Hadi Meidani is a Clinical Associate Professor at the Carle Illinois College of Medicine , specifically within the Department of Biomedical and Translational Sciences at the University of Illinois at Urbana-Champaign . He teaches courses in Civil and Environmental Engineering, including topics like Systems Engineering & Economics , Machine Learning in CEE , and Uncertainty Quantification . Ph.D., Civil Engineering, University of Southern California (2012) M.S., Electrical Engineering, University of Southern California (2012) M.S., Structural Engineering, Sharif University of Technology (2005) B.S., Civil Engineering, K.N. Toosi University of Technology (2002) Dr. Meidani's research focuses on uncertainty quantification , scientific machine learning , and optimization under uncertainty for engineering systems. His work spans stochastic multiscale analysis , physics-informed machine learning , and model reduction techniques. His recent publications emphasize machine learning for infrastructure systems , graph neural networks , physics-informed models , and traffic assignment . Key trends include deep learning , multi-fidelity modeling , and neural operator transformers applied to metamaterial design , seismic reliability , and autonomous freight delivery .
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Elmira Hassanzadeh is an Associate Professor at the Department of Civil, Geological and Mining Engineering , Polytechnique Montréal, with a focus on integrated water resource modeling and management under climate and anthropogenic changes. She is affiliated with the Global Institute for Water Security (University of Saskatchewan) and the Experimental and Digital Water Flow Engineering Group (GENIE EAU) . Education: PhD in Civil Engineering, University of Saskatchewan Postdoctoral Fellow, McGill University Research interests include climate change impact assessment, socio-hydrological modeling, stakeholder engagement in water management, and sustainable development of water systems in cold regions. Her work emphasizes decision-making under uncertainty and adaptive strategies for ungauged basins. Recent publications (2024–2020) span coastal flood hazard modeling, climate-driven hydrological changes in tropical and Canadian watersheds, evaluation of agricultural practices under warming climates, and integrated approaches to water quality and system dynamics. Keywords include Hydrology , Climate Change , Water Security , and Socio-Hydrology . Supervision: She has mentored 15+ graduate students in projects related to Lake Urmia, Saskatchewan River Basin, and climate adaptation in Africa and the Pacific.
Professor Emily So serves as Deputy Head of the School of Arts and Humanities at the University of Cambridge and directs the Cambridge University Centre for Risk in the Built Environment (CURBE). A chartered civil engineer with extensive field experience, she holds leadership roles in the Open-Oxford-Cambridge AHRC Doctoral Training Partnership and chairs the Faculty EDI Committee. Her research focuses on urban risk and resilience , particularly in earthquake-prone regions. Combining structural engineering with epidemiological approaches, she develops innovative casualty estimation models and engages directly with affected communities worldwide. Her work spans seismic safety, disaster epidemiology, and remote sensing applications for rapid damage assessment. Professor So's publication trends reveal strong emphasis on machine learning for disaster risk modeling , with recent work featuring graph neural networks, deep clustering for urban morphology, and LSTM-based population forecasting. Her research bridges engineering, social sciences, and data science to address resilience in developing nations. 2010 Shah Family Innovation Prize (Earthquake Engineering Research Institute) Fellow of the Institution of Civil Engineers (FICE) Scientific Advisory Group for Emergencies (SAGE) member advising UK government As Director of CURBE, she leads interdisciplinary collaborations with EEFIT, Global Earthquake Model (GEM), World Bank, and USGS. Her field investigations following major earthquakes inform practical solutions for vulnerable communities, notably contributing to the 2017 World Building of the Year design in China. Current work includes sabbatical research for 2025-2026 focused on decolonizing architectural approaches to disaster resilience. Professor So maintains active roles in professional organizations and international disaster response frameworks, with her CURBE team developing methodologies now implemented globally for seismic safety improvements.
