جست‌وجوی استاد و پژوهشگر

Olli Varisمشاهده پروفایل

استاد

• Water Resources Management
• Sustainable Development
• Climate Change Adaptation
• +۵ مورد دیگر

Olli Varis is an Aalto Distinguished Professor at Aalto University's Department of Built Environment, specializing in Water and Environmental Engineering. He holds adjunct professorships at Asian Institute of Technology (Thailand) and has served as Vice Dean for Research & Innovation at Aalto School of Engineering (2013–2018). His expertise spans water resources management in developing economies, climate change impacts, and transboundary water governance. Education: Doctoral degree in Engineering (Helsinki University of Technology, 1991), Licentiate (1988), and dual Master's degrees in Agriculture (University of Helsinki, 1986) and Engineering (Helsinki University of Technology, 1984). Research focuses on sustainable development goals (SDGs), particularly water-energy-food nexus dynamics, urbanization impacts, and global river basin vulnerabilities. Key interests include flood early warning systems, migration-environment linkages, and Asian transboundary water challenges. Notable awards include Aalto Excellence Awards (2018, 2021), Best Research Paper 2023, and Environmental Research Letters' Best Paper 2010. Over 350 publications include works on China's water risks, Nepal's flood resilience, and global migration drivers. Active in UNESCO, WMO, and UNU/WIDER. Recent projects address urbanization's environmental pressures, interdisciplinary education challenges, and东南亚数字经济的崛起与挑战 (Vietnam's digital economy challenges). Leads the Water and Environmental Engineering research group, supervising 12 theses. Involved in public outreach,如芬兰赫尔辛基大学的媒体参与案例.

Stephen Croftمشاهده پروفایل

استاد

• Nuclear Materials Measurement Science
• Radiation Detection
• Nuclear Spectroscopy
• +۳ مورد دیگر

Professor Stephen Croft is a faculty member at Lancaster University , affiliated with the School of Engineering . His research focuses on Nuclear Materials Measurement Science , with expertise in radiation detection, neutron interrogation, and X-ray/gamma-ray spectroscopy. Current projects include cosmic ray neutron monitoring , active neutron interrogation of nuclear materials , and radiation damage assessment . His recent publications emphasize semi-empirical modeling of atomic interactions and advanced detection techniques for nuclear applications. He has contributed to understanding vacancy transfer probabilities , X-ray fluorescence cross-sections , and water detection in nuclear environments . His work supports nuclear security, power plant safety, and space weather monitoring. Scientific awards : None explicitly mentioned in the text. Research groups : Involved in Nuclear Space Weather initiatives.

Athanasios Rontogiannisمشاهده پروفایل

دانشیار

• Signal Processing
• Machine Learning
• Computational Signal and Image Processing
• +۴ مورد دیگر

Athanasios Rontogiannis is an Associate Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA). He holds a PhD in Signal Processing from the National University of Athens (1997) and has held roles including Research Director at the National Observatory of Athens (2017–2021). His research focuses on signal processing, machine learning, and hyperspectral image analysis. Education: MEng (Electrical Engineering, NTUA, 1991), M.A.Sc. (University of Victoria, Canada, 1993), PhD (Signal Processing, National University of Athens, 1997). Research interests include adaptive algorithms, sparse representations, and tensor models. He has served on editorial boards of IEEE Transactions on Signal Processing and EURASIP journals, receiving an honorary distinction in 2020. He is a Senior Member of IEEE and affiliated with EURASIP and the Technical Chamber of Greece. Key contributions span hyperspectral unmixing, Bayesian algorithms, and space data exploitation. His work integrates machine learning for applications in space science and signal processing.

David M. Higdonمشاهده پروفایل

استاد

• Bayesian Statistical Modeling
• Uncertainty Quantification
• Space-Time Modeling
• +۷ مورد دیگر

David M. Higdon is a Professor and Department Head of the Department of Statistics at Virginia Tech within the College of Science. He specializes in Bayesian statistical modeling of environmental and physical systems, focusing on integrating physical observations with computer simulations for prediction and inference. Previously, he spent 14 years at Los Alamos National Laboratory as a scientist and group leader in the Statistical Sciences Group. Education: Ph.D. in Statistics, University of Washington, 1994 M.A. in Mathematics, University of California San Diego, 1989 B.A. in Mathematics, University of California San Diego, 1987 Research Interests: Higdon’s work spans space-time modeling , inverse problems in hydrology and imaging , statistical modeling in ecology and environmental science , and multiscale models . He develops methods for parallel processing in posterior exploration , statistical computing , and Monte Carlo simulations . His research addresses critical challenges in uncertainty quantification (UQ), including climate modeling, nuclear density functional theory, and geophysical imaging. Publications Trends: His recent articles emphasize Bayesian methodologies applied to complex systems, such as climate forecasting, materials science, and cosmology. A recurring theme is the development of emulators and surrogate models to handle computationally intensive simulations. Awards: Fellow of the American Statistical Association Advising & Grants: While no specific advisees are listed, Higdon has contributed to interdisciplinary collaborations in UQ and statistical modeling. His work has been supported by grants from agencies such as the National Science Foundation and Department of Energy. Labs/Teams: He leads the Statistics Department’s efforts in UQ and computational statistics, fostering collaborations across engineering, environmental science, and physics.

