جستجوی استاد راهنمای دانشگاهی

Dr. Olga Zinovieva is a Lecturer in Mechanical Engineering and Program Coordinator at UNSW Canberra's School of Engineering and Technology. Her research focuses on computational modeling in metal additive manufacturing, particularly on processing-microstructure-property relationships. She has held research positions at the University of Bremen, Russian Academy of Sciences, and Tomsk Polytechnic University, and visiting roles in Australia, Germany, Brazil, and France. Research Interests: Modeling for additive manufacturing Multiscale methods Computational materials science Computational mechanics Microstructure evolution in 3D printing Mechanical behavior under dynamic loading Recent research trends from her publications emphasize predictive modeling of mechanical properties in additively manufactured metals, microstructure simulation, and digital solutions for advanced manufacturing. Her work integrates ICME approaches and high-performance computing to optimize alloy performance and process parameters. Scientific Awards and Grants: ARC Discovery Early Career Researcher Award (2025–2028) NSW DIN Pilot Project (2024–2025) CSIRO ON Prime Performance Bonus (2024) UNSW Start-up Grant (2022–2024) DFG-RFBR Project (2017–2022) Multiple travel and research grants from RFBR, University of Bremen, and Tomsk State University Supervision and Grants: Dr. Zinovieva actively supervises PhD and undergraduate research students in projects related to additive manufacturing modeling. She has secured over 20 grants as a Chief Investigator, including leadership in international collaborations between Germany and Russia. She mentors students through UNSW’s HDR programs and industry-linked research initiatives. Labs and Teams: She leads computational research in metal additive manufacturing at UNSW Canberra, utilizing high-performance computing resources. She collaborates with international teams at the University of Bremen and participates in editorial and advisory roles for journals such as Metals and Journal of Materials Informatics .

• Additive manufacturing
• Metals and alloys
• Computational mechanics
• +۱۲ مورد دیگر

Professor Matthew Simpson is a leading figure in applied mathematics at the School of Mathematical Sciences, Faculty of Science, Queensland University of Technology (QUT). He holds the position of Professor of Applied Mathematics and is an Australian Research Council (ARC) Future Fellow, reflecting his sustained research excellence. His work bridges mathematical theory and biological applications, particularly in cell migration, tissue invasion, and multiscale modeling. BE (Environmental) Honours 1, University of Newcastle (1995–1998) PhD (with Distinction), Environmental Engineering, University of Western Australia (2000–2003) Research Fellow, Department of Mathematics and Statistics, University of Melbourne (2003–2006) ARC Postdoctoral Fellow, University of Melbourne (2006–2009) Lecturer (2010–2011) and Senior Lecturer (2011–2013), QUT Associate Professor (2013–2014), QUT Professor and ARC Future Fellow (2014–present), QUT Matthew Simpson’s research focuses on mathematical and computational modeling of biological systems , particularly collective cell motion, diffusion processes, and reaction-diffusion dynamics. His interests span multiscale modeling , random walk processes , cell biology , and numerical and computational mathematics . He develops and analyzes models to understand phenomena such as wound healing, cancer progression, and tissue engineering. His recent publications (2023–2025) demonstrate a strong trend toward integrating data-driven modeling , likelihood-based inference , and equation learning with traditional mechanistic models. These works emphasize parameter identifiability , uncertainty quantification , and prediction robustness in biological contexts. Themes include sharp-fronted wave propagation, mechanical cell interactions, tumor spheroid formation, and generalized diffusivity in food drying, showcasing the breadth and depth of his modeling expertise. Among his key accolades are: J.H. Michell Medal (2012) – Awarded by ANZIAM for distinguished research by an early-career applied mathematician in Australia and New Zealand. ARC Future Fellowship (2013–2017) – For the project 'New data-driven mathematical models of collective cell motion' (FT130100148). Professor Simpson has also played significant editorial and leadership roles, including: Executive Associate Editor, Journal of Engineering Mathematics Academic Editor, PLoS ONE Editorial Board Member, ANZIAM Journal Co-chair of the 2015 ANZIAM meeting He has supervised PhD students on topics such as moving boundary problems, first-passage times, stochastic simulations, and curvature-dependent growth in biological systems. His research projects have been funded by competitive Australian grants (ARC DP and FT schemes), including studies on 3D cell migration, ghrelin’s role in cell invasion, and epithelial-to-mesenchymal transition in cancer and wound healing. He is actively involved in developing computational tools for biological modeling and promoting best practices in scientific publishing.

