جست‌وجوی استاد و پژوهشگر

• Software Engineering
• Artificial Intelligence
• Biomimetic Systems
• +۳ مورد دیگر

Thuy-linh Nguyen is a Lecturer at the Peter Faber Business School under the Faculty of Law and Business. Her research focuses on interdisciplinary applications of computational and biological systems, particularly in software evolution inspired by biological metaphors. Key areas include biomimetic software development, artificial intelligence, and theoretical computing. Nguyen has contributed to studies on seismic activity in hydropower reservoirs, gene therapy antibody screening, and marine fisheries analysis. Her work spans technical, medical, and environmental domains, often leveraging AI and advanced analytics. Research Interests: Nguyen’s primary interests lie at the intersection of software engineering and biological systems, aiming to create adaptable and evolutionary computational frameworks. She also explores applications in healthcare informatics, environmental modeling, and material science through data-driven approaches. Recent Articles Highlight: Her 2025 study on geomorphic factors influencing seismic activity in hydropower reservoirs exemplifies her focus on environmental risk assessment. Collaborative projects in AI for medical compliance (2024) and biomimetic robotics (2024) showcase her cross-disciplinary engagement. Retracted works indicate rigorous peer review participation. Awards: No scientific awards explicitly listed in the provided text. Nguyen’s contributions are primarily evidenced through publication output. Advising/Grants: No student advisees or grant details are mentioned. Her academic role appears focused on research and teaching.

• Geoinformatics
• Civil Engineering
• Transportation Systems
• +۴ مورد دیگر

Dr. LOVAS Tamás is an Associate Professor and Head of the Department of Photogrammetry and Geoinformatics at the Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). He also serves as a Representative and Coordinator for the Specialization in Construction Information Technology Engineering (MSc) within the Faculty Council. His expertise spans geoinformatics, civil engineering, and transportation systems, with a focus on laser scanning, point cloud integration, and smart infrastructure solutions. Education: While formal education details are not explicitly provided, his academic role and publications suggest a strong background in civil engineering and geomatics. His courses include topics like Intelligent Transport Systems (BMEEOFTMF61), ITS GIS (BMEEOFTMF62), and Laser Scanning (BMEEOFTDT81). Research Interests: Dr. Lovász’s work centers on leveraging geospatial technologies for infrastructure analysis, including urban land cover classification , automated road surface segmentation , and scan-to-BIM workflows . He pioneers applications in transportation safety, autonomous vehicle HD mapping, and disaster risk assessment using RPAS and LiDAR. His team develops AI-driven strategies for point cloud data and digital twins, enhancing infrastructure monitoring and urban planning. Key Achievements: He has been awarded the Magyar Felvételi információ #építő250 ösztöndíj and contributed to projects like the ZalaZONE automotive proving ground’s HD mapping workflow. His research bridges academic innovation with practical engineering solutions, such as optimizing electric vehicle charging station placement and assessing rockfall hazards in volcanic regions. Grants & Advising: His work includes funded projects on laser scanning for bridge load testing and steel section inspection. While specific grant details are not listed, his publications reflect sustained engagement with industry-relevant research. He advises on complex construction IT projects and guides students through MSc specializations in construction information technology. Labs & Teams: His department collaborates with the Vásárhelyi Pál Doctoral School of Civil Engineering and Earth Sciences , focusing on geomatics, geotechnical engineering, and infrastructure systems. His team integrates cutting-edge technologies like LiDAR, photogrammetry, and AI to advance civil engineering practices.

