture, and computational modeling, he investigates how muscles and tendons work during various activities such as walking, running, jumping, and cycling. His work has significant implications for sports performance, rehabilitation, and assistive device design. Analysis of his recent publications reveals a strong focus on muscle energetics, tendon mechanics, and the application of exoskeleton technology. His research spans from fundamental muscle physiology to practical applications in sports and rehabilitation. He frequently collaborates with researchers across multiple institutions and disciplines, demonstrating the interdisciplinary nature of his work. As Director of HDR Students, Professor Lichtwark plays a key role in supervising and mentoring postgraduate research students. His leadership in the Centre for Sensorimotor Performance contributes to advancing knowledge in human movement science and its applications.

• Big Data
• Social Network Mining
• Stream Processing
• +۱۲ مورد دیگر

Dr. Thanh Tam Nguyen is a Lecturer at the School of Information and Communication Technology, Griffith University, Gold Coast Campus. He holds a PhD in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, and is a Fellow of the Higher Education Academy (FHEA). His academic and research profile is centered on advancing Big Data and Smart technologies through efficient and trustworthy AI systems. His educational background includes a Doctor of Science and a Master of Science, both from EPFL. He is actively involved in high-impact research and has published over 65 papers in top-tier venues such as SIGMOD, VLDB, SIGIR, ICDE, IJCAI, VLDBJ, TKDE, and Pattern Recognition, with over 35 in CORE A* journals and conferences. His work has attracted more than 4,200 citations (h-index 35+). Dr. Nguyen's research focuses on Big Data Analytics, Social Network Mining, Stream Processing, Privacy-Preserving Machine Learning, Recommender Systems, Explainable AI, and Graph Neural Networks . He aims to bridge human insights with data models to ensure transparency and trust in data-driven decisions. His recent work explores misinformation management, machine unlearning, and federated learning, with applications in social networks, healthcare, and sustainable agriculture. The 15 most recent publications reflect a strong trend in privacy-preserving AI, explainability, federated learning, and graph-based modeling . Key themes include machine unlearning, adversarial robustness in recommender systems, heterogeneous graph representations, and trustworthy AI deployment. His work is frequently published in ACM and IEEE venues, indicating sustained excellence in computer science and AI research. Fellow of the Higher Education Academy (FHEA) Dr. Nguyen has secured over $1 million in research funding from government (DFAT, A4I, AKF), industry (CSIRO, Ubitech, Johnson & Johnson), and international bodies (NAFOSTED, ETRI, KARI). He serves as a guest editor for IEEE Journal of Biomedical and Health Informatics, area chair for ACL and EMNLP, and reviewer for top journals like TKDE, JVLDB, and CSUR. He supervises multiple PhD students and collaborates with leading international researchers such as Prof. Karl Aberer (EPFL), Prof. Björn Schuller (Imperial College), and Prof. Hongzhi Yin (UQ). He is a key contributor to the Responsible Big Data Lab at Griffith University and leads projects on misinformation management, AI safety, and sustainable agriculture through AI-powered traceability. His impact extends to policy and industry, particularly in cybersecurity and trustworthy AI adoption.

• Orthopaedics
• Tissue Engineering
• Osteoarthritis
• +۴ مورد دیگر

Ross Crawford is a Professor of Orthopaedic Research at Queensland University of Technology and a Visiting Medical Officer at Prince Charles Hospital and Holy Spirit Northside. His work focuses on orthopaedic research , particularly in osteoarthritis , bone regeneration , and clinical orthopaedics . He has secured significant grants from organizations like Stryker , ARC , and NHMRC . Rhodes Scholarship Stryker Fellowship Research Trends : His recent publications highlight advancements in hypoxia-mimicking scaffolds , stem cell therapies , and biomechanical innovations for joint repair. Collaborations span biomedical engineering , clinical sciences , and materials research . Scientific Awards : Neville Davis Prize (Finalist) - 1995 Society of St. Andrews Travelling Scholarship - 1995 Allan Frederick Dwyer Prize - 1994 Supervision : He supervises research on topics like robotic bone tracking and antimicrobial biomaterials . His lab collaborates with institutions globally, including Oxford University and Prince Charles Hospital .