• Applied Mathematics
• Mathematical Modelling
• Computational Modelling
• +۷ مورد دیگر

Dr. Weihao Li is a Research Fellow at The Australian National University's School of Computing, specializing in computer vision and machine learning. His research focuses on object detection, image segmentation, open-set recognition, and point cloud segmentation. He holds a Dr. rer. nat. (PhD equivalent) and is registered to supervise research students. His research interests revolve around advancing techniques for dynamic instance segmentation, open-set learning, and 3D point cloud analysis. Notable projects include the ANU bushfire smoke dataset and contributions to generalized semantic segmentation and anomaly recognition. His work emphasizes data augmentation strategies and weakly-supervised learning methods. Key technical areas include synthetic dynamic instance copy-paste for video segmentation, curved geometric networks for anomaly detection, and cross-modal fusion in building facade analysis. He collaborates on computing-for-social-good initiatives, such as environmental monitoring via hyperspectral imaging. Dr. Li's publications span 2016–2024, with a focus on advancing computer vision through innovative architectures and methodologies. His recent work explores open-set recognition, few-shot learning with reinforced attention, and geometric prior-based segmentation techniques.

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

Christoph Schrank is an Associate Professor at QUT's School of Earth and Atmospheric Sciences, specializing in structural geology and rock physics. His research combines field studies with synchrotron-based experimental techniques to investigate deformation processes in tectonic settings. Research focuses on: Synchrotron analysis of rock deformation Tectonic modeling of fault systems Geothermal energy applications Pattern formation in porous media Publication analysis shows emphasis on experimental rock physics (40%), microstructural analysis (30%), and Precambrian tectonics (20%). His work frequently integrates advanced imaging techniques with mechanical modeling. Funded projects include ARC DP170104550 (pressure waves in earthquake mechanics) and DP140103015 (finite strain modeling). Coordinates Honours program for Earth Science and teaches structural geology field methods.

• Structural Geology
• Rock Physics
• Tectonic Modeling
• +۴ مورد دیگر

Dr. Nicolas Francois is an Associate Professor in the Department of Materials Physics at Australian National University (ANU), specializing in experimental geomaterials physics, soft matter, and fluid hydrodynamics. He leads the X-ray Tomography and Applications Research Group, combining curiosity-driven and applied research in out-of-equilibrium systems. ARC Industry Fellow (2024-2030): Improving Australian iron ore comminution for green steel production ARC DECRA Fellow (2016-2018): Biofilms in two-dimensional turbulent flows His research spans fundamental questions in: Fragmentation of solid materials Autonomous devices powered by chaotic flows Hydrodynamic waves Stochastic thermodynamics Granular matter Polymer rheology and applied areas in: Comminution of geomaterials Mechanics of fractured rocks Wave-energy conversion Environmental fluid mechanics Publications reveal a trajectory focused on X-ray tomography applications, granular dynamics, and turbulence-driven systems. He utilizes advanced imaging techniques to study material failure mechanisms and fluid-structure interactions, contributing to fields ranging from green steel production to biofilm dynamics. Current student projects and grants emphasize sustainable resource processing and fundamental fluid physics.

