جست‌وجوی استاد و پژوهشگر

Irene Scopellitiمشاهده پروفایل

استاد

• Consumer Behavior
• Decision Theory
• Marketing
• +۳ مورد دیگر

Professor Irene Scopelliti holds the position of Professor of Marketing and Behavioural Science at Bayes Business School (formerly Cass) within the Faculty of Management at City St George's, University of London. She leads the Marketing Group and co-directs the Behavioural Research Lab. Her research focuses on consumer psychology, judgment, and decision-making, with notable contributions to areas such as social norms, cognitive biases, and behavioral interventions. She has a PhD from Bocconi University and has held positions at Carnegie Mellon University and various visiting roles internationally. Education: BA in Music, Conservatorio di Musica, Italy MSc in Economics and Management, University of Calabria, Italy PhD in Management (Marketing), Bocconi University, Italy Research interests span consumer behavior, decision theory, and organizational behavior. Notable work includes studies on food consumption norms, gamification in savings goals, and gender differences in self-promotion. Her findings have been featured in outlets like Psychological Science , Management Science , and media like BBC News and Forbes . Awards include the Academy of Management Best Paper Proceeding (2016), Cass Business School Research and Enterprise Prize (2015), and recognition from the AMA Sheth Doctoral Consortium (2009). She has also contributed to academic leadership roles, including REF lead for the Faculty of Management and Behavioral Research Pool Director. Her teaching includes analytical methods for marketing at the MSc level and experimental design in the PhD program. She collaborates with institutions such as the University of Klagenfurt and University of Calabria, emphasizing interdisciplinary approaches to behavioral science.

Yong Chenمشاهده پروفایل

استاد

• Fisheries Ecology
• Stock Assessment
• Population and Ecosystem Dynamics
• +۳ مورد دیگر

Yong Chen is a Professor at the School of Marine and Atmospheric Sciences (SoMAS), Stony Brook University. He specializes in fisheries ecology, stock assessment, and climate change impacts on marine ecosystems. His research focuses on optimizing monitoring programs, evaluating fisheries management strategies, and understanding ecosystem dynamics under climate change. Education: Ph.D. from the University of Toronto (1995) Research Interests: Dr. Chen’s work addresses critical challenges in fisheries management, including stock assessment methodologies, climate-driven shifts in species distribution, and the integration of ecological and socio-economic factors into conservation strategies. His studies often involve advanced modeling techniques such as Ecopath with Ecosim and habitat suitability analysis. Key Themes in Publications: Recent articles highlight his focus on hybrid management strategies for mixed fisheries, climate impacts on species phenology and connectivity, and the efficacy of marine protected areas. He emphasizes data integration challenges and the development of decision support tools for sustainable fisheries. Grants and Advising: No specific grants or advisees are listed here. However, his research has likely involved collaborations with international fisheries organizations and government agencies. Labs/Teams: A lab site is referenced in his profile, though the specific team structure or ongoing projects are not detailed in the provided text.

David Wanikمشاهده پروفایل

استادیار

• Data Science
• Natural Hazards
• Remote Sensing
• +۳ مورد دیگر

David Wanik is an Assistant Professor in the Department of Operations and Information Management and Associated Faculty in the Department of Civil and Environmental Engineering at the University of Connecticut. He serves as Academic Director for Business Data Analytics at the Stamford campus and conducts research in the Eversource Energy Center, focusing on data science, natural hazards, remote sensing, and IoT applications in utility systems. PhD, MS, and BS in Environmental Engineering from University of Connecticut His research bridges natural hazard prediction, power grid resilience, and environmental data science. Key themes include: Machine learning for power outage prediction Climate change impact on energy demand Remote sensing for population and environmental monitoring IoT-enabled infrastructure hardening Recent publications emphasize deep learning for nighttime light imagery analysis, hybrid physics-data-driven models for grid resilience, and climate-integrated demand forecasting. His work integrates satellite data, LiDAR, and utility infrastructure records for predictive analytics. Teaching includes courses in business analytics, Python-based data science, and deep learning for the MS Business Analytics and Project Management program.