• Bioengineering
• Railway Systems
• Fire Safety
• +۷ مورد دیگر

Dr. Yolanda Ballesteros Iglesias is an Associate Professor at the Institute for Research in Technology (IIT) within the School of Engineering (ICAI) at Universidad Pontificia Comillas. Her research focuses on Bioengineering, Railway Systems, Fire Safety, Thermal and Fluids Engineering, and Energy Economics and Regulation. She also specializes in Materials Science, Environment, Biomaterials, Nondestructive Testing (NDT), and Adhesives. Dr. Ballesteros has held roles such as Honorary Professor at Universidad Autónoma de Madrid and collaborates with the Acoustic and Vibration Group at the Universidad Nacional de Rio Cuarto (Argentina). Her work includes over 35 journal publications, with recent contributions in Results in Engineering , Frontiers in Detector Science and Technology , and International Journal of Adhesion and Adhesives . Key research areas span graphene-modified materials, seismic energy harvesting, and biomedical 3D printing. She has secured grants for projects such as 'Self-sensing implants based on additive manufacturing techniques' (2023–2024) and 'Effect of cold plasma treatment on cell viability of scaffolds' (2024–2026). Dr. Ballesteros has supervised doctoral research, including J. Rodríguez’s thesis on acoustic defect detection in composites. She is a recipient of the SECOT Foundation Prize for Basic Research in Orthopedic Surgery and Traumatology (2016). Her collaborative networks include institutions in Spain, Argentina, the U.S., and India, with active participation in international conferences like IEEE ARGENCON and the World Biomaterials Congress.

Aleksandar Bodićمشاهده پروفایل

پژوهشگر

• Mechanical Engineering
• Structural Analysis
• Numerical Simulations
• +۳ مورد دیگر

Aleksandar Bodić is a Researcher at the Department of Applied Mechanics and Automatic Control, Faculty of Engineering, University of Kragujevac, Serbia. His research focuses on structural analysis, materials science, numerical simulations, and biomedical engineering applications. He holds a position in the Applied Mechanics and Automatic Control department and is affiliated with the university's broader engineering community. His work integrates computational methods like the Finite Element Method (FEM), Smoothed Particle Hydrodynamics (SPH), and Finite Volume Method (FVM) to address challenges in mechanical, civil, and biomedical engineering. Notable areas include piezoelectric nanocomposites, blast-resistant structures, dental material performance, and cardiovascular fluid dynamics. His recent studies emphasize predictive modeling for structural safety, fatigue analysis, and particle dynamics in medical devices. Research interests span advanced materials characterization, structural dynamics under extreme conditions, and computational tools for engineering problem-solving. He collaborates on projects involving interdisciplinary applications, such as improving muzzle brake efficiency for firearms and optimizing drug delivery systems via dry powder inhalers. No academic awards or grants are explicitly mentioned in the provided information. His advisory role and student supervision details are currently unavailable. Affiliated with the Faculty's technical and research infrastructure, his work contributes to the Department for Applied Mechanics and Automatic Control's broader mission in advancing engineering science and technology.

Jinyuan Liuمشاهده پروفایل

استاد

• Geotechnical Engineering
• Urban Tunnelling
• Ground Improvement
• +۶ مورد دیگر

Dr. Jinyuan Liu is a Professor in the Department of Civil Engineering at Toronto Metropolitan University. His research focuses on geotechnical engineering, urban tunnelling, ground improvement, and pile foundations. He holds a PhD from both New York University and Tongji University, with additional degrees from Nanjing Hydraulic Research Institute and Hohai University. His work emphasizes practical applications such as cement stabilization of Champlain Sea clay and AI-driven geotechnical design optimization. Liu operates the GeoOptical Research Lab, where he investigates soil behavior using transparent soil models and advanced imaging techniques. He has contributed to projects like soil nailing for highway construction and deep excavation design in glacial deposits. Liu’s professional activities include roles in the Canadian Geotechnical Society, Deep Foundation Institute, and Tunnelling Association of Canada. He has authored numerous technical reports and journal articles, focusing on pile design methods, soil stabilization, and geotechnical reliability analysis.

• Computational Mechanics
• Stochastic Finite Elements
• Multiscale Modeling
• +۳ مورد دیگر

Professor Chenfeng Li FLSW is Chair in Civil Engineering at Swansea University and Co-Director of the Zienkiewicz Institute for Modelling, Data and AI. An internationally recognized expert in computational engineering, he develops innovative solutions for civil infrastructure, materials science, and energy sectors. Professor Li's research focuses on computational mechanics, uncertainty quantification, and risk assessment. His methods address technical challenges in water-energy-food systems, geotechnical engineering, and manufacturing. Collaborations with industry leaders like ARUP, Costain, and Bauer translate research into practical applications for infrastructure and construction. Key research areas include: Stochastic finite element methods Multiscale modeling of materials Fluid-structure interaction Uncertainty quantification in complex systems Digital reconstruction of microstructures He leads the module 'Design and Analysis for Temporary Works' for MSc Civil Engineering students, providing continuing professional development for industry practitioners. Honors include Fellowship in the Learned Society of Wales. Professor Li serves as Editor-in-Chief of Engineering Computers and contributes to international research networks addressing global infrastructure challenges.