Dana Rezazadeganمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Deep Learning
• Computer Vision
• +۷ مورد دیگر

Dana Rezazadegan is a Senior Lecturer in Computer Science and Software Engineering at Swinburne University of Technology, affiliated with the School of Science, Computing and Emerging Technologies. Her work bridges artificial intelligence, computer vision, and healthcare applications, with a strong focus on human-robot collaboration and digital health solutions. Research Interests: Her primary research areas include deep learning, computer vision, LLMs, health informatics, continual learning, and AI for inclusive education. She investigates how intelligent systems can support human activities in healthcare and assistive robotics. The recent publications highlight a consistent focus on applying AI to healthcare challenges—ranging from clinical NLP and patient decision support to automated severity assessment in diseases like COVID-19. She also contributes significantly to foundational AI methods, including uncertainty quantification, speech summarization, and real-time 3D pose estimation for embedded and mobile platforms. Superstar of STEM, Science and Technology Australia, 2021 Teaching Award, Swinburne University of Technology, 2020 Early Career Marie Curie Fellowship, 2014 Top 20 in Iran's Mathematics Olympiad, 2000 Dana actively supervises PhD students on topics such as continual learning, AI tutoring, electricity price forecasting, and 3D pose estimation. She has secured multiple research grants, including projects on inclusive AI for dyslexic learners and AI for energy forecasting. Her collaborative work spans institutions like Macquarie University and CSIRO, and she engages in public outreach through media contributions on AI ethics and privacy. She leads and contributes to interdisciplinary teams focused on AI in healthcare and education, often involving co-design with clinicians and end-users. Her labs and research groups emphasize real-world applicability, ethical considerations, and human-centered AI design.

• Robotics
• Space Robotics
• Collaborative Robotics
• +۱۰ مورد دیگر

Dr. Michelle Dunn is a Senior Lecturer in the School of Engineering at Swinburne University of Technology, where she leads research in robotics and signal processing. She serves as the academic lead for the Swinburne Rover Team and the lead of Space Robotics within the Swinburne Space Technology and Industry Institute. Her interdisciplinary work bridges engineering, space technology, industrial monitoring, and cultural heritage conservation. School: School of Engineering University: Swinburne University of Technology Academic Rank: Senior Lecturer Dr. Dunn's research is centered on robotics and signal processing, with key interests in Space Robotics, Collaborative Robotics, Lunar Dust Mitigation, and Assistive Technologies. She applies signal analysis techniques to diverse fields including steelmaking, where she uses acoustic and vibration signals to monitor processes, and art conservation, where she integrates spectroscopy and imaging to analyze paintings. Her work combines experimental modeling, sensor development, and data analytics to solve real-world engineering challenges. Her recent publications span robotics in agriculture, lunar dust mitigation, additive manufacturing defect detection, and acoustic monitoring in steelmaking. These works reflect a strong trend toward applying robotics and advanced signal processing to practical, interdisciplinary problems. She frequently collaborates with industry and government agencies, securing funding from the ARC and Department of Industry, Science and Resources. Scientific awards include: Vice-Chancellor's Teaching Excellence (Higher Education) Award (2018) Vice-Chancellor's Teaching Excellence (Higher Education) Award (2013) Dr. Dunn actively supervises PhD and Master’s students across diverse projects, including heat flow monitoring, assistive mobility devices, UAV-based parking systems, and EEG-based voice detection. She has been principal investigator on multiple ARC-funded grants, such as the ARC Training Centre for Collaborative Robotics in Advanced Manufacturing and projects focused on sound and vibration monitoring in steelmaking. Her research contracts include development of portable parasite detection systems and cuffless blood pressure monitoring. She leads and contributes to laboratory-based research in the Swinburne Space Technology and Industry Institute, focusing on space robotics and lunar dust mitigation. Her team also operates experimental setups for acoustic and vibration monitoring in industrial models, supporting innovation in steelmaking and manufacturing.

