Prof. Eleni Chatzi is a Full Professor and Chair of Structural Mechanics at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. She holds a PhD from Columbia University (2010) and has held roles from Assistant to Full Professor at ETH since 2010. Her research focuses on intelligent structural monitoring and data-driven asset management, emphasizing nonlinear dynamics and sensor integration. Affiliations : Institute of Structural Engineering, European Academy of Wind Energy (EAWE President), Swiss Community for Computational Methods (SWICCOMAS Chair) Research interests include Structural Health Monitoring (SHM), system identification, and advanced simulation tools. She pioneered work on data-driven diagnostics and self-aware infrastructure, supported by grants like the ERC Starting Grant (2015). Awards include the 2020 Walter L. Huber Prize and 2024 SHM Person of the Year Award. Her work spans wind energy infrastructure, metamaterials for vibration control, and AI-driven structural analytics. Over 600 publications and 200k+ citations highlight her impact. She teaches computational science and structural dynamics in ETH's programs and collaborates globally on sustainable infrastructure projects.
Professor Hong Hao is a John Curtin Distinguished Professor at Curtin University, affiliated with the School of Civil and Mechanical Engineering and the Curtin Research Centre for Infrastructural Monitoring & Protection. His expertise spans Structural Dynamics, Earthquake Engineering, Blast and Impact Engineering, and Structural Health Monitoring. He holds prestigious roles like Fellow of ATSE, ISEAM, and ASCE, and has led organizations such as the International Association of Protective Structures and the Australian Earthquake Engineering Society. Education: BE (Tianjin University, 1982), MSc (UC Berkeley, 1985), PhD (UC Berkeley, 1989). Awards include the Tan Chin Tuan Fellowship and multiple Ko Medals. He has authored over 200 journal articles, with recent work focusing on blast-resistant materials, seismic fragility, and AI-driven structural health monitoring. His research emphasizes resilient infrastructure, including metaconcrete structures, corrosion-resistant materials, and sensor-based damage detection. Ongoing projects involve smart tunnel safety under BLEVE explosions and modular building systems.
Dr. Amir Hakami is a Professor in the Department of Civil & Environmental Engineering at Carleton University , where he leads the Carleton Atmospheric Modelling Group . His research focuses on advanced air quality modeling techniques to inform environmental policy. Degrees: B.Sc. (Polytechnic of Tehran), M.Sc., Ph.D. (Georgia Tech), Postdoc (Caltech) Contact: Office 3454 Mackenzie Building, Phone: 613-520-2600 ext. 8609, Email: amir.hakami@carleton.ca Research Interests: Air quality modeling at multiple spatial scales Adjoint sensitivity analysis for atmospheric response Inverse modeling and data assimilation techniques Uncertainty quantification in environmental systems Interdisciplinary applications in policy, public health, and economics Teaching: Courses include Environmental Engineering Systems Modeling , Contaminant Transport , and Air Pollution & Emissions Control at undergraduate and graduate levels. Research Group: The group includes Ph.D. candidates, postdoctoral fellows, and alumni working on topics ranging from atmospheric chemistry to sustainable energy systems. Members come from diverse backgrounds in engineering, science, and policy disciplines.
Jan Dirk Wegner is an Associate Professor at the University of Zurich, holding the chair in 'Data Science for Sciences' and leading the EcoVision Lab. He previously served as a Postdoc (2012–2016) and senior scientist (2017–2020) at ETH Zurich's Photogrammetry and Remote Sensing Group, following his PhD (with distinction) from Leibniz University Hannover (2011). His research bridges machine learning, computer vision, and remote sensing to address environmental and geoscience challenges, focusing on large-scale environmental data analysis, vegetation monitoring, and climate change mitigation. Education: PhD (with distinction) in Geodesy, Leibniz University Hannover (2011) Postdoc, ETH Zurich (2012–2016) Senior Scientist, ETH Zurich (2017–2020) Research Interests: Machine Learning, Computer Vision, Remote Sensing, Environmental Science, Climate Science, Geosciences, Explainable AI, Uncertainty Quantification, and Applications in Sustainability. The EcoVision Lab develops data-driven methods for global-scale environmental monitoring, including vegetation parameter mapping, flood prediction, forest degradation detection, and AI-driven ecological modeling. Awards: ETH Postdoctoral Fellowship (2012–2016) Science Prize of the German Geodetic Commission WEF Young Scientist Class 2020 (Top 25 globally under 40) Advising & Leadership: Director of the University of Zurich's Doctoral School in Data Science, leading the EcoVision Lab, and coordinating the CVPR EarthVision Workshops. His roles include Vice President of ISPRS Technical Commission II, member of the ETH AI Center, ELLIS, and UN-ETH Partnership. Labs/Teams: EcoVision Lab focuses on interdisciplinary AI applications for environmental challenges, collaborating with NGOs, governments, and industry to translate research into societal impact.