• Geomaterials Physics
• Soft Matter
• Structured Materials
• +۱۳ مورد دیگر

Zia Javanbakht is a Senior Lecturer at the School of Engineering and Built Environment , Griffith University , specializing in Mechanical Engineering and Industrial Design . As a chartered engineer with a PhD in Mechanical Engineering, he contributes to research in Continuum Mechanics , Material Modelling (composites and metamaterials), and Computational Modelling . He is affiliated with the Australian Centre for Precision Health and Technology (PRECISE) and has been involved in projects related to additive manufacturing, auxetic materials, and composite structures. Research Interests include the development of advanced computational models for material behavior, with a focus on auxetic structures , triply periodic minimal surfaces (TPMS) , and additively manufactured composites . His work addresses challenges in residual stress analysis , multiscale modelling , and machine learning applications in material deformation mechanisms. Scientific Awards Fellow (FHEA) of Higher Education Authority, Dublin, Ireland (since 2021) Key Funded Projects span collaborations with Gilmour Space Technologies (CRC-P grant for rocket fuel tanks), Bond University (concrete sensor testing), and internal Griffith University grants for equipment like the Transient Plane Source Thermal Conductivity Analyser . He actively supervises PhD and Master’s students in topics such as polymer-matrix composites , auxetic timber structures , and additive manufacturing failure models . Collaboration Networks include the AuxeticsLab and partnerships with industry leaders like Stoddart Group Pty Ltd and ATL Composites . His teaching portfolio covers Constitutive Material Modelling (7015ENG) and Computational Statics and Dynamics (7252ENG), reflecting his expertise in computational techniques and structural analysis.

• Continuum Mechanics
• Material Modelling (Composites and metamaterials)
• Computational Modelling
• +۶ مورد دیگر

Professor Hailiang Yu is an Honorary Fellow at the University of Wollongong's School of Mechanical, Materials, Mechatronic and Biomedical Engineering. His research focuses on engineering materials, manufacturing processes, and mechanical engineering, with over 100 journal/conference publications and 30 science-focused newspaper commentaries. He serves as co-Editor-in-Chief of Modeling and Numerical Simulation of Material Science , and holds editorial roles in Scientific Reports and International Research Journal of Engineering Science, Technology and Innovation . Yu has secured significant funding through grants such as the Australian Research Council's 'Large-volume gradient materials' project (2017–2020) and 'A Physical-based abrasive wear model' (2013–2016). His work emphasizes cryorolling, microstructure optimization, and advanced material fabrication techniques. He currently supervises Master's and PhD students in materials engineering and manufacturing innovation. Key research themes include cryogenically processed alloys, bimetallic clad sheets, and high-entropy composites. His publications in journals like Metallurgical and Materials Transactions A and Journal of Materials Processing Technology reflect expertise in structural optimization, tribology, and corrosion resistance. Yu aims to become an international leader in materials manufacturing and mechanical engineering.

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

Dr Daniel Harris is a Senior Lecturer in the Department of Geography at the School of the Environment, University of Queensland (UQ). His research focuses on coastal and coral reef morphodynamics, integrating physical processes like waves and tides with ecological and geological systems. Prior to UQ, he held positions at the University of Sydney and the Leibniz Center for Tropical Marine Ecology (ZMT). He leads The BeachLab, dedicated to developing tools for coastal resilience in a warming world. Research interests include coral reef structural complexity, coastal protection under climate change, and surf zone processes. His work combines field data, remote sensing (e.g., LiDAR, drones), and numerical modeling to address both fundamental and applied questions. Notable projects involve quantifying coral rubble mobility, analyzing Holocene reef evolution, and assessing shoreline change via satellite imagery. His expertise spans marine geoscience, physical oceanography, and environmental adaptation strategies. Publications emphasize coral reef dynamics, coastal geomorphology, and climate impacts. He collaborates with ecologists, geologists, and coastal engineers to advance interdisciplinary solutions. Teaching focuses on geography and marine science, reflecting his commitment to educating future researchers and practitioners. Key contributions include advancing methods for shoreline monitoring using Bayesian networks and Google Earth Engine. His research highlights the critical role of coral reefs in coastal protection, particularly under rising sea levels and extreme weather events. The BeachLab’s work bridges academic inquiry with practical management strategies for vulnerable coastal ecosystems.

• Climate Change Impacts
• Coastal Morphodynamics
• Coral Reef Geomorphology
• +۳ مورد دیگر