Zoe Liمشاهده پروفایل

دانشیار

• Uncertainty Analysis
• Risk Management
• Stochastic Modelling
• +۷ مورد دیگر

Dr. Zoe Li is an Associate Professor in the Department of Civil Engineering at McMaster University, with an additional role as an Associate Member in the Department of Computing and Software. She specializes in developing modeling and decision-support tools to address challenges in water resources management, environmental systems analysis, and climate change impacts. Her research focuses on hydrological modeling, probabilistic forecasting, risk analysis, and environmental systems optimization. She holds a B.Eng. from China and M.A.Sc./Ph.D. degrees from the University of Regina. Her work spans interdisciplinary collaborations, including studies on dam safety under climate change, wastewater treatment plant optimization, and AI-driven environmental monitoring. She has been actively involved in projects such as CityDNA, a digital tool to model urban environments for decision-making during crises like the pandemic. Dr. Li teaches courses in environmental systems engineering and principles of environmental engineering, emphasizing uncertainty quantification and sustainable practices. Her research publications (15+ recent articles) address topics like machine learning applications in environmental systems, climate change impacts on water resources, and infrastructure resilience. She advises graduate students in environmental engineering and systems optimization. Notable grants include funding from Roche Canada for pandemic-related urban modeling. Her work is frequently published in high-impact journals like Journal of Environmental Management and Water Resources Research .

Saleh Taghvaeianمشاهده پروفایل

دانشیار

• Irrigation Engineering
• Water Resources Management
• Precision Agriculture
• +۴ مورد دیگر

Saleh Taghvaeian is an Associate Professor in the Department of Biological Systems Engineering at the University of Nebraska-Lincoln and a Faculty Fellow at the Daugherty Water for Food Global Institute. His research focuses on precision irrigation systems, water resource management, and climate-resilient agricultural practices. He holds a Ph.D. in Irrigation Engineering from Utah State University and academic degrees from Ferdowsi University of Mashhad, Iran. Education: Ph.D., Irrigation Engineering, Utah State University M.S., Irrigation Engineering, Ferdowsi University of Mashhad, Iran B.S., Irrigation Engineering, Ferdowsi University of Mashhad, Iran Research Interests: His work integrates remote sensing, hydrological modeling, and machine learning to address challenges in irrigation efficiency, drought response, and sustainable water use. Key areas include soil moisture dynamics, crop water productivity, and the application of big data in agricultural systems. Publications Trends: Recent articles emphasize GRACE data downscaled analysis for water storage monitoring, AquaCrop modeling for crop performance under water stress, and machine learning applications in precision agriculture. His work spans transboundary water basins (Indus), U.S. High Plains, and Oklahoma Panhandle regions. Awards: 2021 Oklahoma State University Distinguished Early Career Faculty Award 2019 ASABE Larry W. Turner Young Extension Professional Award 2018 Oklahoma Cooperative Extension Service Honor Award Grants and Advising: Leads research projects on irrigation energy conservation, soil salinity mitigation, and agricultural drought resilience. Collaborates with institutions like USDA, UCOWR, and international partners on transboundary water management. Labs/Teams: Active in Nebraska's Water for Food Institute, leading interdisciplinary teams developing decision-support tools for irrigators and policymakers. Engaged in extension programs promoting smart irrigation technologies and water policy advocacy.

• Physical Limnology
• Sediment Transport
• Tidal Hydrodynamics
• +۳ مورد دیگر

Marco Toffolon is a Full Professor at the University of Trento's Department of Civil, Environmental and Mechanical Engineering, where he leads the Physical Limnology Laboratory. He serves as Deputy Director for International Relations and previously directed the Environmental Engineering programs. His research spans ecohydraulics, sediment transport, lake hydrodynamics, and environmental modeling. He investigates physical limnology, tidal morphodynamics, and stratified flows using analytical and numerical approaches. His work integrates field measurements with machine learning for water quality prediction and climate impact assessment. His publications focus on lake dynamics, river morphodynamics, and sustainable water management, with recent emphasis on climate-driven changes in alpine systems. Research demonstrates strong interdisciplinary linkages between hydraulics, ecology, and climate science. Awards: 2016 Coastal Engineering Journal Award 2013 Enrico Marchi Lecture invitation He leads international collaborations with institutions like EPFL and Sun Yat-sen University, and organizes conferences including the Physical Processes in Natural Waters workshop series.

