جست‌وجوی استاد و پژوهشگر

Ramon Leon Gonzalezمشاهده پروفایل

استاد

• Agricultural Weed Management
• Weed Ecology
• Crop-Livestock Systems
• +۴ مورد دیگر

Ramon Leon Gonzalez is the William Neal Reynolds Distinguished Professor and University Faculty Scholar at North Carolina State University, leading the Weed Biology and Ecology department. As Director of Graduate Programs, he oversees research focused on understanding how agricultural practices influence weed behavior and developing sustainable management strategies. His work integrates ecological principles with technological innovations like 3D imaging and machine learning for precision agriculture. His research emphasizes crop-weed interactions, herbicide resistance, cover crop breeding, and the impacts of climate variation on weed suppression. Notable projects include studying Palmer amaranth resistance evolution, cereal rye cover crop dynamics, and robotic data collection systems for biomass estimation. He collaborates across 16 U.S. states in cover crop assessments and leads efforts to develop PROTAC-based weed control biotechnology. Key achievements include establishing the Weed Biology and Ecology Laboratory and pioneering integrated approaches to seedbank management. Despite no explicitly listed students, his involvement in graduate program leadership suggests active academic mentoring. Awards include prestigious university distinctions reflecting his contributions to agricultural science. Recent articles highlight advancements in robotic platforms for weed detection, molecular analysis of herbicide resistance, and critical period modeling for grass weed control. His work bridges traditional agronomy with cutting-edge technologies, addressing both practical farm challenges and long-term ecological sustainability.

Stephanie Clelandمشاهده پروفایل

استادیار

• Environmental Health
• Climate Change
• Environmental Epidemiology
• +۶ مورد دیگر

Dr. Stephanie Cleland is an Assistant Professor and the Legacy for Airway Health Chair in Promotion of Lung Health at Simon Fraser University's Faculty of Health Sciences (since September 2023). She is also a research scientist at the Legacy for Airway Health at Vancouver Coastal Health Research Institute. Her work focuses on evaluating health impacts of climate change-related environmental hazards like wildfire smoke and extreme heat through environmental epidemiology and exposure assessments. Dr. Cleland holds a PhD and MSPH in Environmental Sciences and Engineering from the University of North Carolina at Chapel Hill, and a BS in Computer Science and Community Health from Tufts University. Her postdoctoral research included a fellowship at the U.S. Environmental Protection Agency. Her research interests include Climate change-driven environmental exposures GIS/spatiotemporal exposure modeling Health equity in environmental risks Science communication and public health outreach She emphasizes identifying vulnerable populations and developing strategies to enhance community resilience against climate-related health threats. Her methodological strengths include advanced statistical modeling, health impact assessments, and interdisciplinary collaboration.

• Climate Change
• Atmospheric Science
• Data Science
• +۳ مورد دیگر

Megan Lickley is an Assistant Professor at Georgetown University, holding dual appointments in the Graduate Earth Commons and the Edmund A. Walsh School of Foreign Service . Her research focuses on the drivers and impacts of climate change, integrating atmospheric science, mathematics, and policy to assess outcomes such as water resource management, rapid warming durations, and sea level change. She has contributed to the International Ozone Assessment , analyzing compliance with the Montreal Protocol and its implications for ozone-depleting substances and greenhouse gases. Dr. Lickley earned her Ph.D. from MIT and has extensive international experience: she taught mathematics in the Democratic Republic of Congo at the Catholic University of Bukavu and consulted for the World Bank in Uganda on climate change impact reports. Her work bridges disciplinary boundaries, employing Bayesian modeling and statistical frameworks to address global environmental challenges. Her research highlights include evaluating halocarbon emissions, stratospheric halogen levels, and the timing of precipitation change signals using advanced statistical methods. She has also explored adaptive water supply planning under climate uncertainties, emphasizing the role of learning in infrastructure resilience. Her findings underscore the urgency of policy-driven mitigation strategies and equity-focused adaptation measures in climate-sensitive sectors. Notably absent from her profile are formal lists of students or named awards, though her contributions to international climate assessments reflect her scholarly impact. Her work spans theoretical modeling, policy analysis, and applied environmental research, addressing both scientific and societal dimensions of climate change.

