جست‌وجوی استاد و پژوهشگر

Paruyr Sergey Efendyanمشاهده پروفایل

استاد

• Geodesy
• Land Construction
• Cadastre

Paruyr Sergey Efendyan serves as Professor in the Department of Cartography and Geomorphology at Yerevan State University's Faculty of Geography and Geology since 2020, with prior institutional memberships at YSU (2021-2023) and Armenian National Agrarian University (2009-2023). His academic foundation includes a Certified Specialist degree in Urban Construction from Kiev Engineering and Construction Institute (1969-1974) and postgraduate studies in Applied Geodesy at Moscow Institute of Geodesy and Cartography (1982-1987), culminating in a 2016 Doctor of Science degree from Armenian National Agrarian University for research on Armenia's unified land information system. Professor Efendyan's research centers on Geodesy, Land Construction, and Cadastre, addressing critical challenges in spatial data infrastructure, land valuation methodologies, and geodetic applications for earthquake monitoring and agricultural land management. His work bridges historical land survey practices with modern technological solutions. His 2022-2025 publications reveal strong thematic cohesion around national spatial data infrastructure development, with recurring emphasis on AI integration, legal frameworks, cadastral revaluation, and satellite-based topographic mapping. Key trends include Python-based quality control systems for road data and anthropogenic impact analysis on soil composition. He actively participates in international forums including Geoforum-2023 (Ukraine), Environmental Protection conferences (Russia, 2022), and Land Management summits (Kyrgyzstan, 2021), demonstrating global engagement despite no explicitly listed scientific awards. Professor Efendyan advises students and manages research grants focused on Armenia's spatial data infrastructure modernization, particularly through Python-based quality control frameworks for road network datasets, though specific grant details remain unlisted in available materials.

• Structural Health Monitoring (SHM)
• Earthquake Engineering
• Smartphone Sensor Technologies
• +۵ مورد دیگر

Dr. Ekin Ozer is an Assistant Professor at University College Dublin's School of Civil Engineering. His research focuses on vibration-based structural health monitoring (SHM), earthquake engineering, and mobile sensor technologies. He holds a PhD from Columbia University (2016) and has prior experience in academia (Middle East Technical University) and industry (Novum Structures). His work emphasizes smartphone and participatory sensing for bridge and building monitoring, with contributions to Bayesian risk assessment and machine learning applications. Education: BSc/MSc in Civil Engineering from Bogazici University, MPhil/PhD from Columbia University. Grants include the FLAME project (UCD SATLE) for 3D learning tools and transnational university initiatives. Key research trends in his articles include smartphone-driven SHM innovations, seismic risk assessment frameworks, and integration of cyber-physical systems for infrastructure resilience. He actively supervises PhD students and teaches modules like Structural Analysis, Bridge Engineering, and Case Studies in Infrastructure Design.

Farahnaz Soleimaniمشاهده پروفایل

استادیار

• Structural Engineering
• Seismic Analysis
• Multi-Hazard Resilience Assessment
• +۴ مورد دیگر

Farahnaz Soleimani is an Assistant Professor in the Department of Civil and Construction Engineering at Oregon State University, part of the College of Engineering. Her research focuses on multi-hazard resilience assessment of infrastructure systems, leveraging machine learning and physics-based models for seismic performance evaluation and risk mitigation. She develops computational tools for predictive modeling and sensitivity analysis in structural systems. Education: Ph.D., Civil/Structural Engineering, Georgia Institute of Technology, 2017 M.Sc., Civil Engineering, Georgia Institute of Technology, 2015 M.Eng., Civil Engineering, Tufts University, 2012 B.Sc., Civil Engineering, Sharif University of Technology, 2009 Her research interests include probabilistic modeling, structural dynamics, earthquake engineering, and applications of reliability theory and risk assessment. She also collaborates on interdisciplinary projects at the intersection of data science and STEM education to improve educational practices and diversity. Teaching focuses on structural engineering fundamentals (e.g., statics, dynamics) and applied mathematics/statistics, as well as specialized topics like finite element methods and bridge engineering. No specific labs or teams are listed, but her work emphasizes collaborative, data-driven approaches to civil engineering challenges.

