جست‌وجوی استاد و پژوهشگر

• Computer Vision
• Robotics
• Machine Learning
• +۵ مورد دیگر

Dr. Hamid Rezatofighi is a Senior Lecturer in the Department of Data Science & AI at Monash University's Faculty of Information Technology in Australia. He holds a PhD from the Australian National University (2015) and a Master's in Biomedical Engineering from the University of Tehran (2009). Previously, he was an Endeavour Research Fellow at Stanford University and a Senior Research Fellow at the University of Adelaide's Australian Institute for Machine Learning (AIML). His research focuses on computer vision, robotics, and deep learning, with emphasis on robot visual perception in dynamic environments. Key contributions include multi-object tracking, autonomous systems, and neuro-symbolic AI frameworks. He has led over $17M in research funding, including DARPA projects and an ARC Discovery Project. His work contributes to UN SDG goals related to innovation and infrastructure. Notable projects include the Neuro-Symbolic Systems (HARNESS) project ($5M+), real-time safety intervention systems, and semantic 3D reconstruction frameworks. He has published >80 peer-reviewed papers in top venues like CVPR/ICCV/ECCV and serves as an Area Chair for major AI conferences. His datasets (JRDB series) are widely used benchmarks for robotic perception. Current research spans autonomous navigation, multi-sensor fusion, and socially-aware human-robot interaction.

• Integrable Systems
• Nonlinear Differential Equations
• Difference Equations
• +۳ مورد دیگر

Dr. Peter Van Der Kamp is a Senior Lecturer in Mathematics at La Trobe University's School of Mathematics & Statistics. His research focuses on integrable systems, particularly algebraic and geometric properties of nonlinear differential and difference equations. He has collaborated extensively on projects involving Poisson algebras, Lotka-Volterra systems, and discrete integrable equations. Education: Doctorandus (Theoretical Physics) from Vrije Universiteit (VU Amsterdam), Netherlands PhD (Mathematics) from Vrije Universiteit (VU Amsterdam), Netherlands Research Interests: Dr. Van Der Kamp's work spans integrable systems, with emphasis on: Development of discrete integrable equations Analysis of Lotka-Volterra systems and their superintegrability Study of Darboux polynomials and preserved measures Exploration of boundary conditions in quad equations His research often intersects nonlinear dynamics, algebraic geometry, and mathematical physics. Publications Trends: Recent articles highlight advancements in: Quadratic Poisson algebras and Lambert W-function solutions Trilinear/quadrilinear lattice equations Superintegrable tree-systems and their discretizations New integrable maps in R^4 Collaborations with experts like Quispel and Nijhoff are central to his work. Grants: Australian Research Council (ARC) Discovery Project: 'Discrete integrable systems' (2011–2015) Labs/Teams: Active contributor to the La Trobe University Mathematics group, focusing on discrete integrability and nonlinear systems research.

• Biomedical Engineering
• Mechanical Engineering
• Cardiovascular Engineering
• +۷ مورد دیگر

Jorge Amaya Catano is a Research Fellow - Mechanical and Validation Engineering at the Centre for Biomedical Technologies , Queensland University of Technology (QUT). He holds a PhD in Biomedical Engineering from QUT (2024) and a Master's in Engineering from EAFIT University (2014). Roles: Research Fellow (QUT), Guest Lecturer (QUT), Adjunct Professor (EAFIT University, Colombia) Education: PhD (Biomedical Engineering, QUT 2024), Master of Engineering (EAFIT 2014) His research focuses on cardiovascular engineering , tissue engineering , and biomedical device validation , with technical expertise in fluid dynamics , biomaterials , bioreactor development , 3D printing , and cell culture techniques . Recent publications explore arterial geometry changes, coronary hemodynamics, optical coherence elastography, and microfluidic pump design. Professional experience includes: Mechanical design engineer for implantable medical devices at BioQ Devices - QHeart Medical (2019-2024) Research Assistant at QUT (Semester 1 2023, Semester 2 2021) Technical Service Engineer at Sesmacol SAS (2016-2018) Production Manager at Dumhos Investments (2015-2016) He supervises research projects and contributes to the Cardiovascular Technology Laboratory at QUT.