Yulia Gelمشاهده پروفایل

استاد

• Uncertainty Quantification
• Artificial Intelligence
• Topological Data Analysis
• +۶ مورد دیگر

Yulia Gel is a Professor in the Department of Statistics at Virginia Tech and serves as a Part-Time Program Director-Expert at the National Science Foundation (NSF). She holds a MSc (summa cum laude) and PhD in Mathematics from Saint Petersburg State University (Russia) and completed a postdoc in Statistics at the University of Washington. Her research focuses on uncertainty quantification in AI, statistical foundations of data science, spatio-temporal processes, and applications in climate science, healthcare, and blockchain analytics. She has received prestigious awards including the NSF Director’s Award (2023), ASA Distinguished Achievement Medal (2018), and TIES Abdel El-Shaarawi Award (2014). Gel has led grants on wildfire prediction, climate informatics, and blockchain data science. She serves on editorial boards of Statistica Sinica, Electronic Journal of Statistics, and Technometrics, and organizes workshops on AI for climate sustainability and fragile Earth systems. Her research group develops topological and geometric methods for graph neural networks, with applications to digital twins, environmental justice, and public health. Education: MSc (1997), PhD (2000) in Mathematics from Saint Petersburg State University; Postdoc in Statistics at University of Washington (2001–2003). Past roles include Professor at University of Texas at Dallas (2015–2024) and Associate Professor at University of Waterloo (2004–2014). Selected visiting positions include NASA Jet Propulsion Lab (2016–2017) and Isaac Newton Institute (2016–2017). She has pioneered statistical software packages like snowboot and funtimes for network inference and time-series analysis. Awards highlight her contributions to environmetrics and statistical methodologies. Current projects include NSF-funded research on AI-driven wildfire prediction and blockchain analytics for climate resilience. Her lab’s recent work emphasizes topological methods (e.g., zigzag persistence) for graph-based forecasting and adversarial robustness.

• Nonlinear Dynamics
• Structural Dynamics
• Vibration Control
• +۳ مورد دیگر

Professor David Wagg is a Professor of Nonlinear Dynamics and Departmental Director of Research and Innovation at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. His research focuses on nonlinear structural dynamics, digital twins, vibration suppression, and real-time hybrid testing. He holds a BEng and PhD from University College London and previously served as a Professor at the University of Bristol (2008–2013). Notable awards include the EPSRC Advanced Research Fellowship (2004–2009). Education: BEng and PhD in Nonlinear Dynamics from University College London. Research Interests: Digital twins for dynamics applications, nonlinear structural dynamics, vibration control, real-time hybrid testing, and identification methods for nonlinear dynamics. His work emphasizes applying nonlinear models and control strategies to engineering challenges like wind turbines and large civil infrastructure. Grants & Leadership: Co-Investigator for EPSRC grants on CITCoM and Digitwin, coordinator of the Marie Curie ETN DyVirt, and PI for the EPSRC programme on Engineering Nonlinearity (2012–2017). He co-authored Nonlinear Vibration with Control (2015) and edited books on structural dynamics. Lab/Teams: Involved in the Laboratory for Verification and Validation (LVV) and leads research groups focused on digital twin applications, inerter-based systems, and structural health monitoring.

Ana Lucicمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Interpretable Machine Learning
• +۶ مورد دیگر

Dr. Ana Lucic is an Assistant Professor at the University of Amsterdam , holding a joint appointment between the Institute for Logic, Language, and Computation (ILLC) and the Informatics Institute . Her research focuses on interpretable machine learning for applications in science and society, with emphasis on Earth system modeling and AI for environmental forecasting . PhD in Explainable Machine Learning (University of Amsterdam, 2022) MSc/BSc in Mathematics (McMaster University, Canada) Former researcher at Microsoft Research AI for Science and Partnership on AI Her recent work includes Aurora , a foundation model for Earth system forecasting published in Nature , and Clifford-Steerable CNNs at ICML 2024. Ana actively mentors PhD students and leads projects in mechanistic interpretability and geospatial machine learning . Scientific awards include top placements in ML competitions. She contributes to open science through reproducibility initiatives and collaborates with AI for climate consortia.