Professor Atilla Ansal is a distinguished academic in Civil Engineering at Özyeğin University's School of Engineering, where he has served as a full-time professor since March 2012 and previously as the Founding Chair of the Civil Engineering Department from 2012-2019. With an extensive career spanning over five decades, Professor Ansal has held prominent positions at Istanbul Technical University, Bogaziçi University's Kandilli Observatory and Earthquake Research Institute, and has served as a visiting professor at numerous international institutions including Northwestern University, University of California, and Tokyo University. Northwestern University, 1978 (Doctorate) Civil Engineering, Istanbul Technical University, 1969 (Master's) Civil Engineering, Istanbul Technical University, 1969 (Bachelor's) Professor Ansal's research focuses on Earthquake Geotechnical Engineering, Soil Dynamics, Seismic Hazard Analysis, Landslide hazard analysis, Seismic Microzonation, and Laboratory and In-Situ Testing of Soil Properties. His work has significantly advanced our understanding of soil behavior under seismic loading, site response analysis, and seismic microzonation methodologies. His research has direct applications in urban planning, earthquake risk mitigation, and performance-based seismic design. Professor Ansal has pioneered approaches to site-specific earthquake characterization and developed methodologies for seismic microzonation that have been implemented in numerous Turkish cities and adopted internationally. His extensive publication record demonstrates consistent contributions to earthquake engineering, with recent work focusing on probabilistic seismic microzonation, 2D basin effects, site-specific response analysis, and performance-based design approaches. His research shows a clear evolution from fundamental soil behavior studies to practical applications in urban risk assessment and mitigation. 7th Prof.N.Ambraseys Lecturer (2024), European Association for Earthquake Engineering 15th Nonveiller Lecturer (2017), Croatian Geotechnical Society Third Prof.Dr. Rıfat Yarar Lecturer (2015), Turkish Civil Engineers Association Third Ord.Prof.Dr. Hamdi Peynircioglu Lecturer (1988) Professor Ansal has advised 15 PhD students and 27 Master's students, shaping the next generation of earthquake engineers. His leadership extends to editorial roles as Editor-in-Chief of the Springer journal 'Bulletin of Earthquake Engineering' since 2002 and Editor-in-Chief for the Springer book series on 'Geotechnical, Geological and Earthquake Engineering'. He served as Secretary General (1994-2014), President (2014-2018), and Vice President (2018-2022) of the European Association for Earthquake Engineering, significantly influencing the field internationally. His work has been supported by numerous grants from Turkish government agencies, international organizations including UNESCO, and collaborative research projects across Europe. Professor Ansal has been instrumental in establishing geotechnical monitoring systems in Istanbul, including vertical arrays for site response analysis. His leadership in the 'Earthquake Master Plan for Istanbul' and 'Seismic Microzonation for Municipalities' projects has created critical infrastructure for earthquake risk management in Turkey's most populous city. His work with GeoIst, Geotechnical Earthquake Engineering and Consultancy Inc. has translated academic research into practical engineering solutions for seismic risk mitigation.