• Medical Imaging
• Computer Vision
• Biomedical AI
• +۲ مورد دیگر

Olivier Salvado is Professor of Artificial Intelligence at Queensland University of Technology, leading the AI for Health Research Network. His research develops next-generation AI technologies for medical imaging analysis, with applications in cortical surface reconstruction, diagnostic algorithm interpretability, and 3D wound modeling. Formerly Chief Research Scientist at CSIRO leading the $25M+ AI for Missions program, his work combines computer vision, deep learning, and biomedical engineering. Research domains include: Interpretable AI for medical diagnosis Neural volume rendering techniques 3D tissue reconstruction from images Biomechanical modeling of biological tissues He currently offers PhD positions in AI applications for health and serves as associate editor for the Journal of Medical Imaging.

• Applied Mathematics
• Multiphase Systems
• Industrial Process Modeling
• +۲ مورد دیگر

Steven Psaltis is a Senior Research Fellow at Queensland University of Technology specializing in mathematical modeling of multiscale, multiphase systems with applications in industrial processes and porous media flow. His research develops computational methods for aluminum electrolysis, wood product characterization, and resource estimation in energy fields. With expertise in C/C++ and OpenGL, he creates virtual reconstruction techniques for material analysis. Research applications include: Aluminum hydroxide precipitation dynamics Coal seam gas production modeling Timber billet reconstruction from rotary peeling Agrochemical transport in plant systems He teaches multivariable calculus, differential equations, and engineering mathematics while developing GPU-accelerated computational methods.

• Bone Mechanics
• Osteoporosis
• Human Motion
• +۵ مورد دیگر

Saulo Martelli is an Associate Professor in Biomedical Engineering and Biomechanics at Queensland University of Technology's School of Mech., Medical & Process Engineering. His research focuses on musculoskeletal biomechanics, particularly quantifying the relationship between anatomical structure, physical activity, and musculoskeletal function in health and disease. He has pioneered computational methods for studying neuromuscular control, bone fracture risk, and exercise prescription in osteoporosis, while advancing experimental techniques for bone microstructure analysis and real-time loading assessment. Teaching includes courses such as Finite-Element Modelling, Advanced Bio-Mechanics in Orthopedics, Sports Biomechanics, and Dynamics. His work aligns with UN Sustainable Development Goals related to health and innovation. He actively contributes to the medical devices industry through research optimizing joint replacements and virtual trials of orthopaedic devices. Research interests span bone mechanics, osteoporosis, human motion modeling, and joint mechanics. Key areas include musculoskeletal modeling validation, bone adaptation to mechanical loading, and non-invasive imaging techniques for clinical applications. Recent work emphasizes algorithm development for strain estimation and computational tools for personalized medicine. Publications highlight advancements in shoulder joint stability modeling, cortical bone adaptation, and friction dynamics. His work integrates biomechanical and computational approaches to address clinical challenges in orthopaedics and sports science. Advising includes supervision of Raissa Katembwe (2016). Collaborations focus on software development for clinical imaging integration and interdisciplinary projects with engineering and medical communities.

• Reliability Engineering
• Maintenance Optimisation
• Predictive Control
• +۸ مورد دیگر