Charles Jonesمشاهده پروفایل

استاد

• Climate Science
• Meteorology
• Wildfire Risk Analysis
• +۵ مورد دیگر

Charles Jones is a Professor in the Department of Geography at the University of California, Santa Barbara. His research focuses on climate variability, extreme weather events, wildfire risk analysis, and regional climate modeling. He leads the Climate Variations and Changes (CLIVAC) research group and has advised multiple graduate students. Key areas of study include precipitation patterns, monsoon systems, and the impacts of climate change on California wildfires. Jones has conducted extensive research on downslope windstorms, Santa Ana winds, and heat stress in agricultural regions like the Imperial Valley. His work integrates high-resolution weather modeling, observational campaigns (e.g., SWEX), and interdisciplinary approaches to address climate risks. Research interests include the Madden-Julian Oscillation, atmospheric rivers, and the South American Low-Level Jet. He has published over 100 peer-reviewed articles and contributed to projects like the Sundowner Winds Experiment. CLIVAC explores climate extremes, fire-weather interactions, and the application of machine learning for predictive modeling. His team collaborates on wildfire mitigation strategies and climate adaptation in vulnerable regions. Notable projects include evaluating HRRR wind forecasts during Santa Ana events and analyzing fuel treatments' effectiveness in reducing fire severity. Jones' work bridges meteorology, climatology, and environmental science to address real-world challenges such as heat stress in agriculture and urban climate resilience.

Sebastian Engelkeمشاهده پروفایل

دانشیار

• Extreme Value Theory
• Spatial Statistics
• Graphical Models
• +۵ مورد دیگر

Sebastian Engelke is an Associate Professor at the Research Center for Statistics at the University of Geneva. His research focuses on extreme value theory, spatial statistics, graphical models, and machine learning applications in climate science and risk assessment. He holds an SNSF Eccellenza Grant and has contributed to foundational work on extremal graphical models and causal inference in heavy-tailed systems. Affiliations: University of Geneva, Research Center for Statistics Grants: SNSF Eccellenza Grant (2020–2025), Ambizione Fellowship (2015–2018) Education: PhD in Mathematics (2013, Georg-August-University of Göttingen), studies at UC Berkeley and University of Göttingen. Research Interests Engelke’s work bridges extreme value theory with modern machine learning, addressing challenges in climate extremes, risk quantification, and graphical model structures. Key areas include: Statistical modeling of multivariate extremes Causal discovery in heavy-tailed distributions Applications in environmental science and climate informatics Key Contributions Recent work includes advancements in extremal graphical models (via matrix completions), neural network approaches for extreme quantile regression, and validation methods for deep learning weather models. His research is published in top journals like Annals of Statistics and Journal of the American Statistical Association . Awards & Recognition Lambert Award (2021) Gumbel Lecture (2023) Fields Research Fellowship (2019) Teaching & Supervision Engelke teaches courses on machine learning, probability, and advanced topics in statistics at the University of Geneva. He supervises PhD students and postdocs in machine learning and extreme value theory. His students include Edoardo Vignotto (extremal random forests) and Nicola Gnecco (causal discovery in heavy-tailed models).

Christopher Osburnمشاهده پروفایل

استاد

• Aquatic Biogeochemistry
• Coastal Carbon Cycling
• Photochemical Degradation of Organic Matter
• +۳ مورد دیگر

Christopher Osburn is a Professor and Director of the Blue Economy Innovation Program at North Carolina State University (NCSU). His research focuses on aquatic biogeochemistry, effects of extreme weather on coastal carbon cycling, and microbial/photochemical degradation of organic matter. He holds a Ph.D. in Earth and Environmental Sciences from Lehigh University (2000) and B.A./B.S. degrees in Geological Sciences and Public Affairs from Indiana University (1991, 1995). Dr. Osburn’s work addresses how climatic events like tropical cyclones influence coastal ecosystems, particularly in North Carolina. He employs advanced analytical techniques (e.g., fluorescence spectroscopy, machine learning) to study dissolved organic matter (DOM) sources, transformations, and transport. His contributions include developing pan-Arctic DOC estimation algorithms and frameworks for DOM source apportionment. Key Research Themes: Coastal carbon cycling, DOM dynamics, climate change impacts, estuarine biogeochemistry Major Projects: Hurricane-driven carbon flux studies, Arctic DOC modeling, seagrass meadow biogeochemistry He has received the University Faculty Scholar award and authored over 60 peer-reviewed articles. Current efforts focus on integrating remote sensing and field data to improve coastal ecosystem monitoring.