Luca Spalazziمشاهده پروفایل

دانشیار

• Computer Science
• Cybersecurity
• Blockchain Technology
• +۵ مورد دیگر

Luca Spalazzi is an Associate Professor at the Department of Information Engineering , Università Politecnica delle Marche , Italy. His research spans multiple domains including cybersecurity , blockchain technology , machine learning , and telerehabilitation systems for Parkinson's disease. He applies formal methods to software verification and security analysis, with a focus on real-time systems and distributed architectures . Key research areas: Cybersecurity, Blockchain, Machine Learning, IoT, Formal Verification Recent work: Blockchain-based sustainable supply chains, Zero-Knowledge Proofs, Smartphone health monitoring His publications (2013-2025) demonstrate expertise in malware detection , smart contract verification , and AI-driven health solutions . Articles include BRAIN 2024 workshop organization and RAPIDO system for Parkinson's telerehabilitation.

Lauren Lindermanمشاهده پروفایل

دانشیار

• Cyber-Physical Systems
• Structural Control
• Wireless Sensor Systems
• +۳ مورد دیگر

Lauren Linderman is an Associate Professor at the Department of Civil, Environmental, and Geo- Engineering within the University of Minnesota's College of Science and Engineering. She serves as the Director of the Multi-Axial Subassembledge Testing (MAST) Laboratory, focusing on cyber-physical systems to enhance structural performance under dynamic loads like earthquakes and wind. Ph.D. in Civil Engineering, University of Illinois at Urbana-Champaign, 2013 M.S. in Civil Engineering, University of Illinois at Urbana-Champaign, 2009 B.S. in Civil Engineering, Washington University in St. Louis, 2007 Her research emphasizes vibration mitigation strategies, decentralized control, wireless sensor systems, and data acquisition techniques. Current projects leverage wireless smart sensors for real-time structural control and health monitoring, enabling multitasking networks that integrate control and diagnostics. Recent publications highlight advancements in wind engineering, structural monitoring, and wireless sensor networks. Key topics include aerodynamic design for highway structures, polymer-based sensing technologies, and robust control frameworks for seismic resilience. While no specific awards are listed, her work is widely disseminated through journals and conferences. Linderman's group actively advises both undergraduate and graduate students, with alumni contributing to structural dynamics and sensor development. The MAST Laboratory collaborates with experts in civil engineering, materials science, and computational systems.

Rafiq Ahmadمشاهده پروفایل

دانشیار

• Design and Manufacturing
• Additive Manufacturing
• Sustainable Production
• +۷ مورد دیگر

Dr. Rafiq Ahmad (PhD, P.Eng) is an Associate Professor at the University of Alberta’s Faculty of Engineering, Department of Mechanical Engineering. He directs the Smart & Sustainable Manufacturing Systems Laboratory (SMART LAB) and the Aquaponics 4.0 Learning Factory (AllFactory) . His work bridges fundamental research in design and manufacturing with advanced industrial applications. Education : PhD & MSc from French institutions (Ecole Centrale de Nantes and Ecole Arts et Metiers Paris), Postdoc at University of Luxembourg Research : Focuses on Smart Manufacturing (zero-defect production), Green Technologies (3R systems), Industrial Robotics (autonomous systems), and Sustainable Production (Aquaponics 4.0). The 15 most recent publications (2025) explore digital twins, robotics for extreme environments, hybrid manufacturing optimization, and sustainable food production. Articles span additive manufacturing, topology optimization, and AI-driven automation. Scientific Awards : 2023 ASTech Award for Digital Innovation; 2022 Edify Top 40 Under 40; multiple NSERC, Mitacs, and Alberta Innovates grants. Teaching : Offers courses in Manufacturing Systems, Lean Manufacturing, and Mechanical Measurements. Labs : SMART Lab (founded 2016) specializes in hybrid manufacturing and robotics; AllFactory focuses on sustainable aquaponics systems.

• Geochemistry
• Geofluids
• Continental Tectonics
• +۴ مورد دیگر

Dennis L. Newell is a Professor & Interim Department Head in the Department of Geosciences at Utah State University . His research focuses on aqueous and stable isotope geochemistry, fluid-rock-biosphere interactions, and geofluids in continental tectonics. He has extensive expertise in low-temperature geochemistry, geothermal energy exploration, and geologic carbon sequestration, integrating interdisciplinary approaches to study crustal fluid systems. Education: PhD in Earth and Planetary Sciences, University of New Mexico, 2007 MS in Geology, Colorado State University, 1997 BS in Geology, New Mexico Institute of Mining and Technology, 1992 Research Interests: Dr. Newell's group investigates fluid flow in faults, mantle-to-surface volatile flux, and geothermal potential. They employ field-based geochemical tools, including stable isotopes and He isotopes, to address applied problems like carbon sequestration and geothermal energy. Key themes include fluid provenance, crustal hydrology, and tectonic influences on fluid circulation. Grants & Advising: Mentored numerous graduate students in geosciences, including Coleman Hiett, Heather Upin, and Jace Koger. Contributed to the Geothermal Play Fairway Analysis in Idaho and Peru, with fieldwork in the Andes and Alaska. Developed methods for tracing CO2 leakage in aquifers and evaluating fault zone fluid pathways. Labs & Teams: Maintains the Stable Isotope Lab at USU, supporting research in fluid-rock interactions and geochemical analysis.