Erica R.H. Fuchsمشاهده پروفایل

استاد

• Technology Policy
• Global Manufacturing
• Innovation Policy
• +۳ مورد دیگر

Erica R.H. Fuchs is the Kavčić-Moura Professor in the Department of Engineering and Public Policy at Carnegie Mellon University (CMU), directing the Critical Technology Initiative (CTI). She holds courtesy faculty positions in Materials Science and Engineering and the Heinz College. Her research focuses on emerging technology development, commercialization, and global manufacturing, with emphasis on national policy implications. Fuchs leads interdisciplinary efforts at CTI to advance critical technology assessment frameworks, ensuring smart investments and policies for national security and economic competitiveness. Formerly, she directed the Manufacturing Futures Initiative, now an endowed institute at CMU. Education: She earned a Ph.D. (2006), M.Sc. (2003), and B.Sc. (1999) in Engineering Systems, Technology Policy, and Materials Science from MIT. Post-MIT, she was a UNIDO fellow in Beijing. Research Interests: Global innovation policy, technology commercialization pathways, and the intersection of technology with economic and security objectives. She authored influential works like the 2021 report *Securing America’s Future*, advocating for a National Technology Strategy to align multi-objective outcomes (security, equity, prosperity). Key Contributions: Catalyzed the National Network for Critical Technology Assessment, mobilizing 13+ universities to address technology gaps. Testified in Congress on supply chain resilience, EV battery policies, and semiconductor strategies. Advises entities like the National Semiconductor Technology Center and MIT’s Institute for Data, Systems, and Society. Affiliations: National Bureau of Economic Research (Research Associate), National Institute of Standards and Technology (NSTC Board), and Brookings Institution panelist. Her work is frequently cited in *Axios*, *Bloomberg*, and the *New York Times*.

Xin Ningمشاهده پروفایل

استادیار

• Soft electronics for aerospace engineering
• Bio-inspired aerospace structures
• In-space manufacturing and assembly
• +۱ مورد دیگر

Xin Ning is an Assistant Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC), where he also holds appointments in the Materials Research Laboratory. Previously, he served as an Assistant Professor at Pennsylvania State University from 2018 to 2023. His academic journey includes postdoctoral research at UIUC and California Institute of Technology (Caltech). Educated at Caltech, he earned a Ph.D. in Aeronautics in 2015 and an M.S. in Aeronautics in 2010. His research focuses on soft electronics for aerospace engineering , bio-inspired aerospace structures , in-space manufacturing and assembly , and multifunctional space structures . These interests drive innovations in lightweight, adaptive, and multifunctional materials and systems for aerospace applications. For instance, his work explores bio-inspired cellular materials for aircraft wings and bistable composite booms for deployable structures. He has been recognized with several honors, including the 2022 Young Investigator Award from the Office of Naval Research, 2019 Haythornthwaite Foundation Research Initiation Award, 2015 William F. Ballhaus Prize from Caltech, and the 2012 Dow-Resnick Fellowship. In addition to research, Professor Ning teaches courses such as AE 323: Applied Aerospace Structures and AE 498: Space Structures . While specific grants are not detailed here, his work has been supported through awards like the ONR Young Investigator grant. He collaborates with the Materials Research Laboratory at UIUC and engages in interdisciplinary projects involving soft electronics and bio-inspired engineering.

Emily Blackمشاهده پروفایل

استاد

• Climate change
• Climatology
• Precipitation
• +۷ مورد دیگر

Dr. Emily Black is a Professor of terrestrial processes and climate at the University of Reading's Department of Meteorology, where she serves as research division lead for Earth Observation and Space and is a senior scientist at the National Centre for Atmospheric Science (NCAS). She leads the TAMSAT programme (Tropical Applications of Meteorology using SATellite data and ground-based observations), which provides real-time rainfall products and soil moisture forecasts to stakeholders across Africa through the TAMSAT-ALERT system. Her work bridges fundamental climate science with practical applications for climate risk management, particularly in vulnerable African communities. Dr. Black's research focuses on the hydrological cycle and its associated hazards, land-atmosphere interactions and their impact on climate, African climate and rainfall monitoring, and soil moisture monitoring and forecasting. She has established herself as a leading expert in African climate systems, with particular expertise in understanding rainfall patterns, drought mechanisms, and the development of forecasting tools that translate scientific knowledge into actionable information for decision-makers. Her work combines observational analysis, modeling approaches, and direct engagement with stakeholders to ensure scientific outputs address real-world needs. Analysis of Dr. Black's recent publications reveals a strong focus on the practical application of climate science for risk management, particularly through the TAMSAT-ALERT system. Her work spans multiple disciplines including climatology, hydrology, meteorology, and agricultural science, with consistent emphasis on African contexts. The research shows evolving sophistication in forecasting techniques, moving from basic rainfall monitoring to integrated systems that predict soil moisture, agricultural impacts, and drought risks. A notable trend is the increasing integration of user needs into scientific development, reflecting her commitment to user-driven science and knowledge exchange. Dr. Black has built an extensive collaborative network across institutions globally, with frequent co-authors including Richard P. Allan, Tristan Quaife, Brian J. Hoskins, Pier Luigi Vidale, and Julia Slingo, all from the University of Reading. Her work has been cited by numerous leading climate scientists worldwide, demonstrating her significant impact on the field. She has secured funding for multiple projects focused on climate monitoring, forecasting, and risk management in Africa, with particular emphasis on agricultural applications and drought resilience. As leader of the TAMSAT programme, Dr. Black oversees a team that combines satellite data analysis, ground-based observations, and modeling expertise to develop climate services specifically tailored for African contexts. The TAMSAT-ALERT system represents a major advancement in seasonal forecasting capabilities for the continent, providing critical information for agricultural planning and disaster risk management. Her team's work has evolved from basic rainfall monitoring to integrated systems that predict soil moisture, crop conditions, and drought risks, demonstrating continuous innovation in climate service development.