• Structural Engineering
• Structural Reliability Analysis
• Design Optimization
• +۵ مورد دیگر

Mohamed El Amine Ben Seghier is an MSCA Fellow and Part-Time Lecturer at the Department of Built Environment, Oslo Metropolitan University. His research focuses on structural reliability analysis, corrosion modeling, and machine learning applications in civil engineering infrastructure. He explores maintenance optimization for deteriorating structures, including pipelines, bridges, and energy systems, with a particular emphasis on corrosion degradation and predictive frameworks. His work integrates advanced machine learning techniques to address challenges in structural resilience, design optimization, and recycling strategies. He has produced over 90 peer-reviewed publications, with recent contributions focusing on hybrid deep learning models for corrosion prediction, geothermal energy piles, and probabilistic frameworks for infrastructure failure analysis. Key research areas include: Structural reliability and risk assessment Machine learning in civil engineering Material degradation modeling Infrastructure maintenance scheduling Offshore and subsea pipeline integrity His publications demonstrate a strong focus on integrating empirical data with computational models to enhance infrastructure resilience against environmental and operational stresses.

• Mining Engineering
• Environmental Engineering
• Hydrogeology
• +۵ مورد دیگر

Dr Behshad Jodeiri Shokri is a researcher at the Centre for Future Materials at the University of Southern Queensland (UNISQ). With degrees in Mining Engineering (BMineExEng, MMineExEng) from Shahrood University and a PhD from USQ, his work bridges mining and environmental engineering. Research Focus: Acid mine drainage (AMD) prediction, rock bolt systems, machine learning applications in mining, sustainable practices, and groundwater contamination. Recent Work Highlights: Development of empirical-analytical AMD models, numerical simulation of rock bolt mechanics, and data-driven XGBoost/ensemble techniques for mine safety. Collaborations: Projects with BHP Group Limited and ACARP (34018 Carbolt™ prototype). Notable Trends: Interdisciplinary use of machine learning for geotechnical challenges and innovative solutions for mine safety and sustainability. Labs/Teams: Affiliated with the Centre for Future Materials , focusing on research-driven environmental and geotechnical solutions.

Hadi Nourizadehمشاهده پروفایل

پژوهشگر ارشد

• Geotechnical Engineering
• Mining Engineering
• Ground Support Systems
• +۵ مورد دیگر

Dr. Hadi Nourizadeh is a Research Fellow at the University of Southern Queensland (USQ) in the Centre for Future Materials (Research). His work focuses on ground support engineering, specifically advancing rock bolt and cable bolt technologies. He holds a BEng, MEng, and PhD in Mining and Geotechnical Engineering, and previously served as a Lecturer at Sahand University of Technology (2011–2018). Dr. Nourizadeh’s research explores axial/shear transfer mechanisms in reinforcing elements, engineered bonding materials (e.g., cementitious grouts, polyester resins), and sustainable practices in mining. His expertise spans coal/resource mining, geomechanics, and construction materials. He has published over 30 papers in high-impact journals/conferences, with a focus on optimizing grouting systems, predicting load-bearing capacities, and integrating machine learning into geotechnical analysis. Key areas include: Grouting Technology: Developing eco-friendly grouts using waste materials (e.g., fly ash, glass powder). Numerical Modeling: Finite element analysis of bolt behavior under varied geotechnical/thermal conditions. Machine Learning: Applying XGBoost and ensemble methods for predicting grout performance. He leads projects like the ACARP-funded Carbolt™ prototype development and waste utilization in concrete. His work aims to enhance safety, sustainability, and efficiency in mining and construction sectors.