• Structural Engineering
• Civil Engineering
• Structural Health Monitoring (SHM)
• +۴ مورد دیگر

Prof. Carlo RAINIERI is an academic researcher affiliated with the Department of Bioscienze e Territorio at the University of Molise, Italy. His work focuses on structural health monitoring (SHM), vibration-based diagnostics, and the dynamic characterization of civil infrastructure. He has pioneered methodologies for environmental compensation in modal analysis, automation of operational modal analysis (OMA), and integration of remote sensing technologies for infrastructure assessment. RAINIERI's research spans bridge monitoring, historical structure preservation, and hospital facility resilience. Key contributions include development of kernel PCA-based environmental effect compensation, hybrid OMA algorithms, and SHM systems validated via shaking table tests. His recent work emphasizes practical clustering approaches for anomaly detection, smart healthcare facility design through vibration monitoring, and cyber-physical systems for infrastructure management. He has collaborated on projects involving UNESCO heritage sites like the Trisulti Charterhouse and the Santa Maria Maddalena church. His experimental studies include investigations on masonry structures' seismic vulnerability, cement paste behavior under storage conditions, and liquid storage tank dynamics. RAINIERI has also contributed to advancing digital twin technologies for historical buildings through BIM-FEM integration. Over 150 published articles demonstrate his expertise in modal parameter monitoring, damage detection algorithms, and probabilistic assessment techniques. His work bridges theoretical advancements with industrial applications, providing actionable insights for infrastructure maintenance and disaster resilience strategies.

Carlos Molina Huttمشاهده پروفایل

دانشیار

• Earthquake Engineering
• Structural Engineering
• Seismic Resilience
• +۳ مورد دیگر

Dr. Carlos Molina Hutt is an Associate Professor in the Department of Civil Engineering at the University of British Columbia (UBC), specializing in Structural & Earthquake Engineering. He leads the Engineering for Seismic Resilience Laboratory (ESR Lab), focusing on assessing seismic risk in buildings and translating this knowledge into tools for engineers, planners, and policymakers. His work emphasizes societal and economic impacts of earthquake resilience in urban environments. Carlos holds a PhD in Earthquake Engineering from University College London (UCL), an MSc from Stanford University, and a BSc from Villanova University. He is a registered Professional Engineer (PE) in California, a Chartered Engineer (CEng) in the UK, and has extensive industry experience with firms like Arup and consulting for the UN and EU. His research is funded by NSERC, NSF, and international organizations. Research interests include seismic resilience, performance-based design, risk analysis, and high-rise building systems. He teaches courses on structural design and seismic engineering at UBC. Notable awards include the EERI Shah Family Innovation Prize (2019) and UCL’s Global Engagement Award (2015). His collaborations span academia, industry, and cities like San Francisco and Vancouver. Recent work examines seismic risk in sedimentary basins, collapse risk of tall buildings, and post-earthquake recovery modeling. The ESR Lab develops tools to bridge engineering science and policy for resilient urban systems. Key achievements include deploying as a technical expert post-earthquakes in Ecuador (2016) and Mexico (2017), and publishing over 50 peer-reviewed articles. Current projects focus on machine learning for seismic risk assessments and integrating basin amplification factors into hazard models.