Qing-Long Hanمشاهده پروفایل

استاد

• Control Theory
• Control Engineering
• Networked Control Systems
• +۱۲ مورد دیگر

Professor Qing-Long Han is Pro Vice-Chancellor (Research Quality) and Distinguished Professor at Swinburne University of Technology, Australia. He has previously held academic and leadership roles at Griffith University and Central Queensland University. He is a globally recognized expert in control theory and engineering, particularly in networked and time-delay systems. Pro Vice-Chancellor (Research Quality), Swinburne University of Technology Distinguished Professor, Swinburne University of Technology Editor-in-Chief, IEEE/CAA Journal of Automatica Sinica President-Elect, Asian Control Association His research interests span Control Engineering, Networked Control Systems, Multi-Agent Systems, Smart Grids, Unmanned Surface Vehicles, Neural Networks, and Secure Control . He is deeply involved in resilient and secure control under cyber threats, optimization, and industrial metaverse applications. His work integrates control theory with AI, IoT, and industrial automation. The recent publications highlight a strong trend toward secure, resilient, and distributed control in cyber-physical systems, particularly under attacks (replay, falsification), communication constraints, and delays. There is a clear focus on real-world applications in autonomous vehicles, trains, drilling systems, and chiller networks, using advanced methods such as reinforcement learning, event-triggering, and neurodynamic optimization. Award highlights include: IEEE Dr.-Ing. Eugene Mittelmann Achievement Award (2024) Norbert Wiener Award (2021) M. A. Sargent Medal (2021) IEEE Andrew P. Sage Best Paper Award (2019, 2020, 2022) Highly Cited Researcher (Clarivate, multiple years) Professor Han actively supervises PhD students in cutting-edge control topics and leads major research grants from the Australian Research Council and National Natural Science Foundation of China. He is a Fellow of IEEE, IFAC, Engineers Australia (Honorary), and the Chinese Association of Automation. He also contributes to editorial leadership in top journals and professional societies. He is associated with research teams and editorial boards in control systems, automation, and intelligent systems, fostering international collaboration and innovation in engineering.

• Machine Learning
• Computer Vision
• Hyperspectral Imaging
• +۵ مورد دیگر

Associate Professor Ivan Lee is affiliated with the University of South Australia's STEM division at Mawson Lakes Campus. He actively supervises research degrees and contributes to interdisciplinary research intersecting computer science, food safety, and smart materials. Research Interests: Specializes in machine learning applications for hyperspectral imaging in food contamination detection Develops novel graph learning algorithms for real-time driver fatigue monitoring Investigates eco-friendly synthesis techniques for graphene-based nanomaterials Advances intelligent sensing systems for structural health monitoring Publications Trends: Recent work focuses on spatio-temporal graph modeling, multi-objective optimization algorithms, and applying deep learning to food safety challenges like aflatoxin detection. His research spans computer vision, IoT systems, and sustainable materials. Supervision: Currently serves as a research degree supervisor at University of South Australia. No scientific awards mentioned in available records.

Torsten Merzمشاهده پروفایل

پژوهشگر

• Uncrewed Aircraft Robotics
• Dependable Autonomous Systems
• Underwater Vehicles
• +۷ مورد دیگر

Dr. Torsten Merz is a Principal Research Engineer at CSIRO's Autonomous Systems Laboratory , focusing on technologies for dependable autonomous mobile robots in environmental applications. He holds a Dr.-Ing. (Doctor of Engineering) and a Diplom-Informatiker (Master's equivalent) from German universities. Education : Doctoral degree in Engineering (2000), Department of Computer Science, University of Erlangen-Nürnberg (Germany) Diplom-Informatiker in Applied Computer Science in the Natural Sciences (1995), University of Bielefeld (Germany) Research Interests : Enabling technologies for autonomous helicopters , underwater vehicles , and uncrewed surface vehicles with a focus on dependable systems and real-time control . Integration of computer vision , modelling languages , and evolutionary robotics into environmental monitoring and infrastructure inspection. Article Trends : Recent work emphasizes edge-AI for reef surveys, underwater imaging for habitat mapping, and multi-objective motion planning for dynamic environments. Historical contributions include control frameworks for autonomous robots, obstacle avoidance in rural areas, and autonomous landing systems for UAVs. Labs & Teams : Lead developer at CSIRO's Autonomous Systems Laboratory , where he pioneered autonomous flight technologies for helicopters and expanded into underwater/surface robotics . Previously led the Perception and Control Group at Linköping University, developing avionics for autonomous helicopters.