Chaopeng Shenمشاهده پروفایل

استاد

• Hydrology
• Deep Learning
• Physics-Informed Machine Learning
• +۹ مورد دیگر

Chaopeng Shen is a Professor in the Department of Civil and Environmental Engineering at Pennsylvania State University. His research bridges hydrology with state-of-the-art deep learning and differentiable modeling techniques, focusing on advancing our understanding of hydrologic cycles and their interactions with ecosystems, energy, and carbon cycles. He leads the Multi-scale Hydrology, Processes and Intelligence group (MHPI) and has developed the Process-based Adaptive Watershed Simulator (PAWS) for large-scale hydrologic modeling. Shen's work emphasizes physics-informed machine learning , where deep learning components are integrated with process-based equations through differentiable modeling. This approach enables training neural networks using big data while respecting physical laws, leading to improved generalizability and robustness. His group has demonstrated advantages of differentiable models in rainfall-runoff prediction, routing, ecosystem modeling, and water quality studies. Notably, his team's deepLDB project addresses landslide prediction using AI and big datasets. Recent publications highlight his contributions to global water modeling (grid-LSTM, differentiable Muskingum-Cunge routing), extreme flood forecasting (probabilistic diffusion models), and hydrologic uncertainty quantification . Shen actively engages in interdisciplinary collaborations through the PRISM Cooperative Institute, which aims to integrate multi-domain data for systemic risk assessment. His group has advised students including Dapeng Feng, Wen-Ping Tsai, Kuai Fang, Xinye Ji, and Tasnuva Mahjabin. Shen's research is supported by the National Science Foundation (NSF), Department of Energy (DoE), USGS, Google.org, and the Gates Foundation. He serves as Editor for the Journal of Geophysical Research - Machine Learning & Computation and Chief Editor for Frontiers in Water: Water & AI. His open-source software tools like PAWS and deepLDB are available through dedicated project websites.

• Nanotechnology
• Materials Science
• Environmental Science
• +۷ مورد دیگر

Giuseppe Cavallaro is an Associate Professor at the Department of Physics and Chemistry , University of Palermo. His research focuses on nanotechnology , biopolymer composites , and cultural heritage conservation . Key research themes include: Halloysite clay nanotubes for drug delivery and pollutant removal Hybrid materials integrating chitosan , cellulose , and metal oxides Applications in sustainable agriculture , art conservation , and environmental decontamination Recent publications highlight his work on thermoresponsive nanocarriers , antimicrobial composites , and green building materials . Contact: giuseppe.cavallaro@unipa.it

• Materials Engineering
• Wood Science
• Biomaterials
• +۴ مورد دیگر

Lauri Rautkari is an Associate Professor in the Department of Bioproducts and Biosystems at Aalto University, Finland. His research focuses on water interactions in biomaterials, particularly wood, with an emphasis on developing advanced analytical methods for water vapor sorption, creating novel low-sorption materials, and investigating hygroscopicity and fungal decay resistance in modified wood systems. Research Highlights: Gas-phase ozone treatment for improved wettability, thermal and chemical wood modification, hyperspectral imaging for moisture prediction, bioinspired coatings for fungal protection, and interlaboratory studies on sorption data quality. Recent Publications: Key contributions to understanding lignin's role in moisture interactions, acetylation reversibility, and the impact of fungal degradation on heat-treated wood. The trend in his publications reflects a strong focus on hygroscopicity, chemical modification techniques (acetylation, melamine-formaldehyde impregnation), advanced imaging methods (hyperspectral, neutron scattering), and the development of sustainable wood-based materials for construction and acoustic applications. Collaborative interlaboratory efforts dominate his work, ensuring standardized methodologies for moisture analysis.