Yuanzhu Zhanمشاهده پروفایل

دانشیار

• Operations Management
• Supply Chain Management
• Big Data and Analytics
• +۷ مورد دیگر

Yuanzhu Zhan is an Associate Professor in Operations and Supply Chain Management at the University of Birmingham's Birmingham Business School, holding the Department of Management's PGR Lead role. Previously, he served as Programme Director for the BSc Business Management (PT) program in Singapore (2021/22). He holds a PhD and MSc from the University of Nottingham, specializing in Risk Management and Business Management. His research focuses on emerging technologies' impacts on operations, innovation, and sustainability, with notable contributions to blockchain governance, AI-driven supply chains, and circular economy frameworks. He co-edits special issues on 'Blockchain in Operations' (International Journal of Production Economics) and 'Generative AI in Digital Platforms' (IEEE Transactions on Engineering Management). Editorial Roles: Associate Editor of Journal of Operations Management, Department Editor of IEEE TEM, Board Member of IJOPM/IJPE/IMDS Awards: 2024 Best Reviewer (JOM), 2022 Emerald Award (IMDS), 2018 Early Career Award (ULMS) Funding: Secured grants from British Academy/Leverhulme Trust, NSFC, and MSI Key Projects: Blockchain-enabled social media platforms, AI in healthcare logistics, electric vehicles for net-zero Zhan's teaching expertise spans Operations Management and Business Analytics at both undergraduate and postgraduate levels. He is a certified expert in Big Data Analytics and actively supervises PhD candidates in technology-driven innovation and sustainable supply chains.

Chris Buddمشاهده پروفایل

استاد

• Applied Mathematics
• Climate Modeling
• Numerical Weather Prediction
• +۵ مورد دیگر

Chris Budd is a Professor at the University of Bath's Department of Mathematical Sciences, affiliated with research centers such as the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa) and the Probability Laboratory at Bath. His research focuses on interdisciplinary applied mathematics, including numerical weather prediction, climate modeling, and collaborations with industries like energy and aerospace. He holds roles as Professor of Mathematics at the Royal Institution and Vice-President of the Institute of Mathematics and its Applications. Budd has received awards, including the Knowledge Transfer Award and the 2020 Joint Policy Board Communications for Mathematics Award. His work bridges theoretical and practical applications, emphasizing public engagement through initiatives like the Bath Taps Into Science Festival. Research interests span complex nonlinear systems, climate dynamics, and machine learning applications in scientific modeling. Recent projects include climate modeling networks like CliMathNet and collaborations on sustainable development goals. His contributions to numerical methods, such as adaptive mesh refinement and optimal transport techniques, enhance weather and climate forecasting accuracy. Budd’s engagement with policymakers and public science communication underscores his commitment to translating mathematical insights into societal impact. Key Projects: REMODEL (EPSRC), Electro-mechanical modeling (Innovate UK), Climate Science Citizen Science projects. Awards: Knowledge Transfer Award (Met Office), 2020 Joint Policy Board Communications Award. Labs/Teams: SAMBa, Probability Laboratory, Institute for Mathematical Innovation (IMI).

