جست‌وجوی استاد و پژوهشگر

Rafał Weronمشاهده پروفایل

استاد

• Forecasting
• Agent-based modeling
• Computational economics
• +۴ مورد دیگر

Rafał Weron is a Full Professor at Wrocław University of Science and Technology, where he has held leadership roles since 2015, including Head of the Department of Operations Research and Business Intelligence and Chairman of the Scientific Discipline Council for Management and Quality Sciences. His expertise spans electricity price forecasting, computational economics, and risk management, with significant contributions to probabilistic forecasting methods. As a globally recognized scholar, he has received prestigious awards such as the Hugo Steinhaus Prize (2018) and the Tao Hong Award (2017). Key Affiliations : Wrocław University of Science and Technology; Polish Academy of Sciences (Statistics and Econometrics Committee); Polish Mathematical Society. Research Trends: Weron's work focuses on electricity price forecasting, leveraging machine learning and statistical models to enhance accuracy and reliability. His publications emphasize probabilistic forecasting frameworks, quantile regression, and hybrid modeling techniques, reflecting a commitment to methodological rigor and practical applications in energy markets. Scientific Awards: Top 1% globally ranked economist (IDEAS/RePEc, 2013-2022) World's Top 2% Most Widely Cited Scientist (2019-2021) 'Hugo Steinhaus' Prize (2018) Tao Hong Award (2017) Emerald Citation of Excellence (2017) Minister of Science & Higher Education Prize (2016) Commission of National Education Medal (2016)

Stephen M. Straderمشاهده پروفایل

دانشیار

• Natural Hazards
• Climate Change
• Meteorology
• +۷ مورد دیگر

Stephen M. Strader is an Associate Professor of Geography and the Environment at Villanova University, serving as Graduate Program Director. He holds a Ph.D. from Northern Illinois University (2016) and specializes in hazards geography, atmospheric science, and GIS applications. His research focuses on severe weather vulnerability, climate change impacts, and disaster risk reduction, with emphasis on tornado exposure, mobile home safety, and urban sprawl effects. He has led grants addressing tornado sheltering behaviors and severe weather communication, and co-authored over 30 peer-reviewed articles. Strader’s work bridges physical and social sciences to enhance community resilience against natural hazards. Education: Ph.D. & M.S. in Geography (Northern Illinois University), B.S. in Geography (Indiana University) Affiliations: American Meteorological Society, Association of American Geographers Research highlights include the 'Expanding Bull's Eye Effect'—explaining how population growth amplifies disaster risks—and studies on tornado impacts in mobile home communities. He actively engages with media to communicate climate and disaster science, including op-eds in The New York Times and CNN.

Ferrante Neriمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Optimization
• +۵ مورد دیگر

Professor Ferrante Neri is a faculty member at the University of Surrey, holding the positions of Professor of Machine Learning and Artificial Intelligence and Associate Dean (International) for the Faculty of Engineering and Physical Sciences (FEPS). He is affiliated with the Nature Inspired Computing and Engineering Research Group, Surrey Institute for People-Centred AI (PAI), and the Computer Science Research Centre within the School of Computer Science and Electronic Engineering. His research focuses on optimization, explainable AI, and machine learning, with contributions to memetic computing and differential evolution. Since 2010, he has chaired the IEEE Task Force on Memetic Computing. He advises PhD students in topics like dynamic multi-objective optimization and AI-driven applications. His teaching expertise includes mathematical foundations for computer science. He has supervised students such as Aisha E S E Saeid and Pengjin Wu. Notable research areas include evolutionary algorithms, neural architecture search, and applications in robotics and environmental monitoring. Labs and teams include the Nature Inspired Computing group, which explores AI-driven solutions for complex problems. His work bridges theoretical advancements and practical applications in fields like autonomous systems and deep learning.