Paolo Gardoni is the Alfredo H. Ang Family Professor and an Excellence Faculty Scholar in the Department of Civil and Environmental Engineering at the University of Illinois Urbana-Champaign, with additional professorial appointments in Industrial & Enterprise Systems Engineering and Biomedical & Translational Sciences. He also serves as Director of the MAE Center and Editor-in-Chief of Reliability Engineering & System Safety. Education Ph.D. in Civil Engineering, University of California, Berkeley (2002) M.A. in Statistics, University of California, Berkeley (2001) M.Eng. in Structural Engineering, University of Tokyo (1997) Laurea (BS+MS equivalent) in Structural Engineering, Politecnico di Milano (1997) Research Interests Gardoni’s scholarship integrates probabilistic methods with large-scale infrastructure systems to advance reliability, risk, and life-cycle analysis. His work quantifies the performance of deteriorating systems under natural and anthropogenic hazards, models societal impacts of disasters, and develops decision frameworks for sustainable and resilient infrastructure. He also examines ethical, social, and legal dimensions of risk, and investigates optimal strategies for hazard mitigation, disaster recovery, and climate adaptation. Across more than 250 refereed journal papers, he has advanced sub-fields ranging from probabilistic mechanics and earthquake engineering to catastrophe bond pricing and engineering ethics, leveraging tools such as stochastic differential equations, Bayesian networks, and physics-informed machine learning. Awards & Honors Alfredo Ang Award on Risk Analysis and Management of Civil Infrastructure (ASCE, 2021) Best Paper Awards in ASCE Journal of Sustainable Water in the Built Environment (2019) and Geotechnical Research (2018 Telford Premium Prize) Fellowships and named professorships: Alfredo H. Ang Family Professor, Excellence Faculty Scholar, and courtesy or honorary professorships at Tsinghua, IIT Guwahati, Tongji, Jianghan, and Loughborough universities. Research Leadership & Funding Gardoni has secured over $58 million in research funding from NSF, DHS, NIST, USAID, Qatar National Research Fund, and other agencies. He directs the MAE Center—formerly an NSF Engineering Research Center—focused on multi-hazard engineering approaches, and is Editor-in-Chief of Reliability Engineering & System Safety (Elsevier, IF 9.4). He founded and formerly led the journal Sustainable and Resilient Infrastructure (Taylor & Francis) and serves on editorial boards of nine additional journals. Advising & Mentorship He has graduated 27 PhD and 35 Master’s students, many of whom now hold faculty positions worldwide. His group maintains an active pipeline of doctoral and post-doctoral researchers working on resilience analytics, infrastructure monitoring, and risk-informed decision-making. Laboratories & Collaborations He leads the MAE Center and is affiliated with the Critical Infrastructure Resilience Institute (CIRI) and the Biomedical and Translational Sciences group. International collaborations span the UK (Loughborough), India (IIT Guwahati), and China (Tsinghua, Tongji, Jianghan), fostering cross-disciplinary research in reliability and resilience engineering.
Amir AghaKouchak is a Chancellor’s Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine (UCI). He directs the Center for Hydrometeorology and Remote Sensing (CHRS) and focuses on interdisciplinary research at the intersection of hydrology, climatology, statistics, and remote sensing. B.Sc. and M.Sc. in Civil Engineering (Water Resources), K.N. Toosi University of Technology, Tehran, Iran (2001, 2005) Ph.D. in Civil and Environmental Engineering, University of Stuttgart, Germany (2010) His research aims to leverage satellite data and ground observations to advance modeling of hydrologic extremes (droughts, floods, landslides) and develop decision-support systems for water resources management. Key areas include climate change impacts , stochastic modeling , and the water-energy nexus . Recent publications highlight his work on multi-hazard analysis, groundwater decline, wildfire resilience, and climate projections. Tools like MhAST and MvCAT demonstrate his methodological contributions to copula-based and multi-hazard modeling.
Dr. John Francis Clinton is the Director of Seismic Networks and Head of the Earthquake Monitoring Section at the Swiss Seismological Service (SED), ETH Zurich. He leads the Marsquake Service for NASA's InSight mission and oversees Switzerland's broadband and strong-motion seismic networks. His expertise spans earthquake early warning systems, seismic instrumentation, and glacial seismology. Clinton is also a Co-Investigator on the Mars InSight mission and involved in international projects like EPOS and RAMSIS. Education PhD in Civil Engineering (Minor in Geophysics), California Institute of Technology (2004) MSc in Civil Engineering, California Institute of Technology (1998) BEng in Civil Engineering, University College Dublin (1997) Research Interests Dr. Clinton focuses on real-time seismology, seismic instrument design, structural health monitoring, and glacial seismology. His work bridges engineering applications with geophysical data analysis, particularly in earthquake early warning systems and induced seismicity studies. He collaborates internationally on projects such as the Valais Near Fault Observatory and Nicaragua’s Earthquake Early Warning development. Publications Overview His 15 most recent papers (2011–2015) highlight advancements in seismic network optimization, Marsquake detection algorithms, and glacial icequake mechanisms. Key themes include improving early warning accuracy, understanding subglacial dynamics, and validating high-rate GPS for structural monitoring. Awards & Memberships Member, Swiss Academy of Sciences (since 2008) Member, IRIS Quality Assurance Advisory Committee (since 2013) Chair, European Integrated Data Archives (EIDA) (2013–2015) Labs & Teams Clinton directs the SED’s Earthquake Monitoring team and collaborates with ETH Zurich’s Geophysics Masters Program. His group manages Switzerland’s seismic networks and leads the Marsquake Service, which analyzes InSight lander data for Martian seismic events.