Catalina González-Dueñasمشاهده پروفایل

استادیار

• Risk and resilience assessment of infrastructure systems
• Applied Artificial Intelligence and Machine Learning for civil infrastructure
• Cascading effects in complex systems under extreme events
• +۲ مورد دیگر

Catalina González-Dueñas serves as an Assistant Professor in the Sid and Reva Dewberry Department of Civil, Environmental, and Infrastructure Engineering at George Mason University's Fairfax campus. Her research program focuses on enhancing infrastructure and community resilience against hurricanes, flooding, and extreme winds through probabilistic methods and artificial intelligence, emphasizing dynamic interactions among built, natural, and social systems. Her academic credentials include: PhD in Civil Engineering from Rice University MS in Civil Engineering from Universidad de los Andes BS in Civil Engineering from Universidad de los Andes Dr. González-Dueñas' research spans risk and resilience assessment of infrastructure systems, applied AI for civil engineering, and cascading effects in complex systems under extreme events. Her work integrates structural engineering with probabilistic hazard analysis to develop performance-based assessment frameworks for built-natural systems under multi-hazard conditions, with increasing attention to social vulnerabilities and risk communication. Analysis of her 14 publications (2018-2023) reveals consistent innovation in multi-hazard risk frameworks, particularly through data-driven hurricane debris modeling and knowledge-informed systems for coupled human-built-natural interactions. Her research trajectory shows growing integration of time-varying social factors and AI methodologies to address coastal community resilience and infrastructure performance under climate change. While the source text references her research group, specific operational details were not provided. No information regarding student advising, grant funding, or scientific awards was included in the available materials.

Wei Zhanمشاهده پروفایل

استاد

• Control Systems
• Systems Engineering
• Nonlinear Control
• +۷ مورد دیگر

Wei Zhan is a Professor and Associate Department Head for Undergraduate Studies in the Department of Engineering Technology & Industrial Distribution at Texas A&M University's College of Engineering. He holds affiliations with the Multidisciplinary Engineering program, focusing on systems engineering, control systems, and renewable energy applications. His academic career includes leadership roles in curriculum development and student recruitment strategies. Dr. Zhan earned a D.Sc. in Systems Science from Washington University (1991), M.S. degrees in Systems Engineering (Washington University, 1988) and Control Engineering (Beijing University of Aeronautics and Astronautics, 1985), and a B.S. in Electrical Engineering (Beijing University of Aeronautics and Astronautics, 1983). His research spans nonlinear control systems , industrial process optimization , and educational innovation . Key areas include fault-tolerant motor control, renewable energy transition frameworks, and maker culture integration into engineering education. Recent publications emphasize energy systems decarbonization, robotics, and pedagogical advancements like capstone project integration. His work bridges academic research with real-world applications such as smart grid reliability, autonomous inspection drones, and lean six sigma methodologies. Dr. Zhan leads initiatives in program development, including the Product Innovation Cellar for student product development and multidisciplinary engineering education. His efforts in curriculum design and student recruitment reflect a commitment to addressing evolving industry needs.

Nimisha Royمشاهده پروفایل

مدرس

• Artificial Intelligence in Education
• Infrastructure Resilience
• Generative AI
• +۳ مورد دیگر

Nimisha Roy is a Lecturer in the School of Computing Instruction (SCI) at Georgia Tech's College of Computing, teaching undergraduate and graduate courses in Computer Science, including Software Engineering, Machine Learning, and the CS Capstone. She also instructs in the Online Master of Science in Analytics (OMSA) program. Her research focuses on AI-driven pedagogical innovation, generative AI, and infrastructure resilience. Dr. Roy holds a Ph.D. in Computational Science and Engineering from Georgia Tech (2021), with NSF-funded work on scientific computing and data-driven modeling of physical systems. Her research interests bridge computing and real-world applications, emphasizing AI in education and sustainable practices. She has advised students across academic levels and published over 30 peer-reviewed works. Notably, she was honored as one of the top 75 Indian women in Geotechnical Engineering (2023) and received teaching awards including the Provost Teaching Fellowship (2024) and William D. Leahy Jr. Outstanding Instructor Award (2025). She also serves on the editorial board of Nature's Scientific Reports and collaborated with EPFL, Switzerland. Her research trends emphasize AI integration into education (e.g., automated grading tools like VISGRADER), disaster resilience through machine learning (e.g., earthquake damage assessment via social media images), and sustainable infrastructure design. She has pioneered active learning strategies using video tutorials and student-created content, enhancing large-classroom engagement. Her work spans geotechnical engineering applications (e.g., landslide mapping) and materials science (e.g., MICP-cemented sands). Awards: Top 75 Indian Women Leaders in Geotechnical Engineering, Provost Teaching Fellowship, Transformative Teaching Grant, Sustainability Education Award, Leahy Instructor Award Grants: NSF-funded doctoral research, Transformative Teaching Innovation Incubator Grant Dr. Roy leads initiatives in equitable grading practices and rubric development for teaching assistants. She actively contributes to interdisciplinary research teams and participates in international academic collaborations. Her lab focuses on leveraging AI to solve complex engineering and educational challenges.