Sophie Ryanمشاهده پروفایل

پژوهشگر ارشد

• Climate and Health
• Medical Geography
• Mental Health
• +۱۲ مورد دیگر

Sophie Ryan is a Climate and Health Research Fellow at Appalachian State University's Department of Geography and Planning, supported by the National Academy of Sciences. She holds a Ph.D. in Geography (candidate) from the University of North Carolina at Chapel Hill and advanced degrees in Geography from Appalachian State University and the University of Vermont. Education : Ph.D. Candidate in Geography (UNC Chapel Hill), M.A. in Geography (Appalachian State), B.S. in Geography (University of Vermont) Ryan's research integrates medical geography and climate science to explore mental health impacts of extreme weather events. Her work combines spatiotemporal modeling , health data analysis , and disaster response studies , focusing on youth, older adults, and vulnerable populations. Recent projects examine greenspace effects on mental health , compound climate events , and pandemic-related health disparities . Her publications highlight climate-mental health linkages , spatial epidemiology , and social vulnerability in disaster contexts. Articles address topics like heat-stress and mental health , transgender youth post-disaster trauma , and suicide risk disparities during the COVID-19 pandemic. Ryan employs distributed lag models , cluster analysis , and geospatial techniques to assess environmental health impacts. Scientific Awards : NASEM Climate-Health Fellow

Johanna Ziegelمشاهده پروفایل

استاد

• Statistical Forecasting
• Probability Theory
• Financial Risk Management
• +۳ مورد دیگر

Johanna Ziegel is a Professor of Statistics at ETH Zurich, Switzerland, since 2024, and a Visiting Scientist at the Heidelberg Institute for Theoretical Studies (HITS). Previously, she held positions at the University of Bern, where she was promoted to Full Professor in 2023. Her research focuses on decision-theoretically sound methods for forecast evaluation, probabilistic forecasting, risk measures in finance, and applications in meteorology, medicine, and climate science. She is actively involved in editorial roles for journals like Bernoulli , JASA: Theory & Methods , and SIAM Journal on Financial Mathematics . Education: PhD in Stereological Analysis of Spatial Structures from ETH Zurich (2010), supervised by Paul Embrechts and Eva B. Vedel Jensen. Postdoctoral research at the University of Melbourne and Heidelberg University. Research Interests: Forecast evaluation, elicitable functionals, risk measures, isotonic regression, statistical calibration, and applications in finance, climate science, and biostatistics. Her work bridges theoretical statistics with practical challenges in uncertainty quantification and decision-making under uncertainty. Advising & Collaborations: Supervised 7 PhD students and mentored several postdocs. Collaborates with the Computational Statistics group at HITS and the Oeschger Centre for Climate Change Research. Her group explores distributional regression under order constraints and novel methods for forecast comparison. Recognition: Credit Suisse Award for Best Teaching (2022), H.I.T. Program for Academic Leadership (2021–2022). Active in professional service, including the Bernoulli Society Council and editorial boards.

Daniel J Bainمشاهده پروفایل

دانشیار

• Hydrology
• Geomorphology
• Biogeochemistry
• +۵ مورد دیگر

Daniel J. Bain is an Associate Professor in the Department of Geology & Environmental Science at the University of Pittsburgh, where he also serves as Deputy Director of the Pittsburgh Water Collaboratory. He holds a B.A. in Chemistry and Geography from Macalester College, an M.S. and Ph.D. in Geography & Environmental Engineering from Johns Hopkins University, and completed a National Research Council Postdoctoral Fellowship at the U.S. Geological Survey's Water Resources Division. His research integrates hydrology, geomorphology, biogeochemistry, ecology, and spatial analysis to assess human impacts on environmental systems over centuries. Focus areas include: Fluvial (stream) system dynamics and sediment chemistry Urban critical zone processes and land-use impacts Water quality monitoring in anthropogenic landscapes Green infrastructure performance and stormwater management Environmental justice implications of urbanization Recent publications (2024-2025) demonstrate strong emphasis on urban hydrology, metal contamination pathways, climate-health interactions in vulnerable communities, and novel assessment methods for environmental systems. Research spans Pittsburgh's urban watersheds to international sites like China and El Salvador, employing field measurements, laboratory analysis, and geospatial approaches. Dr. Bain leads the Bain Lab at Pitt's Space Research Coordination Center, focusing on environmental chemistry and sustainable water systems. He collaborates extensively with community partners, including the Pittsburgh Center for Healthy Environments and Equity Research, and co-organizes symposia on urban environmental challenges.