• Forecasting
• Time Series Analysis
• Inventory Management
• +۵ مورد دیگر

Nikolaos Kourentzes is a Professor of Informatics at the University of Skövde , specializing in forecasting and operations research. His work bridges theoretical advancements in time series analysis with practical applications in supply chain management, tourism demand, and renewable energy forecasting. Academic Rank: Professor Department: Department of Information Technology Research Interests: His research focuses on hierarchical and temporal forecasting methodologies, integrating macroeconomic indicators into demand planning, inventory optimization, and machine learning applications. He explores forecast reconciliation, shrinkage estimators, and the role of expert judgment in predictive analytics. Recent Publications: Highlights include advances in hierarchical forecasting with leading indicators, probabilistic forecasts during crises like the pandemic, and complex smoothing techniques. His work spans journals such as Omega , International Journal of Forecasting , and European Journal of Operational Research . Collaborations: Kourentzes collaborates with researchers globally, including George Athanasopoulos, Rob Hyndman, and Robert Fildes, across domains like tourism analytics, tire industry forecasting, and public health modeling.

Abolfazl Simorghمشاهده پروفایل

پژوهشگر

• Aircraft Trajectory Optimization
• Climate Change Mitigation in Aviation
• Robust Control
• +۳ مورد دیگر

Abolfazl Simorgh is a researcher at Charles III University of Madrid's Department of Aerospace Engineering, specializing in climate-optimized aviation systems. His work bridges mathematical control theory with practical climate impact mitigation, focusing on robust trajectory optimization under environmental and operational uncertainties. He leads development of open-source tools for sustainable flight planning while contributing to major European aviation initiatives. Education: B.Sc. in Control Engineering (2017) M.Sc. in Control Engineering (2020) Ph.D. in Aerospace Engineering from Charles III University of Madrid Dr. Simorgh's research centers on developing mathematical frameworks that reconcile aircraft trajectory optimization with climate impact reduction. His expertise spans robust control systems, optimization under uncertainty, and climate modeling integration, with particular emphasis on non-CO₂ emissions. His methodology addresses both CO₂ and non-CO₂ climate forcing mechanisms through computationally efficient algorithms that account for weather variability and climate metric uncertainties. This work directly supports aviation's decarbonization by providing operational strategies that reduce environmental footprint without prohibitive cost increases. Analysis of his 15 most recent publications reveals a cohesive research trajectory focused on operationalizing climate-optimal flight planning. His work consistently integrates climate science with aerospace engineering through robust optimization frameworks, demonstrating particular innovation in handling multiple uncertainty sources (weather, climate models, emissions). The publications cluster around three interconnected themes: 1) Development of open-source computational tools (ROOST, CLIMaCCF), 2) Network-scale implementation of climate-aware air traffic management, and 3) Risk analysis of climate mitigation strategies. This body of work establishes new methodological standards for quantifying and minimizing aviation's total climate impact. Scientific Awards: Luis Azcárraga Aeronautical Innovation Award for collaborative research impact Best Paper Award (2022) from a high-impact aerospace journal Dr. Simorgh secures significant research funding through European Commission projects including FlyATM4E (climate-optimized flight planning), ALARM (aviation emissions reduction), and RefMAP (sustainable aviation pathways). His grant portfolio emphasizes practical implementation of climate mitigation strategies, with strong industry-academia collaboration. He mentors junior researchers through project teams and has developed three major open-source Python libraries (CLIMaCCF, ROOST, ROC) that have become community standards for climate impact assessment in aviation research. His current work focuses on scaling climate-optimized trajectories to continental airspace while addressing operational constraints and economic viability. He leads a research group focused on climate-aware air traffic management, developing the ROOST simulation framework for GPU-accelerated trajectory optimization and the CLIMaCCF library for standardized climate metric calculations. His team collaborates with European air navigation service providers and aircraft manufacturers to transition research into operational practice, with current projects emphasizing real-time implementation and regulatory compliance frameworks.