• Structural and Seismic Monitoring
• Earthquake Engineering
• Numerical Modeling and Simulation
• +۲ مورد دیگر

Linda Scussolini is a PhD Student in Civil and Environmental Engineering at the Polytechnic of Turin, Department of Structural, Building and Geotechnical Engineering (DISEG), currently in her 38th cycle (2022-2025). She also serves as an External lecturer and teaching assistant for Earthquake Engineering courses. Education: BSc in Building Engineering (2019) from the Polytechnic of Turin MSc in Civil Engineering with honors (2021) from the Polytechnic of Turin, specializing in structures and infrastructures Linda's research focuses on Structural and Seismic Monitoring , Earthquake Engineering , and Numerical Modeling and Simulation . Her PhD research involves nonlinear modeling and calibration of virtual simulators, specifically developing efficient tools for dynamic identification of highly nonlinear systems such as those composed of interacting bodies. Her MSc thesis, conducted with the Technical University of Vienna, examined tensegrity structures with geometric nonlinearities. Her publication record demonstrates expertise in structural health monitoring, with emphasis on Volterra system identification, damage detection methodologies, and satellite data applications. She integrates advanced signal processing techniques with machine learning approaches to address complex structural dynamics challenges in civil infrastructure. Linda has served as a Course Collaborator for Earthquake Engineering across multiple academic years: 2023/24: Earthquake Engineering for Civil Engineering 2024/25: Earthquake Engineering for Civil Engineering 2025/26: Earthquake Engineering for Civil Engineering

Ihsan Engin Balمشاهده پروفایل

مدرس

• Earthquake Engineering
• Structural Inspection
• Timber Structures
• +۳ مورد دیگر

Ihsan Engin Bal is a Lecturer in Construction Safety & Earthquakes at the Hanze University of Applied Sciences , affiliated with the Research Centre for Built Environment – NoorderRuimte . With a background in Civil and Structural Engineering from Karadeniz Technical University (2000), his work bridges seismic risk mitigation, timber-masonry structural systems, and digitalization of construction processes. Education: BEng in Civil and Structural Engineering (1996-2000), Karadeniz Technical University. His research focuses on earthquake engineering , particularly unreinforced masonry (URM) walls, timber structural connections, and low-cost sensor applications for construction safety. Recent projects include Hysteresis (hybrid testing of timber buildings) and Trust in Timber (bio-based construction workforce development). He explores applying digital tools like automated crack detection and vibration monitoring to enhance structural resilience. Key themes in his 2024-2025 publications include seismic performance of URM walls, noise-resistant crack segmentation via machine learning, and climate-proof infrastructure. He collaborates extensively with researchers like E. Smyrou and O. Arslan. Professor Bal actively engages in public discourse, notably analyzing Turkey-Syria earthquake vulnerabilities and advocating for improved construction practices. His work spans practical experiments, computational modeling, and policy-oriented insights for disaster prevention.

Yangkang Chenمشاهده پروفایل

عضو هیئت علمی

• Seismic Signal Analysis
• Seismic Modeling and Inversion
• Deep Learning
• +۴ مورد دیگر

Yangkang Chen is a Research Assistant Professor at the Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin. He leads AI/ML research at the Texas Seismological Network (TexNet). His expertise includes seismic signal analysis, deep learning, and high-performance computing. Chen holds a Ph.D. in geophysics from UT Austin (2015) and was a postdoc at Oak Ridge National Laboratory (2016-2018). Research Focus: AI-driven earthquake monitoring, seismic modeling, and reproducible research. Key Contributions: Developed EQCCT, TXED datasets, and open-source tools like pyseistr and DRR. Leadership: Editor of JGR: Machine Learning and Computation, and AGU fellowships. Education: Ph.D. in Geophysics, UT Austin, 2015 Postdoctoral Research at Oak Ridge National Lab (2016-2018) Research Interests span AI applications in seismology, seismic inversion, and reproducible methodologies. His work bridges computational methods with real-world seismic challenges, such as induced seismicity detection and earthquake cataloging. Awards include First Prize in GeoHackathon 2024, Clarivate Highly Cited Researcher (2020), and multiple IEEE recognitions. He advises over 20 graduate students/postdocs, focusing on ML-driven geoscience problems. Chen's lab develops tools for seismic data analysis, DAS processing, and machine learning frameworks.