Nicholas Nelsonمشاهده پروفایل

دانشیار

• Astrophysics
• Dynamical Chaos
• Solar Physics
• +۳ مورد دیگر

Dr. Nicholas Nelson is an Associate Professor in the Department of Physics at California State University, Chico. His research spans interdisciplinary areas including astrophysics, dynamical chaos, and medical education curriculum development. He specializes in stellar evolution models, solar convection dynamics, and magnetic field generation in stars. His work bridges physics and healthcare, addressing structural competency in medical training and social determinants of health through innovative curricula. Research interests include: solar magnetic loop formation, chaotic dynamics in celestial bodies, and integrating social determinants of health into residency programs. His publications reflect a dual focus on computational astrophysics and healthcare equity. Notable contributions include studies on knuckleball aerodynamics, early career challenges in astrophysics, and curriculum design for addressing health disparities. Though no awards are explicitly listed, his work demonstrates impactful cross-disciplinary engagement. No advising relationships or grant information was provided in the source material. His office is located in PHSC 121B on campus.

Gaël Kermarrecمشاهده پروفایل

پژوهشگر

• Boundary Layer Meteorology
• Atmospheric Turbulence
• GNSS Applications
• +۳ مورد دیگر

Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections

Minna Palmrothمشاهده پروفایل

استاد

• Space Physics
• Computational Astrophysics
• Plasma Dynamics
• +۵ مورد دیگر

Minna Palmroth is a Professor of Computational Space Physics at the University of Helsinki 's Faculty of Science , leading the Department of Physics 's Space Physics Research Group. She directs the Kestävän avaruustieteen ja -tekniikan huippuyksikön (Centre of Excellence in Sustainable Space Science and Technology) and serves as the principal investigator for the Vlasiator hybrid-Vlasov simulation framework.

Andrew Gettelmanمشاهده پروفایل

پژوهشگر

• Atmospheric sciences
• Climatology
• Climate modeling
• +۶ مورد دیگر

Andrew Gettelman is a distinguished climate scientist at Pacific Northwest National Laboratory whose research spans atmospheric sciences, climatology, and climate modeling. With a D-index of 91 and over 32,652 citations across 343 publications, he ranks 422nd globally and 194th nationally in Environmental Sciences. His research interests focus on fundamental climate processes including cloud microphysics, aerosol-cloud interactions, stratospheric dynamics, and climate model development. Gettelman has made significant contributions to understanding Arctic climate feedbacks, particularly how clouds respond to sea ice loss, and has advanced the representation of aerosols in climate models through his work on the Community Atmosphere Model (CAM). Analysis of his publication trends reveals a consistent focus on improving climate model representations of atmospheric processes, with recent work emphasizing climate sensitivity in the Community Earth System Model (CESM2) and bounding global aerosol radiative forcing. His research bridges fundamental atmospheric science with practical applications for understanding climate change. Among his recognitions, Gettelman has been named to the World's Best Scientists 2025 list. His highly cited works include foundational papers on cloud microphysics schemes and aerosol representation in climate models. Gettelman maintains extensive collaborative networks, frequently working with researchers from the National Center for Atmospheric Research, University of Colorado Boulder, and other leading climate institutions. His research has been instrumental in advancing climate modeling capabilities used in major international climate assessments.

Katarina Domijanمشاهده پروفایل

دانشیار

• Bayesian applications to data analysis
• Machine learning
• Statistical computing
• +۳ مورد دیگر

Katarina Domijan is an Associate Professor in Statistics at the Department of Mathematics and Statistics, Maynooth University, Ireland. She holds a PhD in Statistics from Trinity College Dublin (2008) and has been affiliated with Maynooth University since 2008, transitioning from Lecturer/Assistant Professor to her current role in 2024. Her academic career includes editorial roles as Associate Editor for The R Journal (2021–present) and the Journal of Computational and Graphical Statistics (2015–2024). Research Interests focus on Bayesian methods for high-dimensional data, particularly in classification problems. She specializes in feature selection and model visualization, with applications spanning agricultural data analysis (e.g., hyperspectral imaging for lactose prediction), medical diagnostics (e.g., sepsis and cancer detection), and space physics (e.g., Saturn Kilometric Radiation classification). Her work bridges theoretical statistics with real-world challenges, including socio-economic studies and forensic science. Key Research Areas Bayesian statistical inference Machine learning for large feature spaces Statistical computing and model interpretability Data visualization and chemometrics Scientific Contributions include leading projects like VistaMilk Phase II (2024–2030, €152,300) and Measuring Carbon Sequestration (2024–2028, €174,788.90). Her 15 most recent publications highlight advancements in ensemble modeling, spatial statistics, and medical diagnostics. Scientific Awards Associate Editor, The R Journal (2021–present) Associate Editor, Journal of Computational and Graphical Statistics (2015–2024) Student Supervision includes PhD and MSc graduates such as Dr. Bruna Wundervald (2024) and Dr. Mark O’Connell (2017). She also collaborates with researchers across disciplines, including Dr. Nadim Akasheh in food hypersensitivity studies.