• Remote Sensing
• Image Processing
• Multimedia Security
• +۷ مورد دیگر

Dr. Mohammad Awrangjeb is a Senior Lecturer at the School of Information and Communication Technology , Griffith University, with over 15 years of experience in academia and research. He holds a PhD from Monash University (2008) and has held academic positions at Federation University Australia (2014-15), Monash University (2012-13), and the University of Melbourne (2008-12). Education: PhD in Computer Science, Monash University (2008) MSc in Computer Science, National University of Singapore (2004) BSc (Engineering) in Computer Science, Bangladesh University of Engineering and Technology (2001) His research focuses on remote sensing data processing , including automated 3D city modeling, power line corridor monitoring, solar potential estimation on buildings, forest biomass estimation, hyperspectral image processing, multimedia security, EEG signal processing, and medical image analysis. He has co-authored over 80 publications and secured $435,000 in research funding, including an Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA, 2012-15) and grants from CRCSI and Griffith University. His work has been applied in environmental monitoring, energy planning, and infrastructure safety. Scientific Awards: Discovery Early Career Researcher Award (DECRA Fellow) (2012-2015) The Len Curtis Award (2017) Dean’s Highly Commended Certificate, Griffith Sciences (2020, 2019) He actively supervises PhD students in areas like hyperspectral imaging , forest biomass estimation , intrusion detection , and medical image segmentation . He serves on editorial boards and committees, including IEEE and the Remote Sensing and Photogrammetry Society, and has contributed to software development at CRCSI.

Rich Littleمشاهده پروفایل

پژوهشگر

• Marine Environmental Science
• Fisheries Management
• Ecological Modeling
• +۵ مورد دیگر

Dr. Rich Little is a Senior Research Scientist at CSIRO Environment in Hobart, Australia. His work focuses on integrating biophysical models with socioeconomic analyses to address challenges in marine resource management, fisheries economics, and climate adaptation. He has developed decision-support tools like ELFSim for coral reef fisheries and leads the South East Australian Marine Ecosystem Survey (SEA-MES). Additionally, he contributes to Marine Visual Technologies, which employs AI for sustainable fisheries monitoring. Certificate in Executive Management and Development (2018), Australian Graduate School of Management PhD (2000), University of Alberta MSc (1995), University of Western Ontario BSc (1989), University of Western Ontario Diploma (1993), University of Western Ontario Rich Little’s research spans marine population dynamics, tradeable permit markets, Bayesian Belief Networks for fishing behavior, and the economics of marine protected areas. His recent work explores parametric insurance for climate adaptation, deep learning applications in electronic monitoring, and resilience-building in mixed fisheries. Publications highlight interdisciplinary approaches to reconciling ecological, economic, and social objectives. His scientific accolades include the CSIRO Julius Career Development Award (2008-2011), the Early Career Research Excellence Award (2005), and an Honorary Associate position at the University of Tasmania (2007-2010). He has also contributed to transdisciplinary initiatives like the Theo Murphy Frontiers of Science meeting.