• Spatial Data Infrastructure
• Crowdsourced Data
• Property Rights
• +۴ مورد دیگر

Professor Kevin McDougall is an Honorary Professor at the University of Southern Queensland, affiliated with the School of Surveying and Built Environment under the Civil Engineering and Surveying faculty. His academic career includes roles such as Head of School from 2013 to 2020. He holds a PhD from the University of Melbourne and qualifications in Surveying from Queensland institutions. McDougall specializes in Spatial Data Infrastructure, crowdsourced data analysis, property rights, and mining engineering. His research integrates geotechnical systems, sustainable materials, and machine learning to solve challenges in rock bolt performance, grouting systems, and disaster management. Education: Bachelor of Surveying (BSurv), University of Queensland, 1980 Bachelor of Surveying (Honours) (BSurv(Hons)), University of Queensland, 1983 Master of Surveying and Mapping (MSurv&Map), University of Queensland, 1986 PhD in Geomatics, University of Melbourne, 2007 Research Interests: McDougall’s work bridges geotechnical engineering and sustainable practices, focusing on rock bolt mechanics, grouted systems, and data-driven solutions for infrastructure. He explores the application of digital twins in built environments and the use of crowdsourced data for disaster management. His research also addresses land use policy impacts and erosion modeling in arid regions. Articles Trends: Recent studies emphasize numerical simulations, machine learning for material prediction, and large-scale testing of geotechnical systems. His work on axial load transfer mechanisms and cable bolt performance under varying conditions reflects a focus on enhancing infrastructure resilience. Collaborations span mining waste utilization, environmental impact analysis, and spatial policy evaluation. Advising & Labs: McDougall supervises doctoral research on topics like grout-enhanced concrete, sustainable mining practices, and rock bolt dynamics. He contributes to interdisciplinary teams within the Centre for Applied Climate Sciences, Centre for Agricultural Engineering, and Centre for Future Materials, advancing practical solutions for geotechnical and environmental challenges.

• Cyber Intelligence Analysis
• Cybersecurity
• Data Security
• +۴ مورد دیگر

Dr. Geoffrey Skinner is a Senior Lecturer at the University of Newcastle's School of Information and Physical Sciences, specialising in Data Science and Statistics. He holds a PhD from Curtin University and a Bachelor of Engineering (Computer Engineering) from the University of Newcastle, complemented by a Graduate Certificate in Tertiary Teaching. His research expertise centers on Cyber Intelligence Analysis, with a focus on cybersecurity, data privacy, and eHealth technologies. He has contributed to over 100 publications and led multiple grants, including the SMS4dads initiative addressing mental health support for fathers. His work integrates technical, legal, and social dimensions to address privacy and security challenges in digital ecosystems. Notable projects include developing frameworks for trust management, secure authentication systems, and eHealth applications targeting youth and workforce health. His interdisciplinary approach bridges computer science, education, and healthcare, emphasizing practical solutions for contemporary cybersecurity and data protection challenges. Education: PhD, Curtin University Bachelor of Engineering (Computer Eng)(Honours), University of Newcastle Graduate Certificate Practice of Tertiary Teaching, University of Newcastle Research Interests: Cyber Intelligence Analysis Data Security & Privacy eHealth Innovations Trust and Reputation Management Grants: SMS4RRDads (2021-2025): $3.1M to support rural fathers' mental health. Be Positive Be Healthe: eHealth weight loss program for young women.

• Applied Mathematics
• Nanotechnology
• Granular Materials
• +۳ مورد دیگر

Professor Natalie Thamwattana holds a position at the University of Newcastle's School of Information and Physical Sciences, specializing in Mathematics. She has been recognized with prestigious awards, including the 2014 JH Michell Medal and the University of Wollongong's Emerging Researchers Excellence Award. Her research focuses on applied mathematics, nanotechnology, and granular materials, with notable contributions to carbon nanostructure modeling and electrorheological fluids. Natalie has supervised ten PhD students, many of whom now hold academic and research roles globally. Education: Doctor of Philosophy in Applied Mathematics, University of Wollongong Research Interests: Natalie's work bridges mathematics and interdisciplinary applications, including nanomechanics, mathematical modeling of nanostructures (e.g., carbon nanotubes, graphene), and fluid dynamics. She pioneered studies on granular materials' exact solutions and developed continuum models for molecular interactions. Her contributions extend to environmental applications, such as permeable reactive barriers and dye-sensitized solar cells. Grants & Collaborations: ARC Discovery Project (2017-2019) on electromaterials for energy ARC Linkage Project (2020-2022) on clogging in reactive barriers Collaborations with engineering, computer science, and medical fields Awards & Recognition: Fellow of the Australian Mathematical Society Fellow of the Royal Society of New South Wales Featured in the 'Women of Mathematics' exhibition Labs & Leadership: Natalie directed the Priority Research Centre for Computer-Assisted Research Mathematics and its Applications (CARMA) and co-directed the Mathematics in Industry Study Group (MISG). She is actively involved in promoting gender equity in mathematics through roles in WIMSIG and outreach programs targeting high school students.