Michael E. Cholette is an Associate Professor in the School of Mechanical, Medical & Process Engineering at Queensland University of Technology's Faculty of Engineering. With expertise spanning multiple engineering disciplines related to dynamic systems, reliability, and applied optimization, his work focuses on practical applications across various industries and infrastructure systems. Dr. Cholette earned his B.S. from the University of Michigan in 2007 and completed his Ph.D. at the University of Texas at Austin in 2012, where his research centered on fault detection and diagnosis for complex systems with applications in automotive systems and semiconductor manufacturing. Following his doctoral studies, he worked as a postdoctoral research fellow with the CRC for Infrastructure and Engineering Asset Management in Brisbane, Australia, focusing on reliability modeling and asset management before joining QUT as a Lecturer in 2013. He was promoted to Associate Professor in 2021. His primary research interests include asset management, reliability modeling, Condition-Based Maintenance (CBM), and maintenance optimization. Additional research areas encompass condition monitoring, control systems, autonomous vehicles, and building optimization. Dr. Cholette has successfully secured research funding from various industrial and government bodies including Queensland Rail, Wilmar Sugar, the Australian Research Council, the Australian Renewable Energy Agency, and the US Department of Energy. His recent publications reveal a strong focus on renewable energy systems, particularly concentrated solar power plants, with significant contributions to solar field design, heliostat soiling management, and thermal storage optimization. His transportation-related research shows expertise in railway infrastructure maintenance, track geometry monitoring, and predictive maintenance approaches. The interdisciplinary nature of his work bridges mechanical engineering, control theory, and operations research to solve practical engineering challenges. Fellow of the International Society of Engineering Asset Management Co-chair of the Scientific Committee for the 2017 World Congress on Engineering Asset Management Member of Engineers Australia Dr. Cholette has supervised numerous doctoral students whose research spans solar energy systems, autonomous vehicle control, building energy optimization, and maintenance planning. His teaching includes courses in Engineering Asset Management and Maintenance, Vibration & Control, and Advanced Dynamics. He actively participates in multiple academic and professional societies and maintains strong industry connections that inform both his research and teaching practices.

• Composite Materials
• Structural Engineering
• Finite Element Analysis
• +۳ مورد دیگر

Dr. Cam Minh Tri Tien is a Postdoctoral Research Fellow at the University of Southern Queensland (USQ), affiliated with the Centre for Future Materials and the iLAuNCH research group, within the School of Engineering. His expertise spans composite materials, structural engineering, and numerical methods. He holds a BEng from HoChiMinhUT (2008), an MSc from Konkuk University (2010), and a PhD from USQ (2016). His research focuses on pipeline rehabilitation systems, advanced fluid dynamics simulations, and structural behavior analysis of composite materials. His work includes developing predictive models for internal replacement pipe systems under various loading conditions and advancing numerical techniques like integrated radial basis functions (RBFs) for solving complex engineering problems. Recent contributions address debonding effects in structural repairs, temperature-induced axial responses, and digital twin applications in composite component lifecycle management. Dr. Tien has supervised multiple doctoral and master’s projects, including principal supervision of a doctoral thesis on digitizing composite component workflows. His research outputs total 18312 views and 1840 downloads, with active engagement in international conferences and peer-reviewed journals.

John Davyمشاهده پروفایل

استاد مدعو

• Acoustics
• Building Acoustics
• Vibration Engineering
• +۵ مورد دیگر

Adjunct Professor John Davy is affiliated with RMIT University's School of Science, specializing in acoustics and vibration engineering. With over 50 years of research experience, his work focuses on sound insulation, building acoustics, and automotive noise reduction. He collaborates with Professor Mohammad Fard on squeak and rattle noise classification in vehicles and holds part-time roles at CSIRO and as a consultant for USG Boral. His industry experience includes leadership roles in organizations such as the International Institute of Acoustics and Vibration and the ISO working groups on sound insulation and room acoustics. Key areas of research include structural connections in cavity walls, porous materials for sound absorption, and vibration effects on driver alertness. His academic contributions span theoretical and applied acoustics, with recent studies addressing driver performance in automated vehicles, acoustic measurement methodologies, and material science for noise control. Awards and recognitions include his part-time industry engagement and collaborative research projects. His work bridges academic research and industrial applications, emphasizing practical solutions for acoustic challenges in buildings and transportation systems.