Babak Moaveni is a Professor in the Department of Civil and Environmental Engineering at Tufts University, serving as the Associate Chair since September 2024. He also holds a joint appointment as a Professor in Electrical and Computer Engineering. His research focuses on structural health monitoring, Bayesian inference, earthquake engineering, and offshore wind energy systems. Moaveni earned his Ph.D. in Structural Engineering from the University of California San Diego (2007), following an M.S. (2001) and B.S. (1999) from Sharif University of Technology in Tehran, Iran. His research interests span probabilistic system identification, signal processing, uncertainty quantification, and verification/validation of computational models. Notable grants include leadership in the PIRE project on offshore wind energy digital twins and the Coastal Virginia Offshore Wind Pilot Project. He has supervised multiple Ph.D. and M.S. students, with current advisees including Mehdi Akhlaghi and Nasim Partovi-Mehr. Moaveni has received the Best Presentation Award at the 2022 EDGE Symposium and serves on editorial boards for journals like Structural Health Monitoring and Frontiers in Built Environment . His lab, the Structural Health Monitoring Lab, specializes in infrastructure management and offshore wind energy systems. Key professional activities include membership in the American Society of Civil Engineers (ASCE) and roles on Tufts' Tenure and Promotion Committee. His teaching includes courses on structural health monitoring, numerical methods, and structural reliability.
Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.
Erin Bell is a Professor in the Department of Civil and Environmental Engineering at the University of New Hampshire . She holds a Ph.D. in Structural Engineering from Tufts University and has extensive experience in structural health monitoring, finite element modeling, and infrastructure sustainability. B.C.E., Georgia Institute of Technology M.S., Civil Engineering, Tufts University Ph.D., Structural Engineering, Tufts University Her research focuses on structural health monitoring, bridge condition assessment, and integrating AI techniques like artificial neural networks and deep reinforcement learning for infrastructure asset management. Recent work includes equitable maintenance strategies for aging bridges in flood-prone zones and tidal energy conversion for sustainable bridge monitoring systems. Key trends in her publications include the application of machine learning to structural analysis, finite element model calibration, and climate change adaptation in transportation infrastructure. She has led projects on deep reinforcement learning for bridge scour maintenance, modal-based uncertainty quantification, and multi-scale modeling of steel bridges. Grants and Collaborations : Erin Bell has secured funding from the National Science Foundation (NSF) , US Department of Energy (DOE) , and New Hampshire Department of Transportation . Notable projects include the Living Bridge initiative for tidal energy-powered smart infrastructure and statewide data exchange systems for bridge condition assessment.
Craig L. Just holds the Donald E. Bently Professorship in Engineering and serves as a Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering. He also works as a Faculty Research Engineer at IIHR—Hydroscience and Engineering. With a PhD in Environmental Engineering and Science (2001) and an MA in Chemistry (1994), both from the University of Iowa and University of Northern Iowa respectively, his career spans over two decades of academic and practical contributions. Education: PhD, Environmental Engineering and Science, University of Iowa (2001) MA, Chemistry, University of Northern Iowa (1994) BS, Chemistry, University of Northern Iowa (1992) Dr. Just's research focuses on water quality monitoring through sensor technology, freshwater mussel biosensing , pharmaceutical contaminant removal , and PCB exposure analysis from dredging operations. His work bridges environmental engineering with ecological health and sustainable systems. Recent publications highlight trends in anaerobic digestion optimization , PCB emission characterization , and machine learning applications for biogas prediction. He has extensively studied constructed wetlands , nitrogen cycling , and flood risk mitigation in agricultural and urban contexts. As director of the Iowa Wastewater and Waste to Energy Research Program, he leads initiatives connecting bioremediation , smart infrastructure , and community engagement . His projects span from hydrological modeling in Iowa to international water programs in Honduras.