Ahmed Abdallaمشاهده پروفایل

استادیار

• Geodesy
• Geoinformatics
• Surveying
• +۶ مورد دیگر

Dr. Ahmed Abdalla is an Assistant Professor in the Department of Civil & Environmental Engineering at Louisiana State University (LSU), affiliated with the Center for Geoinformatics. He holds a PhD in Surveying from the University of Otago, New Zealand, and has held academic positions at institutions in Sudan, Germany, and Sweden. His research focuses on geodesy, geoinformatics, and remote sensing applications in environmental monitoring, with specialties in geoid modeling, land subsidence analysis, and gravity field studies. He has extensive experience in GNSS, InSAR, and satellite gravimetry technologies. Education: PhD in Surveying, University of Otago, New Zealand (2013) MSc in Geodesy and Geoinformatics, Royal Institute of Technology, Sweden (2009) BSc in Surveying Engineering, University of Khartoum, Sudan (2003) Research Interests: Geoid and gravity field modeling Land subsidence monitoring using GNSS/InSAR Remote sensing for environmental applications GIS integration with geophysical datasets His recent work emphasizes coastal Louisiana subsidence analysis, Sudan gravity field development, and machine learning enhancements for geodetic measurements. Over 50 peer-reviewed publications demonstrate his contributions to geospatial science and engineering. Professional Experience: 2018-Present: Assistant Professor, LSU 2014-2018: Assistant Professor, University of Khartoum 2017-2018: Visiting Scientist, Leibniz University of Hanover Labs/Teams: Active member of LSU's Center for Geoinformatics, leading geospatial research initiatives in environmental monitoring and geodetic infrastructure development.

• Information Systems
• Technology Management
• Information Technologies

Assoc. Prof. Dr. Özgür Tolga Pusatlı is affiliated with Çankaya University, Faculty of Engineering, Department of Information Systems. He holds a PhD in Information Systems from the University of Newcastle, Australia, with a thesis on interoperability and information system replacement in the health sector. Bachelor's Degree in Geological Engineering from Middle East Technical University (1997) Master's Degree in School of Design, Communication & IT from University of Newcastle (2003) PhD in Information Systems from University of Newcastle (2009) His research spans Information Systems , Technology Management , and Information Technologies , focusing on machine learning applications in geotechnical engineering and structural safety analysis. Recent work includes computational modeling for slope stability. The 2022 publication in Water (Switzerland) demonstrates his interdisciplinary approach combining data science with civil engineering challenges.

• Structural Engineering
• Structural Control
• Structural Health Monitoring
• +۴ مورد دیگر

Roles & Affiliations: Ian F. C. Smith is a Honorary Professor at EPFL's ENAC School, affiliated with the EESD laboratory. He holds dual Swiss-Canadian citizenship and has been a leading figure in structural engineering and adaptive systems. Education: PhD in Engineering from the University of Cambridge (1982). Research Interests: Focuses on adaptive civil structures, biomimetic systems, structural health monitoring, and advanced computing applications in civil engineering. His work includes developing structures that adapt to loads through shape morphing, improving infrastructure resilience via data-driven methods, and enhancing safety through sensor networks and vibration analysis. Key Contributions: Over 150 publications on structural control, smart materials, and data interpretation. Notable works include frameworks for occupancy detection via floor vibrations, biomimetic adaptive control of tensegrity structures, and optimization of measurement systems for bridge testing. Advising & Labs: Supervised numerous PhD students (e.g., S. Drira, N. Bertola). Leads the EESD lab, exploring earthquake engineering, structural dynamics, and adaptive systems. Collaborates on projects like the Singapore Cyber-Civil-Infrastructure initiative and the biomimetic deployable footbridge system.