جستجوی استاد راهنمای دانشگاهی

• 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.

• Fluid Mechanics
• Civil Engineering
• Environmental Engineering
• +۶ مورد دیگر

Professor Tongming Zhou is a faculty member in the Department of Civil, Environmental and Mining Engineering at the School of Engineering, The University of Western Australia (UWA) . He serves as Director of the UWA Boundary Layer Wind Tunnel Laboratory and Program Chair for Civil Engineering , contributing to both academic leadership and industrial applications. His work bridges fundamental fluid mechanics with practical engineering challenges. Education : PhD in Fluid Mechanics from The University of Newcastle (1999) Teaching : Coordinates core units like CIVL2551, CIVL5551, and CIVL4402/CIVL3402 Hydraulics, emphasizing real-world application and industry collaboration Research Interests focus on: Suppression of vortex shedding and vortex-induced vibrations (VIV) in cylindrical structures Enhancement of VIV and galloping for renewable energy harvesting Wave resonance in floating LNG facilities Sloshing dynamics in tanks with Newtonian/non-Newtonian fluids Wind tunnel testing for industrial wind load analysis Recent Research Trends show interdisciplinary work combining experimental and numerical fluid dynamics, with applications to offshore engineering, maritime safety, and energy systems. His projects explore VIV in flexible risers, gas leakage effects on pipelines, and triboelectric nanogenerators for wind energy. Grants : ARC Grant (2019-2021): Development of novel inerter-based dampers ARC Grant (2013-2015): Local Scour below Offshore Pipelines ARC Grant (2011-2015): Vortex & Force Characteristics of Inclined Cylinders UWA Grant (2008): Control of Vortex Shedding with Helical Strakes Facilities Leadership : Upgraded UWA’s Boundary Layer Wind Tunnel , Hydraulic Laboratory Water Flume , and 6DOF Hexapod motion platform , acquiring advanced equipment like PIV systems and high-precision load cells.

Jiwon Kimمشاهده پروفایل

دانشیار

• Transport Engineering
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Associate Professor Jiwon Kim is a leading researcher in Transport Engineering at the University of Queensland's School of Civil Engineering. She serves as Director of Higher Degree by Research and was a DECRA Fellow from 2019-2022. Holding degrees from Korea University and Northwestern University, she specializes in AI/ML applications for transportation systems. PhD, Northwestern University BS & MS, Korea University Her research focuses on Artificial Intelligence and Machine Learning applications in transportation, including: Deep learning for traffic management Reinforcement learning in mixed traffic environments Multi-agent systems for urban mobility optimization Spatiotemporal trajectory analysis Recent publications demonstrate expertise in: Eco-driving strategies Traffic incident prediction Queue length estimation Crash risk modeling Scientific recognition includes: ARC DECRA Fellowship (2019-2022) She supervises doctoral students in: Transportation data analytics Autonomous vehicle systems Intelligent traffic management Current projects explore real-time traffic monitoring, synthetic mobility data generation, and connected vehicle technologies.

• Electrical Engineering
• Power Systems
• Renewable Energy
• +۵ مورد دیگر

Professor Grahame Holmes is an Honorary Professor in the School of Engineering at RMIT University, Australia. His expertise spans electrical energy conversion, smart energy systems, renewable energy integration, power electronics, and grid infrastructure. He focuses on advancing technologies for sustainable energy storage, grid stability, and high-efficiency power conversion. Research Interests : Electrical and Electronic Engineering, Communications Technologies, Power Electronics, Renewable Energy Systems, and Grid Integration Solutions. His work emphasizes practical applications such as hydrogen energy storage systems, grid-interactive inverters, and modular multilevel converters. Recent Contributions : Prof. Holmes has published extensively on topics like advanced PWM techniques, resonant current controllers, and DC transformer designs. His research bridges theoretical advancements with real-world implementations, addressing challenges in smart grid stability and high-frequency power conversion. Advising & Grants : Supervised projects include 'Hydrogen Energy Storage System for Nanogrid' (2015) and 'Synchronised Control of Grid-Interactive Inverters' (2015). While specific grant details are not listed, his work aligns with major themes in sustainable energy research. Labs & Collaborations : Engages in collaborative research through RMIT's facilities, focusing on hardware-software co-simulation frameworks and FPGA-based real-time systems.