Jamie Craigمشاهده پروفایل

استاد

• Ophthalmology
• Glaucoma
• Genetics
• +۷ مورد دیگر

Professor Jamie Craig is a leading academic and clinician-scientist at Flinders University , serving as the Chair and Academic Head of the Department of Ophthalmology and Director of the Flinders Centre for Ophthalmology, Eye and Vision Research . A Practising Consultant Ophthalmologist , he bridges laboratory research and clinical practice, particularly in glaucoma and other eye diseases. Bachelor of Medical Science (Hons), University of Adelaide (1991) PhD, University of Oxford (1995) Research Interests : His work focuses on genetic susceptibility to glaucoma through the Australian and New Zealand Registry of Advanced Glaucoma , enabling genome-wide association studies to identify causal genes. He explores animal models for cataract and corneal dystrophies and investigates gene-environment interactions in Pseudoexfoliation Syndrome . Current projects aim to translate genetic risk profiles for glaucoma and diabetic retinopathy into clinical tools. Scientific Awards include multiple honors such as the NHMRC Research Excellence Award (2018) , South Australian Scientist of the Year (2024) , and numerous early-career prizes from the University of Adelaide. He was awarded a Clinician Special Purpose Fund PhD Scholarship (2025) and holds an NHMRC Senior Practitioner-Fellow status. Research Trends show a strong focus on genetic studies (67% of recent work) using genome-wide association and polygenic risk scores , alongside machine learning applications (22%) for glaucoma screening and epigenetic research (11%) in congenital eye diseases.

Kok Chiang Liangمشاهده پروفایل

مدرس

• ASIC Design
• Power Management Unit
• Robotics
• +۲ مورد دیگر

Dr. Kok Chiang Liang is a Lecturer and Program Coordinator for Electrical and Electronic Engineering at the School of Engineering , part of the College of Engineering, Science and Environment at Newcastle Australia Institute of Higher Education (NAIHE). He previously worked at DSO National Laboratories and SUSS, receiving multiple awards including the Design Innovation Award and Teaching Excellence Gold Awards . He holds a PhD and BEng (Honours) from Nanyang Technological University (NTU). Education PhD, Electrical & Electronic Engineering, NTU (2014) BEng (Honours), Electrical & Electronic Engineering, NTU As a researcher, Dr. Kok focuses on ASIC design for power management , robotics , artificial intelligence , and energy harvesting applications . His work bridges IoT and sustainable engineering, with over 50 publications in Q1/Q2 journals and conferences. Notably, he has pioneered innovations in medical device design, urban sustainability, and educational technology. His recent articles highlight trends in sustainable electronics and AI integration across domains. He has received significant recognition, including two Best Paper Awards and substantial research seed funding (over S$260,000). Dr. Kok also contributes to community service as a District Councillor and Grassroots Volunteer in Singapore, and serves on the STEM Industrial Advisory Board and IEEE committees . Scientific Awards Design Innovation Award (Individual), DSO National Laboratories (2018) Teaching Excellence Gold Award, SUSS (2020, 2025) Best Paper Award, 3rd ICESA (2021) Best Paper Award, 6th ICPEE (2024) Dr. Kok’s leadership extends to research grants as Principal Investigator and Co-PI, and to policy advisory roles for Singapore’s Ministry of Education. His interdisciplinary approach combines technical innovation with societal impact, reflected in his roles at People’s Action Party Meet-the-People Sessions and Ang Mo Kio Town Council .

Timothy Donohueمشاهده پروفایل

مدرس

• Bulk Materials Handling
• Discrete Element Modelling (DEM)
• Computational Fluid Dynamics (CFD)
• +۷ مورد دیگر