Miyuki Hino is an Assistant Professor in the Department of City and Regional Planning and an Adjunct Assistant Professor in the Environment, Ecology, and Energy Program at the University of North Carolina at Chapel Hill. She holds a Ph.D. in Environment and Resources from Stanford University and a B.S. in Chemical Engineering from Yale University. Her research focuses on climate hazards, governance, and public policy , with emphasis on equitable adaptation to climate change. Key areas include sea level rise impacts, flood risk on property markets, and managed retreat strategies. She has conducted extensive work on floodplain development policies, household relocation programs, and community resilience frameworks. Dr. Hino's interdisciplinary approach integrates environmental science, urban planning, and social equity . She collaborates with academic and municipal partners, such as the Center for Urban and Regional Studies and Annapolis, MD local governments, to develop actionable solutions for climate adaptation. Her work bridges technical analyses (e.g., sensor networks, machine learning) with policy design to ensure both effectiveness and justice in climate responses. Recent projects emphasize preventing future 'trapped households' by analyzing zoning policies and market dynamics that drive risky development. She advocates for climate-smart growth strategies to balance economic needs with environmental safety, while addressing disparities in vulnerability across communities. Her research has been featured in Science Advances , Nature Climate Change , and interdisciplinary journals. She actively engages with policymakers to translate findings into practical measures, such as equitable buyout programs and floodplain management reforms.
Jim Hall is a Professor of Climate and Environmental Risk at the University of Oxford's School of Geography and the Environment, and serves as Director of Research there. He is also a Visiting Fellow at Linacre College and holds leadership roles including Chair of the Science Advisory Committee at IIASA, and Expert Advisor to the UK's National Infrastructure Commission. His work focuses on systemic risk analysis, infrastructure resilience, and policy implications of climate change adaptation. Prof Hall has pioneered methodologies like the National Infrastructure Systems Model (NISMOD) and chairs the Data and Analytics Facility for National Infrastructure (DAFNI). His research spans flood risk management, energy systems decarbonization, and transboundary water resource conflicts in regions such as the Eastern Nile Basin and the Caribbean. Key research areas include robust decision making under uncertainty, info-gap theory applications, and integrated assessments of human-environmental systems. He has contributed to major international assessments, including the IPCC's Fourth Assessment Report, and developed frameworks for multi-hazard stress testing of infrastructure networks. Scientific Awards: George Stephenson Medal (2001), Prince Sultan Prize for Water (2018), Royal Academy of Engineering Fellowship (2010) His advising and grants work includes mentoring a DPhil student Erin Canning and leading projects like MARIUS and ENHANCE. He has also developed innovative modeling tools for coastal erosion prediction and probabilistic assessments of global shipping fuel transitions. Prof Hall’s research groups actively engage in interdisciplinary projects, including the Oxford Martin Programme on Resource Stewardship and the UK Infrastructure Transitions Research Consortium. His work emphasizes bridging scientific analysis with actionable policy solutions for climate adaptation.
Manish Verma is Professor of Operations Management and Associate Dean, Graduate Studies at the DeGroote School of Business, McMaster University. His academic journey began with an MBA and PhD in Business Administration with Operations Management/Management Science specialization from Desautels Faculty of Management at McGill University. Dr. Verma's research focuses on multimodal transportation of dangerous goods, risk assessment, network design and planning in transportation, humanitarian logistics, green supply chain management, and disruption/resilience in transportation systems. His current research engagements center on safety and security issues in freight transportation and humanitarian logistics, funded by NSERC and SSHRC grants. He has been frequently approached by media to comment on railroad accidents involving dangerous goods. An analysis of his recent publications reveals a strong emphasis on hazardous materials transportation risk management, with significant contributions to rail-truck intermodal systems, hazmat risk modeling using value-at-risk methodologies, and emergency response planning for transportation networks. His work bridges theoretical operations research with practical transportation safety applications. $245K research grant for rail safety research from Government of Canada As an educator, Dr. Verma has taught courses including Predictive Analytics for Managers, Network Design Issues in Freight Transportation, and Management Science Research Issues. His scholarly impact is evidenced by publications in leading journals such as Transportation Research Part E, European Journal of Operational Research, and Safety Science. He actively contributes to real-world transportation safety through media commentary and research that informs policy decisions regarding dangerous goods transportation.