Professor Michael Breakspear is an internationally recognized leader in computational neuroscience, brain imaging, and translational neurotechnology at the University of Newcastle's School of Psychological Sciences. His research bridges complex systems theory, mathematical modeling, and clinical neuroscience to advance understanding of brain dynamics in health and disease through interdisciplinary collaboration across mathematics, physics, neuroimaging, psychiatry, and artificial intelligence. Professor Breakspear holds a Doctor of Philosophy from the University of Sydney, along with multiple undergraduate degrees including a Bachelor of Medicine and Bachelor of Surgery. His academic journey includes professorial appointments at the University of Sydney (School of Physics), University of Queensland (School of Psychiatry), and University of Western Sydney (School of Psychiatry), where he progressed from Post-doctoral Research Fellow to Associate Professor. Current: Professor, University of Newcastle, School of Psychological Sciences 2017-present: Principal Research Fellow, National Health & Medical Research Council 2017-present: Senior Scientist and Head, QIMR Berghofer Medical Research Institute 2012-2017: Professor (adjunct), University of Sydney, School of Physics 2011-present: Professor (adjunct), University of Queensland, School of Psychiatry 2007-2012: Associate Professor, University of Western Sydney, School of Psychiatry Professor Breakspear's research program integrates expertise across mathematics, physics, neuroimaging, psychiatry, and artificial intelligence. His core expertise includes computational neuroscience (modeling brain dynamics using nonlinear systems theory), neuroimaging and connectomics (pioneering methods to analyze brain networks), brain disorders and mental health (applying computational models to disorders like schizophrenia and bipolar disorder), and neurotechnology and AI (developing machine learning techniques for imaging biomarkers). His recent publications demonstrate a strong focus on brain dynamics, neuroimaging techniques, and applications to psychiatric and neurological disorders. His work spans theoretical frameworks to clinical applications, with particular emphasis on understanding the neural basis of mood disorders, Alzheimer's disease, and psychosis, employing advanced computational approaches to uncover fundamental principles of brain organization and dysfunction. Senior Researcher Award (2017) Principal Research Fellow, National Health & Medical Research Council (2017-present) Professor Breakspear actively collaborates with clinical researchers, engineers, and technology developers to translate theoretical frameworks into practical diagnostic and therapeutic innovations. He provides leadership in training programs at the nexus of neuroscience, mathematics, and data science, fostering the next generation of interdisciplinary researchers through mentorship and collaborative projects that bridge theoretical and clinical domains.

• Computational Neuroscience
• Neuroimaging
• Connectomics
• +۱۰ مورد دیگر

Professor Georg Gottwald is a distinguished academic in the School of Mathematics and Statistics at the University of Sydney, where he has been a faculty member since 2002, progressing from Lecturer to his current position as Professor since 2013. He also holds a Visiting Professor position at the University of Surrey in the UK since 2013. His extensive research career spans dynamical systems theory, geophysical fluid dynamics, and the intersection of machine learning with complex systems. Professor Gottwald's research focuses on dynamical systems theory as an abstract formalism for studying systems evolving in time and space. His work has significant applications across diverse fields including climate modeling, biological systems, and complex networks. He is particularly known for developing methods for model reduction of complex dynamical systems, stochastic modeling approaches, and the application of machine learning techniques to dynamical systems. His research aligns with the Faculty of Science Research Strengths in Understanding the Universe, Fundamental Laws of Nature, Complex Systems, Climate and Environmental Change, Data and Decisions, and National Security. His most recent publications demonstrate a strong trajectory toward integrating machine learning with dynamical systems theory, particularly in developing stable generative models, learning dynamical systems with random feature maps, and combining data assimilation with machine learning for forecasting. His work spans pure mathematical theory to practical applications in climate science, finance, and biological systems, showing remarkable breadth while maintaining deep mathematical rigor. Future Fellowship, 'Stochastic methods in mathematical geophysical fluid dynamics', Australian Research Council, 2010-2014 Australian Research Fellowship, 'Stochastic methods in mathematical geophysical fluid dynamics', Australian Research Council, 2010-2015 (declined) Australian Research Fellowship, 'Geometric methods in geophysical fluid dynamics', Australian Research Council, 2004-2009 Professor Gottwald has successfully supervised numerous PhD and Master's students who have gone on to academic and industry positions worldwide. His current research group includes postdocs and PhD students working on machine learning for dynamical systems, stochastic model reduction, physics-informed machine intelligence, and tensor methods for scientific machine learning. He has secured multiple ARC Discovery Project grants and has been involved in significant international collaborative research projects. He is actively involved with the Sydney Dynamics Group, which he co-founded in 2007, fostering collaboration between the University of Sydney and UNSW. Professor Gottwald maintains strong editorial commitments as Associate Editor for Geophysical and Astrophysical Fluid Dynamics, SIAM Journal of Applied Dynamical Systems, and Journal of Computational Dynamics, and serves on the Editorial Advisory Board for Chaos and the Editorial Board for Physical Review E. His professional activities demonstrate leadership in the dynamical systems community through organizing workshops, seminars, and special journal issues.