Reza Nakhaie Jazarمشاهده پروفایل

استاد

• Mechanical Engineering
• Automotive Engineering
• Electrical and Electronic Engineering
• +۸ مورد دیگر

Professor Reza Nakhaie Jazar is the Discipline Head of Mechanical and Automotive Engineering at RMIT University's School of Aerospace, Mechanical and Manufacturing Engineering, where he has led teaching and research programs since 2009. Prior to this, he served as an Adjunct Professor at Columbia University (2007–2009) and held academic roles including Assistant Professor at North Dakota State University (2001–2006) and Research Fellowships at the University of Waterloo and University of Calgary (2000–2001 and 1999–2000). He also lectured at Iranian institutions earlier in his career. His research focuses on dynamic systems, vehicle dynamics (with emphasis on autonomous vehicles and safety), MEMS (microelectromechanical systems), and robotics. Professor Jazar has contributed to industry-standard methodologies such as the RMS Optimization method and Floating-Time method, and has published over 200 works, including books and journal articles. He is Editor-in-Chief of the Journal of Nonlinear Engineering and actively engages with conferences and publishers globally. His research interests span Mechanical Engineering , Automotive Engineering , Electrical and Electronic Engineering , Biomedical Engineering , Manufacturing Engineering , and Classical Physics . He explores topics like nonlinear dynamics, vibration isolation, and optimal control in robotics and vehicles. Recent projects include developing algorithms to enhance EV charging infrastructure, trajectory optimization for autonomous vehicles, and improving vehicle safety through infrastructure-based sensors. Professor Jazar supervises research projects on automotive systems, MEMS, and robotics. His work integrates machine learning and mathematical modeling to address challenges in energy management, fault-tolerant control, and smart vehicle design. No scientific awards are explicitly mentioned in the text, though his editorial roles and contributions highlight significant academic influence.

• Electrical and Electronic Engineering
• Materials Engineering
• Nanotechnology
• +۳ مورد دیگر

Shruti Nirantar is a Lecturer in Electronic Engineering at RMIT University's School of Engineering. Her research focuses on advanced materials and nanotechnology for next-generation electronics, including neuromorphic memories, vacuum electron devices, and sensor technologies. She actively supervises PhD and Master’s students in areas such as quantum technologies, nanoscale electronics, and sustainable energy systems. Her research interests span electrical engineering, materials science, and optical physics, with a strong emphasis on practical applications like phase-change devices, thin-film sensors, and graphene-based systems. She has contributed to high-impact studies on resistive switching memory, ferroelectric tunnel junctions, and terahertz photonics, published in journals like Advanced Materials and Nano Letters . Dr. Nirantar’s work bridges fundamental materials science and applied nanoelectronics, addressing challenges in energy efficiency, device miniaturization, and smart sensor integration. Current projects include developing nanoscale vacuum-channel circuits for satellite communications and off-grid water purification systems using graphene membranes. She has supervised 2 completed PhD students and currently guides 3 PhD and 1 Master’s candidate. Her contributions to semiconductor-free nanoelectronics and terahertz technologies have been recognized through collaborations with industry and academic institutions globally.

Andrew Eberhardمشاهده پروفایل

استاد

• Optimization Theory
• Machine Learning
• Convex Analysis
• +۷ مورد دیگر

Professor Andrew Eberhard holds the position of Deputy Head of Department (Research and Innovation) in the Department of Mathematical and Geospatial Sciences (MGS) at RMIT University's School of Science. He has also served as Deputy Director of the Australian Mathematical Sciences Institute (AMSI) and currently sits on its board. His academic journey includes visiting professorships at institutions such as the University of Perpignan (France), Dalhousie University (Canada), and Blaise Pascal University (France). He has contributed significantly to optimization theory and applications, including roles as Co-chair of the AustMS special interest group (MoCaO) from 2018–2024 and Program Leader of the Platform Technologies Research Institute (2012–2015). Professor Eberhard's research focuses on nonsmooth analysis, convex functions approximation, optimization algorithms, and their applications in control theory, signal processing, and economic modeling. He has applied his theoretical work to real-world challenges like utility function estimation, air traffic flow management, and blood inventory optimization. His recent work includes advancements in stochastic optimization with integer variables and machine learning integration for enhancing algorithm performance. He has been an invited speaker at prestigious events such as the International Conference on Applied Mathematics (2024, Vietnam), Variational and Nonsmooth Analysis (2024, Hong Kong Polytechnic University), and ANZIAM's plenary session (2012, Australia). His teaching interests emphasize nonsmooth analysis and its interdisciplinary applications. Professor Eberhard has supervised numerous research projects, including those on hyperparameter optimization in machine learning, MIMO signal processing, and asset protection routing. His grants include leadership roles in developing algorithms for stochastic integer programming and multi-criteria decision-making under uncertainty. He collaborates actively through the Platform Technologies Research Institute and is affiliated with multiple academic journals as an editor or reviewer.