Dr. Kevin Kochersberger is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech , with a career spanning academic research, technical innovation, and educational leadership. His work focuses on autonomous aerial systems , robotic control , and applied aerodynamics , particularly through the Uncrewed Systems Laboratory . Kochersberger's research has pioneered UAV-based radiation detection , 3D terrain mapping , and low-resource drone applications , including establishing the African Drone and Data Academy in Malawi . Education: Ph.D., Mechanical Engineering, Virginia Tech (1994) M.S., Mechanical Engineering, Virginia Tech (1984) B.S., Mechanical Engineering, Virginia Tech (1983) A.S., Engineering Science, Jamestown Community College (1981) Kochersberger's publications demonstrate expertise in UAV path planning , smart material actuation , and radiation source localization , with over $9M in research funding. His scientific awards include AIAA Associate Fellow (2009) and Aviation Week Aerospace Laureate (2003). Notable projects involve helicopter-deployable robotic systems and urban canyon navigation without GPS. Recent articles highlight BVLOS drone simulators , 2.5D terrain mapping , and autonomous negative obstacle traversal , reflecting his focus on real-time adaptive control and heterogeneous robotic systems . He teaches Drone Technology and Flight Operations and Advanced Design Projects , emphasizing student-driven innovation and industry collaboration .
Sai Ravela is a Principal Research Scientist in the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at the Massachusetts Institute of Technology (MIT). His research focuses on nonlinear stochastic dynamics, coherent fluid systems, uncertainty quantification, and autonomous observing technologies. He specializes in developing data-driven methodologies for natural hazard detection, climate change impacts, and environmental risk assessment. Ravela’s work integrates computational science with geophysical applications, including storm surge modeling, extreme rainfall analysis, and geothermal exploration. He pioneers techniques like neural dynamical systems and adversarial learning to improve predictive accuracy in nonstationary climate regimes. His contributions span environmental monitoring systems, autonomous aircraft resilience frameworks, and policy-informed climate vulnerability assessments. Key research areas include: Coastal flood risk in Bangladesh and Vietnam Dynamic data-driven applications systems (DDDAS) Machine learning for geosciences and environmental systems Uncertainty quantification in complex fluid dynamics He leads interdisciplinary projects at MIT’s Computational Science and Engineering (CSE) program, advancing methods for data assimilation, surrogate modeling, and real-time environmental observatories. His innovations bridge theoretical frameworks with practical solutions for climate adaptation and disaster resilience.
Matthew Dunbabin is a Professor at Queensland University of Technology (QUT) and Chief Investigator at the Australian Centre for Robotic Vision (ACRV). His expertise spans environmental robotics, with a focus on vision-based autonomous systems for marine conservation, water quality monitoring, and greenhouse gas management. He holds a PhD from QUT and a BEng (Aerospace) from RMIT. Dunbabin has led projects at CSIRO and QUT, developing robots like COTSBot and RangerBot to combat marine pests and promote reef restoration. His work has earned national and international awards, including the 2019 Australian Water Association Award and 2016 Google Impact Challenge. Education: PhD in Engineering, Queensland University of Technology (Queensland, Australia) BEng (Hons) in Aerospace Engineering, Royal Melbourne Institute of Technology (Melbourne, Australia) Research Interests: Environmental robotics and autonomous systems Vision-based perception and classification Marine habitat restoration and pest control Greenhouse gas monitoring via autonomous vehicles Cooperative robotics and sensor networks Awards & Recognition: 2019 Australian Water Association Award (SAMMI Project) 2019 Good Design Award - Sustainability (RangerBot) 2016 Google Impact Challenge People’s Choice Award (RangerBot AUV) 2010 Australian ICT Industry Association National iAward (iSnet) 2006 Queensland Engineering Excellence Innovation Award (Starbug Project) Grants & Projects: ARC Centre of Excellence for Robotic Vision (ACRV): Leading robotic vision research (2014–present) Revolutionising Protection Against Air Pollution: Air quality monitoring networks (2015–present) Establishing Advanced Networks for Air Quality Sensing: Sensor development for urban environments (2017–present) Labs & Collaborations: ACRV at QUT Institute for Future Environments (QUT) CSIRO Autonomous Systems Laboratory (2001–2013)