Long Nguyenمشاهده پروفایل

استاد

• Nonparametric Bayesian Statistics
• Optimal Transport
• Machine Learning
• +۴ مورد دیگر

Long Nguyen is a Professor of Statistics at the University of Michigan, Ann Arbor, with a courtesy appointment in Electrical Engineering and Computer Science. He is affiliated with the Michigan Institute for Data Science (MIDAS) and the Vietnam Institute for Advanced Study in Mathematics (VIASM). His research focuses on Bayesian nonparametrics, optimal transport, machine learning, and spatiotemporal data analysis. Nguyen holds a PhD in Computer Science from UC Berkeley and has held postdoctoral positions at Duke University and the Statistical and Applied Mathematical Institute. Education: B.Sc. in Computer Science from Pohang University of Science and Technology; M.Sc. in Mathematics from Arizona State University; Ph.D. in Computer Science from UC Berkeley (2007). Research Interests: Bayesian nonparametric methods, optimal transport theory, statistical inference for complex models, and applications in spatiotemporal data, functional data analysis, and hierarchical modeling. He emphasizes developing scalable algorithms and geometric approaches for statistical learning. Editorial Roles : Annals of Statistics Journal of Machine Learning Research SIAM Journal on Mathematics of Data Science Bayesian Analysis Awards : IMS Fellow, ASA Fellow NSF CAREER Award IEEE Signal Processing Young Author Award L. J. Savage Dissertation Award (via student Aritra Guha) Advising & Collaborations : Guided over 20 PhD students and postdocs, many now in academia and industry. Collaborates on projects in AI ethics, music theory, and environmental data science. Active in organizing summer schools in Vietnam on Bayesian statistics and machine learning. Labs & Teams : Co-leads the Statistical Machine Learning reading group at U-M and collaborates with the VIASM on advanced mathematical research in Hanoi.

Tomas Karlssonمشاهده پروفایل

استاد

• Solar Wind-Magnetosphere Interaction
• Bow Shock Physics
• Magnetosheath Jets
• +۳ مورد دیگر

Tomas Karlsson is a Professor and Deputy Head of Department at the Royal Institute of Technology , specializing in Space and Plasma Physics . He teaches courses such as EF2240 Space Physics , EF2245 Space Physics II , and EI1240 Electromagnetic Theory , while serving as examiner or coordinator for advanced projects and thesis work in space-related fields. His research focuses on the interaction between the solar wind and planetary magnetospheres , with specific interests in bow shock physics , magnetosheath jets , solar wind magnetic holes , auroral physics , and comparative studies of magnetospheres across planets and comets. He employs spacecraft data (e.g., MMS , Cluster , BepiColombo ) and simulations to analyze plasma dynamics and space weather phenomena. The 15 most recent publications highlight trends in solar wind turbulence , magnetospheric boundary processes , and planetary plasma interactions , with recurring themes in SLAMS (Short Large-Amplitude Magnetic Structures) , magnetosheath jet formation , and magnetic hole propagation . These works span statistical surveys, hybrid simulations, and multi-mission data analysis.

Drexler Jamesمشاهده پروفایل

استادیار

• Health Equity and Disparities
• Social and Psychological Determinants of Health
• Biological Race Essentialism
• +۳ مورد دیگر

Drexler James is an Assistant Professor of Psychology at the University of Minnesota, Twin Cities, and an affiliate faculty member of the Robert J. Jones Urban Research and Outreach-Engagement Center. His research focuses on the social and psychological determinants of health among minoritized groups, particularly African American adults and men of color who have sex with men. He also examines the health consequences of biological race essentialism, using intersectionality as a framework to understand health inequities. James holds a B.Sc. in Psychology from the Illinois Institute of Technology and a Ph.D. in Social & Personality Psychology from the University of Illinois at Chicago, with a minor in Community Health Research. His specialties include racism and health, psychological essentialism, and internalized oppression. As the primary investigator of the Health, Intersectionality, Essentialism, & Stigma (HIES) Research Team, he investigates how stigma operates dynamically across perceivers and targets to reinforce health disparities. Recent work explores barriers to healthcare access, internalized racism’s mental health impacts, and the socio-cultural implications of racialized stereotypes. His academic contributions span over 20 peer-reviewed articles addressing race-related health disparities, internalized oppression, and the psychological impacts of systemic racism. While no formal awards are listed, his work demonstrates significant engagement with marginalized communities’ health challenges.