Daniela Castro Camiloمشاهده پروفایل

مدرس ارشد

• Extreme Value Theory
• Environmental Risk Analysis
• Spatial Statistics
• +۳ مورد دیگر

Dr. Daniela Castro Camilo is a Senior Lecturer in Statistics at the University of Glasgow's School of Mathematics & Statistics. Her research focuses on extreme value theory applied to environmental hazards, including landslides, climate extremes, and risk assessment. She leads projects like the Mitigating Landslides Impacts in Scotland (MLIS) and Geostatistical Binary Models for Extremes (GEOBEx) , funded by the Scottish Government and EPSRC. She collaborates with institutions such as the British Geological Survey and the Met Office. Her work bridges statistical methodology and environmental applications, with notable contributions to landslide hazard modeling and spatial extremes. She actively participates in international conferences and organizes events like the ESS-sponsored session at the 2024 RSS Conference. She is a core member of GLE²N (Glasgow-Edinburgh Extremes Network), fostering interdisciplinary research in statistical risk analysis. Recent projects include developing probabilistic forecasting tools for weather-driven faults in electricity networks and advancing Bayesian methods for extreme event prediction. Her research emphasizes practical solutions for resilience to environmental disasters, combining cutting-edge statistical techniques with real-world data challenges.

John Allenمشاهده پروفایل

دانشیار

• Meteorology
• Severe Weather
• Climatology
• +۱۰ مورد دیگر

Dr. John Allen is an Associate Professor of Meteorology in the Department of Earth and Atmospheric Sciences at Central Michigan University, where he also serves as Director of the Earth and Ecosystem Science Ph.D. Program and Associate Director of the NSF Artificial Intelligence Institute for Environmental Sciences (AI2ES). He is actively engaged in interdisciplinary research focusing on severe convective storms, their climatology, and responses to climate change. Education: Ph.D., Earth Sciences (Meteorology), The University of Melbourne, 2013 B.S., Research Honours (Meteorology), The University of Melbourne, 2008 B.S., Meteorology and Applied Mathematics, The University of Melbourne, 2007 Dr. Allen’s research centers on global severe weather, particularly tornadoes and hail, and their interactions with climate variability and change. He employs machine learning, statistical modeling, and environmental datasets to improve forecasting and risk assessment. His work spans climatology, atmospheric dynamics, and operational meteorology, with a strong emphasis on translating climate projections into actionable resilience strategies. His recent publications demonstrate a strong trend in applying artificial intelligence and deep learning to severe weather prediction, including hail nowcasting, frontal boundary detection, and hodograph analysis for hazard discrimination. These works reflect a focus on both theoretical understanding and practical forecasting applications. Scientific Awards: National Science Foundation CAREER Award (2020) Central Michigan University Provost’s Award for Outstanding Research (2019/2020) College of Science & Engineering Award for Outstanding Research (2019) AGU Editors' Citation for Excellence in Refereeing (2015) European Severe Storms Laboratory Heini Tooming Award (2015) AMS STAC Outstanding Early Career Award (2022) AMS Editor’s Award for Reviews (2022) Dr. Allen advises numerous Ph.D. students and postdoctoral researchers, and leads multiple funded projects with NSF and NIST. He has served as an editor for Weather and Forecasting and Artificial Intelligence for the Earth Systems . His research group, the Allen Research Group, conducts fieldwork and collaborates internationally on hail and tornado studies. Key Research Projects: NSF-funded ICECHIP hail field campaign (co-lead, summer 2025) Quantifying Risk of Wind and Hail Storms in a Warming Climate (NIST-funded) Geospatial Predictive Analysis of Hail and Wind (AON Inc.) Left-moving Supercell Storm Processes (NSF) Improving High-Impact Hail Forecasts (NSF PREEVENTS)

David Stainforthمشاهده پروفایل

پژوهشگر ارشد

• Climate Modeling
• Climate Economics
• Uncertainty Quantification
• +۵ مورد دیگر