• Dynamical Systems
• Geophysical Fluid Dynamics
• Climate Modeling
• +۵ مورد دیگر

Dr. Amar Khennane serves as a Senior Lecturer at the University of New South Wales (UNSW) Canberra campus within the School of Engineering and Information Technology. His academic career spans multiple institutions including previous appointments as Maitre de Conferences in Tizi-Ouzou, Algeria, Research Associate in Newcastle, Australia, and Lecturer/Senior Lecturer at the University of Southern Queensland (USQ). His research interests focus on sustainable construction materials, particularly bio-cementitious materials, composite materials, timber engineering, reinforced concrete, and hybrid structures. Dr. Khennane has published extensively in these fields with 47 peer-reviewed journal papers, 33 conference papers, 6 other publications, and 2 books including the widely recognized "Introduction to Finite Element Analysis Using MATLAB (R) and Abaqus" (2013). His recent work emphasizes recycling timber waste into geopolymer cement composites, sustainable wood-geopolymer masonry units, and fire response of timber structures. His scholarly output shows a clear trend toward sustainable construction materials and advanced structural analysis techniques, with significant contributions in finite element modeling, seismic performance evaluation, and fire resistance of composite structures. The majority of his recent publications (2020-2024) focus on developing sustainable building materials using recycled components and analyzing structural behavior under various loading conditions. Dr. Khennane actively contributes to engineering education through teaching courses in Structural Analysis, Finite Element Method, Reinforced Concrete, and Stress/Strain Analysis. His educational background includes authoring textbooks that bridge theoretical concepts with practical computational tools like MATLAB and Abaqus.

• Bio-Cementitious materials
• Composite materials
• Timber engineering
• +۵ مورد دیگر

Aleksandr Zinoviev is a Senior Research Associate at the School of Engineering and Information Technology (SEIT) at UNSW Canberra, where he has been working since 2022. His research spans multiple institutions across the globe, including previous positions at Siemens Digital Industries Software in Belgium, University of Bremen and AMSIS GmbH in Germany, and Institute of Strength Physics and Materials Science of the Russian Academy of Sciences and Tomsk Polytechnic University in Russia. He has also conducted research stays at the University of Bremen (Germany) and São Paulo State University (Brazil). Dr. Zinoviev's research interests are highly interdisciplinary, focusing on metal additive manufacturing, thermodynamics of materials, computational materials science, solid mechanics, software engineering, and machine learning. He specializes in developing and applying novel knowledge-based approaches to address engineering challenges, particularly in improving materials and parts produced by advanced manufacturing, optimizing production processes, and enhancing data processing. His work bridges the gap between fundamental materials science and practical engineering applications, with a strong emphasis on computational modeling and simulation. Analysis of his recent publications (2021-2025) reveals a consistent focus on additive manufacturing process modeling, microstructure-property relationships in additively manufactured metals, and computational approaches to materials science. His research particularly emphasizes cellular automata modeling, multiscale simulation techniques, and the application of machine learning to materials processing. The publications demonstrate expertise in both experimental characterization and advanced computational methods for predicting mechanical behavior of additively manufactured components. Dr. Zinoviev actively mentors prospective PhD and Research Master's candidates, offering guidance on topics related to thermal modeling of additive manufacturing and process optimization. He has indicated that scholarships of up to $35,000 (AUD) are available for qualified candidates who achieved High Distinction in their undergraduate program and/or have completed a Masters by Research.