• Cybersecurity and Privacy
• Data Management and Data Science
• Distributed Computing and Systems Software

Professor Jun Zhang is a leading academic in cybersecurity at Swinburne University, Australia, where he directs the Cybersecurity Lab. He has been honored as Australia's top cybersecurity researcher and instrumental in establishing Swinburne as a globally recognized cybersecurity research institution. His work includes high-impact papers and multi-million-dollar R&D projects, culminating in awards like the 2021 'Top Cybersecurity Research Institution' accolade. As course director of the Bachelor of Cyber Security, he pioneered an industry-driven teaching model with Deloitte and CSIRO, significantly boosting course enrollment. His collaborations extend to Adobe's Curriculum Innovation Program and the Australian P-TECH initiative, promoting STEM education and cybersecurity awareness. He supervises doctoral candidates and leads grants focused on AI-driven cybersecurity, smart home security, and blockchain-based edge computing. His research spans vulnerability detection, GAN forensics, IoT security, and privacy preservation in OSNs. Research interests include cybersecurity fundamentals, data science applications, and distributed systems. Notable achievements include the PTFix framework for Java vulnerabilities, the IoTFuzz smart home testing system, and CTI mining methodologies. Awards reflect his mid-career research excellence and industry partnerships. His grants with CSIRO and defense organizations emphasize real-world impact, addressing challenges from malware detection to adversarial machine learning. The Cybersecurity Lab and collaborative projects like Artchain demonstrate his commitment to bridging academia and industry. Professional activities include supervising over 20 HDR students and securing grants totaling millions. His work on blockchain-based edge storage (CSEdge) and SDCCP congestion control highlights innovation in networking. Future directions include advancing AI for design collaboration with CSIRO and enhancing privacy in smart energy technologies. His contributions span technical, educational, and community outreach domains, positioning him as a pivotal figure in cybersecurity's evolution.

• Cybersecurity
• Privacy-Preserving Technologies
• Internet of Things (IoT)
• +۴ مورد دیگر

Dr. Kanchana Thilakarathna is a Senior Lecturer in Distributed Computing at the University of Sydney's School of Computer Science, and a member of the Centre for Distributed and High Performance Computing. They hold a PhD from the University of New South Wales (UNSW) and a B.Sc. Eng (Hons) from the University of Moratuwa, Sri Lanka. Prior to academia, they worked as a Research Scientist at CSIRO/Data61 and had industry experience as a Mobile Radio Network Engineer. Research Interests : Dr. Thilakarathna focuses on cybersecurity, privacy in mobile and IoT systems, mixed reality privacy, and distributed computing platforms. Their work emphasizes user-centric solutions like the Yalut social media app, which enables decentralized data sharing. Key themes include privacy-preserving techniques, edge computing, and secure federated learning frameworks. Recent Work : Recent articles (2023–2025) explore machine unlearning for large language models, federated learning security, and IoT network slicing using P4 programmability. Their work on synthetic video traffic generation (VideoTrain++) and drone detection (DronePrint) demonstrates cross-disciplinary innovation. Awards : Malcolm Chaikin Prize (2015), Meta Research Awards (2020/2022), and Heidelberg Laureate Fellowship (2019). Grants : ARC Research Hub for Future Digital Manufacturing (2024), NSW Defence Innovation Network Projects (2024/2021), and Facebook Research Awards (2022/2020). Students : Advising 4 current PhD students on topics like wireless trust establishment and machine unlearning. Labs/Teams : Part of the Centre for Distributed and High Performance Computing and Sydney Nano Institute.