David Stainforth is a Professorial Research Fellow at the Grantham Research Institute on Climate Change and the Environment at the London School of Economics and Political Science (LSE) and an Honorary Professor in the Department of Physics at the University of Warwick. A physicist by training, he co-founded the climateprediction.net project at Oxford University and has focused on climate modeling, uncertainty quantification, and decision-making under deep uncertainty. Primary Affiliation: Grantham Research Institute on Climate Change and the Environment, LSE Honorary Professor: Department of Physics, University of Warwick Research Interests : Stainforth investigates uncertainty in climate modeling , nonlinear dynamical systems , and climate economics . His work bridges climate science and policy analysis , emphasizing the challenges of linking climate projections to societal decision-making . He critiques the use of probability distributions in climate projections and advocates for restructuring academic research to better address climate change’s interdisciplinary challenges. Scientific Contributions : His recent work focuses on parametric uncertainty in climate models , economic damages from temperature variability , and assessing regional climate information . Key trends in his articles include nonlinear climate responses , integrated assessment models , and innovative approaches to adaptation planning . Scientific Awards : Lloyds Science of Risk Prize 2021 for research on temperature variability and economic damages NERC Research Fellowship Tyndall Research Fellowship Advising and Grants : Stainforth collaborates extensively with researchers like Raphael Calel, Suraje Dessai, and Erica Thompson on climate policy , economic assessments , and uncertainty frameworks . His projects often involve interdisciplinary grants and large-scale climate modeling experiments . Labs and Teams : He co-founded and led the climateprediction.net project, the world’s largest climate modeling experiment. He contributes to initiatives like the UK Climate Projections (UKCP09) and decision-making under uncertainty frameworks.

Luke Barnardمشاهده پروفایل

دانشیار

• Solar Physics
• Space Weather
• Heliospheric Physics
• +۳ مورد دیگر

Dr. Luke Barnard is an Associate Professor in the Department of Meteorology at the University of Reading, specializing in solar physics and space weather. His research focuses on solar wind dynamics, coronal mass ejections (CMEs), and their interactions with planetary environments. He contributes to models like HUXt for solar wind prediction and collaborates on space missions such as STEREO, Parker Solar Probe, and Tianwen-1. His work involves data assimilation techniques, ensemble modeling, and reconstruction of historical solar activity. Dr. Barnard's studies bridge observational data with theoretical models to advance understanding of heliospheric phenomena and their geophysical impacts. Key Affiliations: Department of Meteorology, University of Reading. Research Themes: Solar wind modeling, CME propagation, space weather forecasting, geomagnetic effects, and long-term solar variability. Collaborations: Extensive international collaborations, including with NASA, ESA, and institutions such as BepiColombo and MAVEN missions. His recent work emphasizes probabilistic solar wind forecasting, CME interaction with comets and planets, and historical reconstructions of solar activity. He has published over 79 peer-reviewed articles, with a focus on solar-heliospheric dynamics and space weather mitigation strategies.

Olivia Romppainen-Martiusمشاهده پروفایل

استاد

• Climate Science
• Meteorology
• Natural Hazards
• +۳ مورد دیگر

Prof. Olivia Romppainen-Martius is a Professor and Group Leader of the Climate Impacts research group at the Institute of Geography, University of Bern. She co-directs the Mobiliar Lab for Natural Risks and focuses on short-term climate dynamics, high-impact weather systems, and midlatitude weather patterns. Her work integrates advanced modeling techniques with real-world applications in disaster risk reduction. Her research spans climate variability analysis, probabilistic forecasting of extreme events, and the development of early warning systems. She leads collaborative projects combining machine learning with Earth system modeling to improve understanding of weather extremes under climate change. Key interests include flood forecasting, hailstorm dynamics, and Mediterranean cyclone behavior. Prof. Romppainen-Martius has pioneered web-based visualization tools for impact-based flood warnings and has contributed to kilometer-scale Earth system modeling frameworks like nextGEMS. Her methodologies emphasize statistical reconstruction of historical weather events and the application of AI to convective weather prediction. Her research outputs reflect a strong focus on bridging climate science with practical risk management strategies, particularly in alpine and pre-alpine environments. Current efforts include long-term analysis of Swiss hailstorms and development of crowd-sourced data integration for meteorological observations.