Dr. Timothy Donohue serves as Conjoint Lecturer in the Faculty of Engineering and Built Environment at the University of Newcastle, Australia, while also holding the position of General Manager at TUNRA Bulk Solids (The University of Newcastle Research Associates Ltd). With a Doctor of Philosophy and Bachelor of Engineering (Mechanical) (Hons) from the University of Newcastle, he has built a career centered on numerical modeling for industrial problem solving, particularly in bulk materials handling. Dr. Donohue's research expertise focuses on transfer chutes, passive dust control techniques, and calibration of parameters for Discrete Element Modeling (DEM). His work combines Computational Fluid Dynamics (CFD) with DEM to reduce dust generation in material handling systems through passive means. His foundational research on permeability of packed beds and development of packing algorithms for simulating packed beds of spheres and fibrous materials has provided a strong basis for his current work in DEM and CFD applications. His research interests encompass bulk materials handling, discrete element modeling, computational fluid dynamics, dust control, transfer chute design, bin and hopper design, and bulk material stress analysis. His publication record demonstrates consistent contributions to the field of bulk solids handling, with recent work focusing on silo quaking, gate load analysis, particle degradation effects, and advanced DEM calibration techniques. His research bridges theoretical modeling with practical industrial applications, particularly in the coal and iron ore industries. Dr. Donohue has received numerous awards recognizing his contributions, including the First Prize Winner at the 2016 Unearthed Hackathon Hunter Valley, the A.W. Roberts Award for Outstanding Young Engineer in 2015, and several other prestigious honors throughout his career. With over 170 industrial projects completed since joining TUNRA Bulk Solids in 2007, Dr. Donohue has extensive experience in both conceptual design and troubleshooting existing systems. He has supervised PhD, Master's, and Final Year Project students at the University of Newcastle and has been involved in lecturing and tutoring undergraduate courses. Additionally, he has delivered approximately 20 industry short courses since 2009, ranging from 1 to 5 days in length.

• Neurofibromatosis Type 1
• Rare Genetic Diseases
• 2D Facial Recognition Technology
• +۴ مورد دیگر

Professor Tracy Dudding-Byth AM is a Consultant Clinical Geneticist in the NSW Genetics of Learning Disability (GOLD) Service at Hunter Genetics, Australia. She holds a conjoint professorship at the University of Newcastle within the School of Medicine and Public Health, Department of Medical Genetics. Her work bridges clinical research and patient advocacy, focusing on neurofibromatosis type 1 (NF1) and rare genetic diseases. PhD, University of Newcastle Co-founder, Rare Voices Australia Her research explores genetic modifiers in NF1 severity and the application of 2D facial recognition technology (FaceMatch) for diagnosing syndromic intellectual disability. She leads a $1.6M Medical Research Future Fund project on cutaneous neurofibromas and has contributed to RNA diagnostics standardization via the SpliceACORD consortium . The FaceMatch platform integrates computer vision with genomic data to enhance diagnostic accuracy across age groups. Her studies span neurogenetic disorders , X-linked intellectual disability , and RNA splicing mechanisms , with collaborative links to the Max Planck Institute and Wellcome Trust Sanger Institute. 2021 Research Australia Health and Medical Research Data Innovation Award 2015 HCRF Research Mentor of the Year 2024 Member of the Order of Australia (AM) She supervises 3 higher-degree research students in rare disease studies and mentors medical students in case report publication. Her community roles include the Medical Advisory Committee of the Steve Waugh Foundation for rare disease advocacy.

• Genetics
• Intellectual Disability
• X Chromosome Disorders
• +۴ مورد دیگر

Dr. Anna Hackett is a Conjoint Senior Lecturer in the School of Biomedical Sciences and Pharmacy at the University of Newcastle, specializing in Medical Genetics. With over two decades of research experience, her work primarily focuses on X-linked intellectual disability disorders, genetic diagnostics, and the molecular mechanisms underlying neurodevelopmental conditions. Her research interests encompass a wide range of topics within medical genetics, including X chromosome disorders, noncoding variants in intellectual disability, genomic diagnostics, and the molecular pathways involved in neurodevelopmental disorders. Dr. Hackett has made significant contributions to understanding the genetic basis of X-linked intellectual disability through the identification of novel genes and variants. Analysis of her recent publications reveals a strong focus on advanced genomic technologies for diagnosing intellectual disability, with particular emphasis on X-linked disorders. Her work spans from basic molecular mechanisms to clinical applications, demonstrating a translational research approach that bridges laboratory findings with patient care. She has been instrumental in developing and applying next-generation sequencing techniques for improved diagnostic yield in genetic disorders. Dr. Hackett maintains an active research program with extensive collaborations across multiple institutions in Australia and internationally. Her work has contributed significantly to the understanding of X-linked intellectual disability mechanisms, genomic diagnostics, and the clinical implications of genetic variants. She is frequently involved in large-scale collaborative studies that combine clinical expertise with advanced genomic technologies to improve diagnosis and understanding of genetic disorders.