• Computer Vision
• Machine Learning
• Robotics
• +۶ مورد دیگر

Dr. Feras Dayoub is a Senior Lecturer at the School of Computer and Mathematical Sciences (Faculty of Sciences, Engineering and Technology) at the University of Adelaide , specializing in Embodied AI and Robotic Vision within the Australian Institute for Machine Learning (AIML) . He co-directs the CROSSING French-Australian laboratory for human-autonomous agent teaming and holds an Adjunct position at the Queensland University of Technology (QUT) , serving as an Associate Investigator at its Centre for Robotics . Previously, he was a Chief Investigator at the ARC Centre of Excellence for Robotic Vision . His research focuses on advancing reliable deployment of computer vision and machine learning on mobile robots in real-world environments. Applied projects include agricultural automation , environmental conservation , and autonomous infrastructure monitoring . He has published extensively on topics like object detection , domain adaptation , 3D representation learning , and vision-language navigation , with a particular emphasis on robustness in dynamic and partially observed environments. Dr. Dayoub is also an educator specializing in programming , computer vision , and robotic perception . He contributes to open-source robotics research through tools like AARK (Autonomous Racing Toolkit) and has led teams developing solutions for precision agriculture (e.g., Deepfruits fruit detection system) and environmental monitoring (e.g., Crown-Of-Thorns starfish detection ). Key Collaborations : CROSSING Lab, QUT Centre for Robotics Research Themes : Embodied AI, Robust Perception, Domain Adaptation

• Mechanobiology
• Biomechanics
• Organ-on-chip
• +۵ مورد دیگر

Associate Professor Arnold Lining Ju is a biomedical engineer at the University of Sydney's School of Biomedical Engineering, affiliated with multiple institutes including the Heart Research Institute and Sydney Nano Institute. He holds academic positions in both the Faculty of Engineering and Faculty of Medicine & Health. Education: BSc from Peking University, PhD from Georgia Tech and Emory University (USA). Honors include Snow Fellowship, Heart Foundation Future Leader Fellowship, and multiple awards for cardiovascular research innovation. Research focuses on mechanobiology and biomechanics of thrombosis, developing microfluidic devices and organ-on-chip systems. Key projects include AI-driven single-cell nanotools, 3D biofabrication, and anti-thrombotic peptide design. Leads interdisciplinary teams and collaborates internationally with institutions like Harvard and University of Texas. Teaching roles include coordinating advanced cellular biomechanics courses and supervising PhD/Masters students in biomedical engineering and physiology. Over 50 peer-reviewed publications, with contributions to Nature Materials, Nature Communications, and other top journals.

David Burtonمشاهده پروفایل

مدرس ارشد

• Aerodynamics
• Fluid Mechanics
• Wind Engineering
• +۱۱ مورد دیگر

David Burton is a Senior Lecturer in the Department of Mechanical & Aerospace Engineering at Monash University, Faculty of Engineering. He leads the Monash Wind Tunnel Research Platform (MWTRP), a major research facility supporting experimental and applied aerodynamics research across multiple industries. Research Interests: His expertise lies in experimental fluid dynamics, with a focus on wind engineering, industrial aerodynamics, and aero-acoustics. Key areas include building, vehicle, and sports aerodynamics, flow control, and the impact of wind storms and cyclones. He integrates experimental testing with numerical simulation, particularly in complex bluff body flows and sustainable engineering design. The recent publication trends reflect a strong emphasis on postcritical flow over rough and multiple cylinders, aerodynamic modeling in sports (especially cycling), and real-world applications such as freight train aerodynamics and cyclone resilience. His work combines rigorous experimentation with practical engineering solutions. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: David Burton is accepting PhD students and actively supervises research projects. He has served as Primary Chief Investigator on significant research grants, including 'Wind and Water Loading of Flags in Cyclones' (2021–2022) and 'Wind Comfort Simulation and New Engineering Design Process' (2022–2023), demonstrating sustained external funding and project leadership. Labs and Teams: He manages the Monash Wind Tunnel Research Platform (MWTRP), an ISO9001-accredited facility featuring the largest wind tunnel of its type in the Southern Hemisphere. The platform includes CNC machining, rapid prototyping, and a multidisciplinary team of postgraduate students, designers, technical officers, and postdoctoral researchers, supporting collaborations across automotive, defense, construction, UAVs, wind energy, and sports sectors.