• Manufacturing Engineering
• Mechanical Engineering
• Materials Engineering
• +۳ مورد دیگر

Professor John Mo is a distinguished academic and researcher in manufacturing systems, enterprise modeling, and industrial automation, affiliated with RMIT University's School of Engineering. He holds a professorial position and has over 30 years of experience in academia and research institutions like CSIRO. His work focuses on complex engineering systems, advanced manufacturing processes, and interdisciplinary projects. Key projects include systems support engineering for defense industries (funded by DMO), diamond tool manufacturing (Advanced Manufacturing CRC), and supply chain asset tracking (National EPC Network). He has led large-scale international initiatives such as GLOBEMEN under the Intelligent Manufacturing Systems program and ROSDAM software development. Professor Mo's professional roles include Editor-in-Chief of the International Journal of Agile Systems and Management, and Chairman of the Hong Kong Institution of Engineers' Australian Chapter. He has received awards like the CSIRO Divisional Award for innovative research and commendations for industry impact. His research interests span manufacturing engineering, materials science, systems engineering, and risk management. Current projects emphasize digital transformation, predictive maintenance, and transdisciplinary engineering approaches. He supervises PhD/Masters students in advanced machining techniques, risk modeling, and robotics applications. His work bridges academic research with industry needs through strategic partnerships and innovative solutions.

• Applied Mathematics
• Cybersecurity
• Numerical Techniques
• +۶ مورد دیگر

Dr. Geetika Verma is a Lecturer in Mathematics and Cybersecurity at the School of Science, RMIT University STEM College. Her research spans applied and pure mathematics, focusing on numerical techniques, industrial applications of mathematics and statistics, and cybersecurity algorithms such as cryptography. She actively engages in work-integrated learning (WIL) initiatives, coordinating internships and research projects for mathematics, statistics, and cybersecurity courses. Dr. Verma has been recognized with multiple teaching and outreach awards for her industry-linked pedagogical approaches. Her research interests include fractal geometry, functional and harmonic analysis, evolutionary population dynamics, and cybersecurity. She has contributed to over 17 peer-reviewed publications since 2014, addressing topics from fractal convolutions to elliptic curve key generation. Dr. Verma serves on the B H Neumann Prize committee and coordinates the Mathematical Sciences Seminar. She is open to supervising Masters and PhD students in fractal-related research.

• Artificial Intelligence
• Medical Imaging
• Structural Engineering
• +۵ مورد دیگر

Dr. Azadeh Alavi is a Lecturer at RMIT University's School of Computing Technologies in Melbourne, Australia. Her research focuses on interdisciplinary applications of artificial intelligence, particularly in medical imaging, structural engineering, quantum computing, and sustainability. She supervises PhD and master's projects in areas such as AI-driven medical image analysis, digital twin technology for infrastructure monitoring, and psychedelics-inspired therapeutics design. Her work spans diverse domains including healthcare analytics (e.g., diabetic foot ulcer classification, dementia prediction), civil infrastructure monitoring (e.g., bridge integrity assessment, real-time structural health systems), and theoretical AI (e.g., analyzing AI systems against consciousness definitions). Key contributions include developing PRIMITI for miRNA-mRNA interaction prediction and SellaMorph-Net for sella turcica segmentation in cephalometric imaging. Dr. Alavi’s recent publications highlight advancements in multimodal fusion learning for medical imaging, quantum-classical hybrid models for structural monitoring, and AI applications in fashion sustainability. She is an active collaborator in international research networks and maintains an ORCID profile (0000-0002-9565-217X). Her supervision portfolio includes projects on AI ethics, digital twin implementations, and health data mining. She teaches advanced computing modules and advises students on cutting-edge AI methodologies for real-world challenges across engineering and healthcare sectors.