Liping Wangمشاهده پروفایل

استاد

• Building Performance Modeling
• HVAC Fault Detection and Diagnosis
• Energy Efficiency in Indoor Agriculture
• +۹ مورد دیگر

Liping Wang is a Professor in the Department of Civil and Architectural Engineering at the University of Wyoming, part of the College of Engineering and Physical Sciences. She also serves as the Director of the Center for Controlled Environment Agriculture, highlighting her leadership in sustainable building and agricultural systems. Her work bridges engineering, energy efficiency, and environmental resilience. Academic Background: B.S., Xi’an University of Architecture and Technology, China M.S., Xi’an University of Architecture and Technology, China Ph.D., National University of Singapore Her research interests focus on building performance modeling, fault detection and diagnosis for HVAC systems, energy efficiency in indoor agriculture, and the development of resource-efficient and resilient future communities. She applies data-driven and adaptive modeling techniques to enhance building energy systems and indoor environmental quality. The analysis of her recent publications reveals a strong trend toward intelligent building systems, with recurring use of machine learning (e.g., Gaussian mixture models, particle swarm optimization) for HVAC modeling, fault detection, and energy optimization. Her work increasingly integrates controlled environment agriculture, reflecting a shift toward sustainable food-energy-water nexus solutions. Topics span from fundamental thermodynamics to applied field evaluations of ASHRAE standards. Scientific Awards: NSF CAREER Award (1944823), National Science Foundation, 2019 Appreciation Award, Advisor of ASHRAE Student Branch, University of Wyoming, 2019 Liping Wang has secured competitive research funding, notably the NSF CAREER Award, and mentors students through research and professional engagement. She actively contributes to the academic community as an Associate Editor of the International Journal of Sustainable Energy Technologies and Assessments and a guest editor for Energy and Buildings . Her work involves interdisciplinary collaboration, with co-authors from diverse engineering and environmental science backgrounds. She has served as an ad hoc reviewer for top journals including Building and Environment , Energy and Buildings , and Applied Energy . She leads the Center for Controlled Environment Agriculture, which likely involves a research team focused on energy-efficient indoor farming technologies, greenhouse modeling, and sustainable building-agriculture integration. Her lab appears to utilize low-cost sensor systems (e.g., Arduino-based platforms) for real-time monitoring of environmental conditions.

William Riebsame Travisمشاهده پروفایل

دانشیار

• Climate Change Adaptation
• Natural Hazards
• Risk Analysis
• +۳ مورد دیگر

William Riebsame Travis is an Associate Professor in the Department of Geography at the University of Colorado, where he also serves as Director of the North Central Climate Adaptation Science Center (CIRES/USGS). He holds a Ph.D. from Clark University (1981) and leads research initiatives through Earth Lab's Adaptation Science program and Western Water Assessment. Research Focus: His work explores three interconnected themes: Extremes, Risk and Disasters : Investigating disaster theory, warning system failures, and societal responses to low-probability/high-consequence events Forecast-Informed Decision Making : Developing quantitative models integrating probabilistic weather/climate forecasts for sectors like ranching and infrastructure management Climate Adaptation Science : Creating frameworks for climate-sensitive resource management through risk analysis and decision modeling His publications demonstrate consistent focus on climate extremes, risk analysis methodologies, and human-environment interactions. Recent work emphasizes accelerating environmental risks (wildfires, droughts) and adaptation decision-making under uncertainty. Advising & Leadership: Directs graduate research (including current advisee Luca Anna Palasti) and secures funding from NOAA, NSF, USGS, and CU's Earth Lab. Leads collaborative projects through the North Central Climate Adaptation Science Center and maintains the scholarly archive of geographer Robert W. Kates.