Dr. Omar Rifaie Graham is a Lecturer (Assistant Professor) in Chemistry at Queen Mary University of London's School of Physical and Chemical Sciences, joining in September 2023. He leads a research group focused on polymer-based artificial cells to study physicochemical parameters underlying biological phenomena and develop technologies at the Living/Non-Living Interface. Previously, he held postdoctoral positions at Imperial College London and the University of Fribourg, Switzerland. Education: Licenciado in Pharmacy (BSc+MSc), Universidad Complutense de Madrid, Spain (2008–2014) PhD in Chemistry, Adolphe Merkle Institute – University of Fribourg, Switzerland (2014–2018) Research Interests: Development of artificial cells using polymer nanocontainers, stimuli-responsive materials (light, hydromechanical stress), and applications in biotechnology, therapy, and diagnostics. His work includes creating polymersomes with novel functionalities for drug delivery, diagnostics, and synthetic biology. Key Achievements: ACS PMSE Future Faculty Award (2023) Swiss Nanoscience Institute 'Best paper in nanoscience' (2021) Best PhD thesis in Experimental Sciences, University of Fribourg (2019) Co-founded a diagnostics company spun from his PhD research (1M+ USD funding) Grants & Collaborations: Royal Society Grant: £29,907 (2025–2026) National Institute for Health Research Grant: £315,942 (2020–2025) RSC Grant for 'Mimicking colour perception with artificial cells' (2024) Lab/Team: Directs a research group at Queen Mary's Department of Chemistry, collaborating with institutions like Imperial College London and the University of Fribourg. Active in synthetic biology, nanomedicine, and biomimetic materials.
Dr. Donna Harris is an Assistant Professor in the Department of Plant Sciences at the University of Wyoming, based at the Sheridan Research & Extension Center. Her academic career includes roles as Senior Scientist at BASF Vegetable Seeds (2015–2020), Research Professional III at the University of Georgia (2007–2015), and prior industry experience with Monsanto and Pioneer Hi-Bred International. She holds a PhD (2014) and MS (2001) in Crop Science from the University of Georgia, alongside a BS (1998) in the same field. Her research focuses on plant breeding and genetics, addressing crop needs for Wyoming producers and consumers. Key areas include soybean rust resistance, quantitative trait loci (QTL) analysis, and germplasm evaluation for disease resistance. She has contributed significantly to soybean breeding programs, identifying novel resistance genes and developing resistant cultivars. Dr. Harris has published extensively on soybean pathology and genetics, with work appearing in Theoretical and Applied Genetics , Molecular Breeding , and Crop Science . Her publications emphasize molecular mapping of resistance genes, germplasm screening, and disease management strategies. While no awards are explicitly listed, her impactful research has shaped soybean improvement efforts in the U.S. and globally. Her professional experience spans academic and industrial settings, with expertise in both theoretical genetics and applied breeding. Current research integrates field-based evaluations with genomic approaches to enhance crop resilience against biotic stresses.
Manolis Chatzis is an Associate Professor in the Department of Engineering Science at the University of Oxford and a Tutorial Fellow at Hertford College. His research focuses on dynamic systems and earthquake engineering, particularly modeling risks for unanchored structural and non-structural components subjected to ground motions. University of Oxford - Department of Engineering Science Hertford College - Tutorial Fellow His work on system identification and observability of nonlinear systems aims to optimize sensor setups for infrastructure reliability. Recent publications address discontinuous Kalman filters for non-smooth dynamics, energy loss in rocking bodies, and experimental validation of seismic response models. Applications span seismically isolated buildings, museum artifacts, hospital equipment, and supercomputers. Key research trends include: Nonlinear dynamics of rocking/sliding systems Bayesian identification methods Energy dissipation mechanisms 3D motion tracking algorithms Sensor fusion and data-driven modeling His publications since 2010 demonstrate interdisciplinary collaboration across civil, mechanical, and computational engineering domains.
Eileen Martin is an Associate Professor in the Department of Geophysics and Applied Math and Statistics at the Colorado School of Mines. Her research focuses on near-surface geophysics, environmental monitoring, and the application of distributed acoustic sensing (DAS) technology. She leads projects involving fiber-optic sensing for permafrost degradation, urban seismic monitoring, and mining safety. Martin has developed open-source tools like DASCore and contributes to scalable computational methods for geophysical data analysis. Education: PhD (2018) in Computational and Mathematical Engineering from Stanford University; MS (2017) in Geophysics from Stanford; BS (2012) in Mathematics and Physics from UT Austin. Research interests include fiber-optic sensing systems, seismic imaging, data-intensive computing, and applications in environmental science. Her work bridges geophysics with computational methods, emphasizing real-world deployment in challenging environments like arctic permafrost sites and underground mines. Her recent work explores DAS for glacier monitoring, mine seismicity detection, and urban infrastructure assessment. Collaborative projects include Arctic permafrost monitoring and developing public datasets for geoscience research (PubDAS repository). Grants and lab activities include NSF CAREER funding for scalable computational seismology and partnerships with industry on fiber-optic monitoring solutions.