• Aerospace Engineering
• Optimal Control Theory
• Air Traffic Management
• +۵ مورد دیگر

Manuel Fernando Soler Arnedo is a Full Professor in the Aerospace Engineering Department at Carlos III University of Madrid's College of Engineering. His research focuses on Aerospace Engineering with specialization in Optimal Control Theory , Climate Impact Mitigation , and Artificial Intelligence applications for air traffic systems. He leads the Aerospace Engineering Research Group and has contributed extensively to Flight Trajectory Optimization , Weather-Induced Uncertainty , and Network-scale Conflict Resolution . Principal Researcher on EU-funded projects like F4EClim (2024-2027) and KAIROS (2023-2026) Key international collaborations with NEXTOR (UC Berkeley) and ETH Zurich Developed tools like CLIMaCCF V1.0 and ROOST V1.0 for climate-aware flight planning His work integrates Artificial Intelligence with Climate Modeling to address 4D Trajectory Planning , Thunderstorm Avoidance , and Non-CO2 Emission Reduction in aviation. Recent publications emphasize Robust Optimization under meteorological uncertainty and Deep Learning for traffic flow management. He has supervised theses on Data Science for Weather Mitigation and Multi-objective Space Mission Design , with grants from European Commission , Boeing , and Spanish government agencies .

• Marine Environmental Chemistry
• Microplastics and Nanoplastics
• Pollution Dynamics
• +۳ مورد دیگر

Martin Hassellöv is a Professor at the Department of Marine Sciences, University of Gothenburg. His research focuses on marine environmental nanochemistry, particularly the study of marine pollution in solid forms, including microplastics, nanoparticles, and their interactions with ecosystems. He leads a research group investigating pollution dynamics across scales, from nanometer-level processes to ecosystem-wide impacts. Key interests include ocean acidification, climate change effects, and pollution sources like shipping, road runoff, and industrial emissions. His work bridges analytical chemistry, environmental toxicology, and modeling. Notable contributions include studies on microplastic distribution in Arctic waters, ship-induced turbulence effects, and nanoparticle behavior in aquatic environments. He collaborates internationally on projects like the NanoFASE initiative, addressing nanomaterial fate and policy frameworks for plastic debris categorization. Publications highlight innovative methods for microplastic analysis (e.g., deep learning for spectral reconstruction) and interdisciplinary approaches to pollution monitoring. His research underscores urgent environmental challenges like exceeding planetary boundaries for novel entities (e.g., synthetic pollutants). Martin advises on policy-relevant topics, such as marine litter management and sustainable shipping practices. He has developed protocols for microplastic extraction from tissues and sediments, enhancing global monitoring capabilities.

• Aeroacoustics
• Noise Control Engineering
• Signal Processing
• +۳ مورد دیگر

Elias Zea Marcano is an Assistant Professor of Engineering Acoustics at the Marcus Wallenberg Laboratory for Sound and Vibration Research (MWL) at KTH Royal Institute of Technology. His research focuses on noise source separation, aeroacoustics, room acoustics, sparse signal processing, and data-driven methods. He reviews for prominent journals like the Journal of the Acoustical Society of America and serves as a Guest Editor for the Journal of Theoretical and Computational Acoustics. His work is supported by the Swedish Research Council and the European Commission. He teaches courses such as Room Acoustics and Spatial Audio and has supervised numerous graduate students and postdocs in areas like sustainable aviation noise reduction and acoustic material characterization. He actively participates in international conferences and publishes cutting-edge research on topics such as fan noise measurement and data-driven speech enhancement.

Kai Gaoمشاهده پروفایل

پژوهشگر ارشد

• Urban Climate Mitigation
• Climate Change Adaptation
• Thermal Comfort and Energy Efficiency
• +۳ مورد دیگر

Kai Gao is a Vice Chancellor’s Postdoctoral Research Fellow (Level A) at the School of PCPM, RMIT University. His research focuses on urban climate mitigation, climate change adaptation, and thermal comfort in built environments. Key areas include radiative cooling technologies, green infrastructure, HVAC systems optimization, and the impact of urban planning on heatwaves. Dr. Gao’s work addresses interdisciplinary challenges such as balancing energy efficiency with thermal comfort in high-rise housing, evaluating the efficacy of tree-planting initiatives, and leveraging machine learning for anomaly detection in climate data. His research often combines experimental and numerical methods, with applications in tropical and arid urban settings like Hong Kong and desert cities. No scientific awards or grants are explicitly mentioned in the provided texts. His Google Scholar profile indicates active publication in urban climate science and related engineering fields.