• Additive manufacturing
• Metal 3D printing
• Materials science
• +۶ مورد دیگر

Dr. Shaoyu Zhao is a Research Fellow (Level A) at RMIT University's School of Engineering. His research focuses on advanced composite structures, mechanical metamaterials, graphene nanocomposites, and molecular dynamics simulations. He holds an ARC DECRA Fellowship and has over 40 journal publications with 2000+ citations (h-index 26). Awards include the ICES2024 Best Paper Award and 2025 DECRA. He supervises Masters/PhD students in areas like metaconcrete and functionally graded structures. Editorial roles include Early Career Board Member for Engineering Structures (Q1), International Journal of Structural Integrity (Q1), and others. Teaching includes the course MIET1076 - Mechanical Vibrations. His work bridges nanoscale simulations (e.g., graphene interfaces) with macro-scale engineering applications (e.g., 3D-printed composites and metamaterial energy absorption). Research spans multi-physics phenomena in perovskite materials and machine learning-driven material analysis. Key Projects: Metaconcrete composites, origami metamaterials, graphene-reinforced nanocomposites Lab Focus: Multiscale modeling for aerospace composites and smart materials

• Advanced composite structures
• Mechanical metamaterials
• Graphene nanocomposites
• +۳ مورد دیگر

Ann Maharaj is an Adjunct Associate Professor in the Department of Econometrics and Business Statistics at Monash University's Caulfield Campus, within the Faculty of Business and Economics. She is an active researcher and educator with expertise in statistical computing and time series analysis. Department: Econometrics and Business Statistics Role: Adjunct Associate Professor Institution: Monash University Campus: Caulfield Her research focuses on advanced statistical methodologies, particularly in time series classification , wavelet analysis , fuzzy classification , and interval time series analysis . These methods are applied in diverse domains such as finance, environmental science, climatology, and human mobility. She has co-authored a book on time series clustering and classification and has published extensively in top-tier journals. The recent trend in her publications (2020–2024) shows a strong emphasis on clustering and classification of complex time series data using wavelet, cepstral, and fuzzy techniques. Her work integrates statistical theory with practical applications, particularly in financial and environmental datasets, contributing to sustainable development goals through data-driven insights. She has received recognition for her teaching excellence: Monash Business School Award for Teaching Excellence (2017) Ann Maharaj is actively involved in academic service and professional communities. She has supervised research students and contributed to statistical consulting and workshops. Her professional affiliations include: Elected member of the International Statistical Institute (ISI) Member of the International Association of Statistical Computing (IASC), serving on its Council (2013–2017) and Executive (2015–2017) Accredited statistician with the Statistical Society of Australia (SSA) Former Secretary and Academic Vice-President of the Monash Branch of the NTEU (2000–2014) She led a research project funded by the Collier Charitable Fund in 2005 on computational infrastructure, indicating early engagement with data-intensive research. Her ongoing scholarly output demonstrates sustained research activity and collaboration with international scholars in statistics and data science. She is associated with research groups and networks focused on statistical computing and time series analysis, contributing to both methodological advancement and real-world application through interdisciplinary collaboration.

• Time Series Classification
• Wavelet Analysis
• Fuzzy Classification
• +۹ مورد دیگر

Ali Karrech is a Professor at the University of Western Australia (UWA), affiliated with the School of Engineering and the Department of Civil, Environmental and Mining Engineering (CEME). He previously held roles as Senior Research Scientist at CSIRO (until 2012) and Assistant Professor at the Petroleum Institute of Abu Dhabi (2007–2009). His expertise spans materials science, geomechanics, mineral processing, and sustainable resource engineering. He serves as Graduate Research Coordinator in CEME and has led the Structures Laboratory (2015–2016). Education: He holds a Higher Doctorate (Habilitation) in Engineering Sciences from École Normale Supérieure Paris-Saclay (2014), a PhD in Structures and Materials from École des Ponts ParisTech (2008), and a Multidisciplinary Master's from Tunisia Polytechnic School (2001). Research Interests: Focus on computational geomechanics, resource engineering (surface mining, in-situ leaching), mineral processing (hydrometallurgy), waste repurposing, and thermal-hydraulic-mechanical-chemical coupling. His work aligns with UN Sustainable Development Goals related to education, energy, and the built environment. Awards: Recognitions include the School of Engineering Teaching Excellence Award (2021), Prize of Best Paper in Concrete Research (2021), and CEEC High Commendations (2023). His research has produced over 194 publications and 20 grants. Teaching: Coordinates units like Engineering Materials (ENSC1004), Finite Element Method (GENG5514), and Surface Mining (MINE4503). Engages in interdisciplinary projects, including the ARC Training Centre in Critical Resources and the FBI-CRC for Future Batteries.

• Materials Science
• Finite Element Analysis
• Mineral Processing
• +۷ مورد دیگر