Wade Smithمشاهده پروفایل

مدرس ارشد

• Dynamics, vibration and vibration control
• Signal processing
• Modelling and simulation
• +۷ مورد دیگر

Dr. Wade Smith is a Senior Lecturer within the School of Mechanical and Manufacturing Engineering at the University of New South Wales. He is an active member of the WAVES research group (Wear, Aeroacoustics and Vibration in Engineering Systems) and conducts his research in the Tribology and Machine Condition Monitoring laboratory. His primary research interests include vibration-based diagnostics of rotating machinery, prognostics of rotating machinery, gear wear monitoring and prediction, simulation and modeling of rotating machines for diagnostic applications, and signal processing of machine vibration signatures using cyclostationarity. His work has significant applications in industrial machinery health monitoring and predictive maintenance systems. Dr. Smith's recent publications demonstrate a consistent focus on advanced diagnostic techniques for rotating machinery, with particular emphasis on gear systems and bearings. His research integrates traditional mechanical engineering principles with modern signal processing and machine learning approaches to develop more effective condition monitoring solutions. He actively supervises PhD and Masters students on projects related to gear diagnostics, wear monitoring, and vibration analysis. His current research projects include gear diagnostics in planetary gearboxes using internal sensors, gear wear monitoring and prediction, sliding contact-induced vibration studies, and transmission-error-based gear diagnostics. Dr. Smith's laboratory is equipped with specialized facilities including gearbox test rigs (both planetary and parallel configurations), a rolling element bearing test rig, an engine test rig, friction rig, tribometer, high-quality microscope, and extensive instrumentation for vibration analysis. His research has attracted collaborations with institutions including Queensland University of Technology, SpectraQuest (USA), Weir Minerals, University of Technology Sydney, RWTH Aachen University (Germany), and Safran.

• Medical Imaging
• Molecular Imaging
• Neuroscience
• +۳ مورد دیگر

Steven Meikle is a Professor of Medical Imaging Physics and Head of the Imaging Physics Laboratory at the Brain and Mind Centre, University of Sydney. He also serves as Deputy Director (Preclinical) of Sydney Imaging and Deputy Director of the National Imaging Facility's Sydney node. His expertise spans advanced imaging technologies, with a focus on PET/SPECT instrumentation and molecular imaging. He holds a B.App.Sc.(Hons) from the University of Technology Sydney and a PhD from the University of New South Wales. Research focuses include developing novel PET systems like Open-field PET (for freely moving rodents) and Total Body PET, which enhance imaging sensitivity and enable real-time behavioral studies alongside brain function analysis. Collaborations include Tsinghua University (China) and UC Davis (USA). He leads projects on motion correction, quantitative imaging, and AI-driven analysis. Key achievements include over 180 peer-reviewed publications, editorial roles in Physics in Medicine and Biology , and leadership in professional societies. Awards include IEEE Senior Membership and Australian Institute of Physics Fellowship. Current student projects explore Total Body PET applications, motion correction, and radiopharmaceutical evaluation. Teaching roles include medical physics courses in diagnostic radiography and medical physics programs. He advises on imaging ethics, facility implementation, and translational research bridging basic science and clinical applications.

• Computational Mechanics
• Scaled Boundary Finite-Element Method
• Dynamic Soil-Structure Interaction
• +۵ مورد دیگر

Professor Chongmin Song is a faculty member at the University of New South Wales (UNSW), affiliated with the School of Civil and Environmental Engineering. His academic rank is Professor, and he specializes in computational mechanics with a focus on innovative numerical methods. He holds a BE and ME from Tsinghua University and a DEng from the University of Tokyo. His research explores computational mechanics, fracture analysis, wave propagation, and soil-structure interactions. Key methodologies include the Scaled Boundary Finite Element Method (SBFEM), image-based modeling, and dynamic simulations of infrastructure systems. He leads significant ARC-funded projects like 'A scaled boundary framework for nonlinear dynamic analysis of structures' (DP250100955) and 'Developing sustainable graded porous cementitious structures' (LP240100123), totaling over $1M in recent grants. Recent publications emphasize adaptive modeling techniques, multiphysics simulations, and high-performance computing applications. Trends include topology optimization for structural dynamics, phase-field fracture modeling for brittle materials, and GPU-accelerated elastodynamics. His work integrates computational efficiency with real-world engineering challenges, particularly in geomechanics and material failure analysis. Professor Song collaborates extensively on projects involving computational fracture mechanics and maintains laboratories focused on numerical simulation advancements. Future work targets scalable algorithms for 3D crack propagation and multiphysics coupling in infrastructure systems.