Kevin Ashمشاهده پروفایل

دانشیار

• Environmental Hazards
• Earth System Science
• Climate Risk
• +۳ مورد دیگر

Kevin Ash is an Associate Professor at the University of Florida's School of Natural Resources & Environment, co-leading the Climate Risk and Storm Hazards (CRASH) Lab. His research focuses on environmental hazards, actionable earth system science, and geospatial analysis of weather-related risks. He emphasizes interdisciplinary approaches to study human-environment interactions, particularly vulnerability assessment and policy implications for communities facing flood, wind, and sea-level rise threats. Education includes a PhD in Geography (University of South Carolina, 2015), MS in Geography (University of Florida, 2010), and BA in Geography (University of Oklahoma, 2004). Postdoctoral work included the National Center for Atmospheric Research (2017–2018) and University of South Florida (2015–2017). Teaching spans hazards geography, GIS analysis, and GeoAI. Courses like GIS 4324/6325 and GEO 2006 emphasize geospatial data analysis and decision-making frameworks. His funded projects include a NSF NCAR/UCAR grant for weather warning frameworks and NOAA-funded studies on tornado sheltering during the pandemic. Key research themes include climate mobility, socio-hydrology, and probabilistic weather communication. The CRASH Lab collaborates across disciplines to address adaptation strategies for vulnerable populations in hazard-prone regions. His publications often bridge physical and social sciences, highlighting geospatial tools for resilience planning. Advising current graduate students include Donal Bissainte, Michelle Ruiz, Jawata Saba, and Christopher Williams. Recent advisee Caley Feemster contributed to tornado warning design studies. Labs/Teams: CRASH Lab (co-led), Florida Climate Institute affiliate.

Rajagopalan Balajiمشاهده پروفایل

استاد

• Hydroclimate Modeling
• Water Resources Management
• Climate Variability
• +۴ مورد دیگر

Rajagopalan Balaji is a Professor and Chair in the Department of Civil, Environmental, and Architectural Engineering at the University of Colorado Boulder, with a fellowship at the Cooperative Institute for Research in Environmental Sciences (CIRES). His work bridges climate science and water resources engineering, focusing on sustainable water management under climate variability. Education: B.Tech from NIT Kurukshetra (1989), M.Tech from Indian Statistical Institute (1991), and Ph.D. in Stochastic Hydroclimatology from Utah State University (1995). Research Themes: Climate drivers of hydrology, ensemble hydroclimate projections, decision support systems, Indian monsoon variability, big-data techniques, and Arctic sea-ice dynamics. Scientific Contributions: Over 50 peer-reviewed publications, including work on Science (2005) and Geophysical Research Letters (multiple). His Google Scholar articles (2025-2020) emphasize wildfire impacts on water quality, Bayesian forecasting models, and global lake storage trends. Awards: Devendra Lal Memorial Medal (2021), CIRES Fellow (2001-present). Students: Supervised 11 M.S. and Ph.D. students, including Katrina Grantz (Ph.D. 2005) and James Prairie (Ph.D. 2005). Applied Interests: Climate-informed reservoir operations, construction safety analytics, and paleoclimate reconstructions for modern water planning. His team develops tools like the SCHAAKE Shuffle for weather resampling.

Peyman Afzali Gorouhمشاهده پروفایل

پژوهشگر

• Power Engineering
• Smart Grids
• Renewable Energy Systems
• +۵ مورد دیگر

Peyman Afzali Gorouh is a Postdoctoral Researcher in the Applied Power Electronic Systems group within the Faculty of Engineering and Science at Aalborg University, Denmark. His research focuses on developing innovative models for energy communities, smart grids, and renewable energy integration. Dr. Afzali's research interests span power engineering, smart grid technologies, renewable energy systems, and energy communities. His work particularly emphasizes prosumer economics, peer-to-peer energy trading, risk modeling in power systems, and energy democracy frameworks. He has developed novel approaches for optimizing energy communities while considering socio-economic-environmental factors, demand response, and uncertainty management. His recent publications (2020-2024) demonstrate a consistent focus on energy community modeling, with particular emphasis on peer-to-peer trading mechanisms, risk-constrained optimization, and multi-objective planning. His work bridges technical power system challenges with socio-economic considerations, creating integrated models that address both engineering and human aspects of modern energy systems. Dr. Afzali maintains an active research profile with numerous publications in high-impact journals including IEEE Transactions on Engineering Management, Energy and Buildings, Applied Sciences, and Sustainable Cities and Society. His research shows strong international collaboration, particularly with researchers from Iranian institutions.