Dr. Andy Nguyen is a Senior Lecturer in Structural Engineering at the University of Southern Queensland, within the School of Engineering. He is an active researcher and educator, specializing in the Structural Health Monitoring (SHM) of critical civil infrastructure such as bridges, buildings, and transport tunnels. Bachelor of Engineering (BEng), NUCE, 1999 Master of Engineering (MEng), NUCE, 2003 Doctor of Philosophy (PhD), Queensland University of Technology (QUT), 2014 Dr. Nguyen's research is at the forefront of integrating advanced technologies into civil engineering. His primary focus is on developing and deploying sophisticated SHM systems that utilize sensors, data analytics, and machine learning to provide real-time insights into the structural integrity of ageing infrastructure. His work aims to enable proactive maintenance, extend the lifespan of structures, and enhance public safety. He has successfully implemented monitoring systems on major bridges and high-rise buildings in Queensland and New South Wales, with systems capable of even detecting distant earthquake events. His research interests span Structural Health Monitoring, Machine Learning for Engineering, Damage Detection, Finite Element Model Updating, Sustainable Building Materials like bamboo, and the application of AI for automated condition assessment of transport infrastructure. The analysis of his recent publications reveals a strong and consistent research trajectory centered on the application of data-driven and AI methods to solve practical problems in civil infrastructure. His work frequently combines signal processing techniques (like Stockwell Transform) with deep learning models for tasks such as crack detection in concrete and pavement. He also conducts significant research on model updating for complex structures like cable-stayed and arch bridges, using vibration data and optimization algorithms. The integration of machine learning for overload classification and the development of cost-effective, automated monitoring systems are key trends in his recent output. Advanced Queensland Fellow (2024-2027) Dr. Nguyen is actively involved in research supervision and collaboration. He is currently supervising several postgraduate students on projects related to AI-powered condition assessment, bamboo as a sustainable building material, and railway track design. He receives research funding from the Queensland Government through his Advanced Queensland Fellowship. His research has direct practical applications, as evidenced by his public engagement, such as writing for The Conversation on safeguarding ageing bridges, and his work with the Australian Network of Structural Health Monitoring. Dr. Nguyen's work embodies the development of a next-generation 'Living' Laboratory for engineering education, where research, teaching, and real-world infrastructure monitoring are integrated. His current projects involve creating smart, automated fault detection systems and advancing 'digital twin'-based monitoring platforms for infrastructure.
Dr. Zhen Peng is a Research Fellow at Curtin University's School of Civil and Mechanical Engineering, part of the Faculty of Science and Engineering. He holds an ARC Early Career Industry Fellowship (2025–2028), focusing on developing cost-effective bridge monitoring systems using computer vision and edge computing in collaboration with Main Roads WA. His work bridges structural engineering, IoT/edge computing, and machine learning to enhance infrastructure safety. Dr. Peng earned his PhD from Curtin University (Chancellor's Commendation, 2022). His research emphasizes structural dynamics, nonlinear damage detection, and mobile crowdsensing frameworks for infrastructure monitoring. He has published extensively in top journals like Engineering Structures and Structural Control and Health Monitoring , receiving notable awards such as the 2023 Best Paper Award and a Gold Medal in the China Postdoctoral Innovation Competition. His current projects include deploying IoT-driven systems for real-time bridge condition assessment and training students via available 2025 PhD scholarships. Dr. Peng teaches courses in civil engineering and structural analysis, contributing to both academia and industry through innovation in smart infrastructure technologies.