Roger H. Frenchمشاهده پروفایل

استاد

• Optical Properties of Materials
• Electronic Structure
• Photovoltaics
• +۴ مورد دیگر

Roger H. French is a Distinguished University Professor and Kyocera Professor of Ceramics at the Department of Materials Science and Engineering, Case School of Engineering, Case Western Reserve University. He holds a PhD from MIT and a BS from Cornell University. His research focuses on optical properties of materials, electronic structure analysis, long-range interactions, photovoltaic degradation science, and data-driven approaches to materials innovation. French leads major initiatives in solar energy systems and has pioneered the application of machine learning to photovoltaic performance prediction and material durability analysis. He chairs the IEEE Technical Committee on Solar Photovoltaic Energy Systems and serves on ASTM committees for renewable energy standards. His awards include the 2020 IEEE Faculty Distinguished Research Award and the Case School of Engineering Research Award. French has authored over 200 publications and holds patents in photovoltaic technologies and data science applications. His work integrates interdisciplinary research across materials science, computational methods, and energy systems, with notable contributions to photovoltaic module reliability, adhesion testing methodologies, and the design of next-generation solar materials. French also develops curricula in applied data science for engineering students, emphasizing practical data analytics in materials research.

• Climate Science
• Atmospheric Dynamics
• Extreme Events
• +۵ مورد دیگر

Dr. Vera Melinda Galfi is an Assistant Professor at the Institute for Environmental Studies (IVM) within the Faculty of Science at Vrije Universiteit Amsterdam. Her research focuses on atmospheric dynamics, extreme climate events, and the interplay between Rossby waves and heatwaves. She investigates compound weather hazards, climate variability, and geophysical fluid dynamics through interdisciplinary approaches combining statistical physics and dynamical systems theory. Her work examines phenomena such as Northern Hemisphere heatwaves, cut-off low systems, and teleconnection patterns, with applications to climate change impacts. Galfi collaborates internationally on projects analyzing climate predictability, extreme event statistics, and flood event dynamics. She teaches courses like 'Machine Learning for Graphs' and contributes to advancing climate science through peer-reviewed publications in journals such as Environmental Research Letters and Bulletin of the American Meteorological Society . Her research highlights include identifying Rossby wave roles in spatially compounding heatwaves and advancing understanding of Western European flood events' meteorological drivers. Galfi actively participates in global climate science networks, contributing to both theoretical and applied aspects of climate dynamics.

Lee How Chinhمشاهده پروفایل

مدرس ارشد

• Predictive Modelling
• Machine Learning
• Statistical Business Analysis
• +۶ مورد دیگر

Dr Lee How Chinh is a Senior Lecturer (Practice) in the Department of Econometrics and Business Statistics at the School of Business, Monash University Malaysia. He is actively involved in teaching, research, and industry collaboration, particularly in data science and analytics. Education: PhD in Statistics, Universiti Sains Malaysia Master of Applied Statistics, Universiti Putra Malaysia Master of Science in Mathematics, Universiti Kebangsaan Malaysia Bachelor of Science (Hons) in Mathematical Sciences, Universiti Kebangsaan Malaysia Dr Lee's research centers on applying statistical and machine learning methods to business and industrial problems. His key interests include predictive modeling, statistical business analysis, and anomaly detection in operational data. He emphasizes practical applications and bridges academia with industry through training and consultancy. The recent publications reflect a strong trend in statistical process control, AI-driven environmental modeling, and educational technology. His work combines theoretical rigor with real-world impact, particularly in quality control and data-driven decision-making. Scientific Awards and Recognitions: Hadiah Sanjungan from PERSAMA for PhD thesis Professional Technologist (MBOT) SAS Certified Professional: AI and Machine Learning Dr Lee actively supervises students and contributes to academic service as a peer reviewer for journals like IEEE Access and PLoS ONE. He is a chief investigator in an active research project focused on building data-driven organizations using AI and data warehousing. He also collaborates with SAS Institute Malaysia as an accredited trainer, delivering data science programs to industry and government. He is involved in professional communities and serves as a technical reviewer and judge for data science competitions and conferences, contributing to the advancement of the field in Southeast Asia.