Jon McCormackمشاهده پروفایل

استاد

• Computational Creativity
• Human-machine interfaces
• Artificial Intelligence/Cybernetics
• +۹ مورد دیگر

Jon McCormack is a Professor jointly appointed in Monash University's Faculty of Art, Design & Architecture (MADA) and Faculty of Information Technology. He founded and directs SensiLab, a research facility focusing on computational creativity, human-machine interfaces, and generative systems. His work spans electronic media art, evolutionary music, and artificial life. McCormack holds a PhD in Computer Science from Monash University, along with degrees in Computer Science, Applied Mathematics, and Film/Television. Research interests include computational creativity, tangible interfaces, and cybernetic systems. Notable projects include 'Explainable Artificial Creativity' (ARC-funded) and 'Building 4.0 CRC,' addressing architectural innovation through AI. He has been recognized with awards for collaborative projects like the Blundstone Intelligent Footwear for Healthcare. McCormack's recent articles explore AI-driven art, generative systems, and interdisciplinary design. His work bridges artistic practice with technical innovation, emphasizing ethical and creative dimensions of human-AI collaboration. SensiLab serves as a hub for practice-based research in digital media and interactive systems. Education: PhD in Computer Science, Monash University (2004) Bachelor of Science (Honours), Computer Science/Applied Mathematics, Monash University (1987) Graduate Diploma in Film/TV, Swinburne University (1986) Bachelor of Science, Computer Science/Applied Mathematics, Monash University (1985) Key Projects: Lead investigator on 'Explainable Artificial Creativity' (2022–2026) Co-investigator in 'Building 4.0 CRC' (2020–2027), exploring AI-driven architectural design Awards: 2022 Designers Australia Award for Blundstone Footwear 2020 'On the Machine Condition' Prize McCormack's lab, SensiLab, fosters collaborations across disciplines, producing exhibitions, software, and theoretical frameworks for computational creativity. He actively supervises PhD students in practice-based research, emphasizing the intersection of art and technology.

• Radiation Oncology
• Medical Physics
• Cancer Treatment
• +۳ مورد دیگر

Dr Emily Hewson is a Cancer Institute NSW Early Career Fellow and member of the Sydney School of Health Sciences at the University of Sydney's Faculty of Medicine and Health. Her research focuses on advancing real-time radiation therapy techniques, particularly in managing intrafraction motion for prostate and other cancers. She leads projects involving multileaf collimator (MLC) tracking, dose optimization, and deep learning integration in radiation oncology. Research interests include adaptive radiotherapy systems, kilovoltage intrafraction monitoring (KIM), and clinical trial implementation (e.g., TROG 15.01 SPARK trial). Her work emphasizes improving treatment accuracy through real-time dose-guided approaches and multitarget tracking for tumors with complex motion patterns. Developed experimental validations for MRI-linac integration and MLC tracking systems Authored a textbook chapter on Adaptive Radiation Therapy (ART) Recipient of Cancer Institute NSW Early Career Fellowship (2023) Recent grants include an AI platform for targeted radiotherapy (2024) and national critical infrastructure funding for lung cancer applications (2023). Her lab collaborates on real-time dose calculation algorithms and clinical trial implementation across multiple institutions.

SangHyung Ahnمشاهده پروفایل

مدرس

• Construction Process Modelling
• Building Information Modelling (BIM)
• Agent-Based Simulation
• +۳ مورد دیگر

SangHyung Ahn is a Lecturer at the School of Civil Engineering , University of Queensland (UQ), since 2017. He joined UQ as a postdoctoral research fellow in 2015 after earning his PhD in Civil Engineering (Construction Engineering and Management) from Purdue University, USA. Prior to his academic career, he worked as an assistant manager at Hyundai Engineering and Construction Co., Ltd. (2003-2007) and holds an MBA in international business from Hanyang University and a B.Sc in Civil Engineering from Korea University. Research Focus: Construction process modelling with virtual reality, decision support systems for construction, automation of data-driven simulation modelling, sensor-based operations analysis, and integration of Building Information Modelling (BIM). Teaching: Coordinates undergraduate courses Introduction to Project Management (CIVL3510) and Construction Engineering Management (CIVL4522) . Research Trends: His recent publications highlight interdisciplinary work in transportation engineering, structural design, and AI-driven simulation tools. Key themes include application of machine learning to car-following models, drone-based vehicle identification, and optimization of public transport systems using agent-based simulations. Supervision: Available for supervision, with completed supervision of PhD and Master’s theses on topics such as BIM-LCA integration, pedestrian trajectory analysis, and AI-driven driving behavior models.