Mohammad Modarres is the Nicole J. Kim Eminent Professor at the University of Maryland within the A.J. Clark School of Engineering. He serves as Director of the Center for Risk and Reliability (CRR) and is a Professor of Nuclear Engineering in the Department of Mechanical Engineering. Dr. Modarres co-founded the world's first degree-granting graduate curriculum in reliability engineering at the University of Maryland and has established himself as an international expert in reliability and risk analysis. Dr. Modarres received his educational credentials from prestigious institutions: B.S. in Mechanical Engineering from Tehran Polytechnic M.S. in Mechanical Engineering from MIT M.S. and Ph.D. in Nuclear Engineering from MIT Dr. Modarres' research spans multiple critical areas in engineering risk and reliability. His primary interests include probabilistic risk assessment, uncertainty analysis, probabilistic physics of failure, and probabilistic fracture mechanics. His work encompasses both experimental investigations and sophisticated probabilistic model development. He has made significant contributions to materials degradation science, prognosis and health management systems, and nuclear safety analysis. His research bridges theoretical developments with practical applications in complex engineering systems, particularly in nuclear power and aerospace sectors. Analysis of Dr. Modarres' recent publications reveals a strong trend toward integrating advanced data science techniques with traditional reliability engineering. His work increasingly incorporates machine learning, deep learning, and entropy-based approaches to solve complex problems in prognostics and health management. There's a clear focus on multi-unit systems, particularly in nuclear power applications, and a growing emphasis on data-driven methodologies for remaining useful life estimation and failure prediction. His research maintains a strong foundation in probabilistic methods while embracing cutting-edge computational approaches. Dr. Modarres has received numerous prestigious honors and awards throughout his distinguished career: Nicole Y. Kim Eminent Professorship in Engineering Minta Martin Professorship in A.J. Clark School of Engineering University of Maryland Distinguished Scholar-Teacher (2019) Tommy Thompson Award for outstanding lifetime contributions to nuclear safety (American Nuclear Society) Fellow, American Nuclear Society Fellow, Institute of Electrical and Electronics Engineers (IEEE) Life Fellow of IEEE 1996 Maryland Inventor of the Year Award (in Information Sciences) FDA Commissioner Special Citation for Contributions to Risk Assessment Methods (2004) 2008 International Research Leadership Award (Society for Reliability Engineering, Quality and Operations Management) Honorary Doctorate from Universidad Da Vinci de Guatemala As the founding director of the Center for Risk and Reliability, Dr. Modarres has built a world-renowned program that has awarded over 500 Ph.D. and master's degrees. His research has been supported by significant grants from government agencies and industry partners, particularly in nuclear safety, aerospace reliability, and critical infrastructure protection. He has mentored numerous students who have gone on to become leaders in reliability engineering across various industries. His center collaborates extensively with the International Atomic Energy Agency (IAEA) and other international organizations on risk assessment methodologies. The Center for Risk and Reliability (CRR), which Dr. Modarres directs, serves as a hub for multidisciplinary research in risk and reliability engineering. The center has recently renovated its facilities to enhance collaboration among researchers from different engineering disciplines. CRR maintains strong partnerships with industry leaders including Amazon Lab126 (as evidenced by their collaboration on device durability research) and has been instrumental in advancing probabilistic risk assessment tools used in nuclear power plant safety analysis. The center hosts regular seminars, workshops, and international conferences, positioning itself at the forefront of risk and reliability research globally.
Brett Sanders is a Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. His research focuses on developing innovative algorithms for flow and transport in river and coastal systems and integrating information technologies to create more accurate and efficient simulation tools for flood hazard assessment. His primary research interests include: Flooding and erosion hazards, particularly coastal flooding and urban flooding Surface water quality Low impact development impacts on hydrology Dam-break flooding Aerial and terrestrial lidar scanning Geographical information systems High performance computing for simulation tools Social dimensions of flood risk and adaptation behaviors Dr. Sanders' recent publications (2024-2025) reveal a comprehensive research program addressing both technical and social aspects of flood risk. His work spans computational hydrodynamics, flood hazard mapping, infrastructure vulnerability assessment, and the socioeconomic dimensions of flood risk. He has made significant contributions to understanding multi-grid modeling of urban flooding, post-fire flood hazards, satellite-based monitoring of land motion, and social inequalities in flood exposure. His research demonstrates how flood dynamics are more complex than simple bath-tub filling models suggest, with important implications for urban planning and climate adaptation. Dr. Sanders has received recognition as a Chancellor's Professor at UC Irvine, indicating distinguished scholarly achievement. His educational background includes: Ph.D. in Civil Engineering from the University of Michigan (1997) M.S. in Civil Engineering from the University of Michigan (1994) B.S. in Civil Engineering from the University of California, Berkeley (1993)
