جست‌وجوی استاد و پژوهشگر

Michael E. Mannمشاهده پروفایل

استاد

• Earth's Climate System
• Human-Caused Climate Change
• Climate Policy
• +۳ مورد دیگر

Michael E. Mann is the Presidential Distinguished Professor in the Department of Earth and Environmental Science at the University of Pennsylvania, with a secondary appointment at the Annenberg School for Communication. He serves as Vice Provost for Climate Science, Policy, and Action and directs the Penn Center for Science, Sustainability, and the Media (PCSSM), while also being a faculty fellow at the Kleinman Center for Energy Policy. Education: BS in Physics and Applied Math (UC Berkeley), MS in Physics (Yale), PhD in Geology & Geophysics (Yale) His research focuses on the Earth’s climate system, particularly the science, impacts, and policy implications of human-caused climate change. He has pioneered studies on climate variability, tropical cyclones, and planetary wave dynamics using models like CLIMBER-2 and observational datasets. Mann’s recent work spans topics such as ocean warming, climate communication, and extreme weather events. His publications highlight trends in tropical cyclone activity, climate policy interventions, and the intersection of climate change with health risks. Scientific Awards: Hans Oeschger Medal (2012), Tyler Prize (2019), Leo Szilard Award (2021), Fellow of multiple scientific societies Key Contributions: Lead Author, IPCC Third Assessment Report (2001); Co-founder of RealClimate.org; Nobel Peace Prize contribution (2007) As a highly cited researcher and public science communicator, Mann bridges climate science with policy and media engagement. His affiliations include leadership roles at interdisciplinary centers focused on sustainability and climate solutions.

Paruyr Sergey Efendyanمشاهده پروفایل

استاد

• Geodesy
• Land Construction
• Cadastre

Paruyr Sergey Efendyan serves as Professor in the Department of Cartography and Geomorphology at Yerevan State University's Faculty of Geography and Geology since 2020, with prior institutional memberships at YSU (2021-2023) and Armenian National Agrarian University (2009-2023). His academic foundation includes a Certified Specialist degree in Urban Construction from Kiev Engineering and Construction Institute (1969-1974) and postgraduate studies in Applied Geodesy at Moscow Institute of Geodesy and Cartography (1982-1987), culminating in a 2016 Doctor of Science degree from Armenian National Agrarian University for research on Armenia's unified land information system. Professor Efendyan's research centers on Geodesy, Land Construction, and Cadastre, addressing critical challenges in spatial data infrastructure, land valuation methodologies, and geodetic applications for earthquake monitoring and agricultural land management. His work bridges historical land survey practices with modern technological solutions. His 2022-2025 publications reveal strong thematic cohesion around national spatial data infrastructure development, with recurring emphasis on AI integration, legal frameworks, cadastral revaluation, and satellite-based topographic mapping. Key trends include Python-based quality control systems for road data and anthropogenic impact analysis on soil composition. He actively participates in international forums including Geoforum-2023 (Ukraine), Environmental Protection conferences (Russia, 2022), and Land Management summits (Kyrgyzstan, 2021), demonstrating global engagement despite no explicitly listed scientific awards. Professor Efendyan advises students and manages research grants focused on Armenia's spatial data infrastructure modernization, particularly through Python-based quality control frameworks for road network datasets, though specific grant details remain unlisted in available materials.

• Remote Sensing
• Arctic Sea Ice Monitoring
• Synthetic Aperture Radar (SAR) Applications
• +۳ مورد دیگر

Wolfgang Fritz Otto Dierking is a Professor in Earth Observation at the Department of Physics and Technology, UiT The Arctic University of Norway. His research focuses on remote sensing of polar regions, particularly sea ice dynamics, iceberg detection, and multi-frequency SAR applications. He works within the Earth Observation research group at Forskningsparken 3 E332.1, Tromso. Academic Rank: Professor (non-emeritus) Key Research Areas: SAR image analysis, sea ice classification, Arctic climate monitoring, and microwave scattering His recent publications emphasize: Development of CFAR algorithms for iceberg detection Multi-sensor data fusion (Sentinel-1/AMSR-2) Incidence angle effects on SAR texture features Integration of satellite and model-derived drift data Operational applications of polar remote sensing Arctic expedition data validation campaigns As an active researcher, he collaborates with institutions like CIRFA, NASA, and European polar research networks. His work supports climate data sets and operational Arctic marine safety applications.

• Spatio-temporal statistics
• Computational statistics
• Earth sciences
• +۵ مورد دیگر

Jo Eidsvik is a Professor at the Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU). He holds a MSc in applied mathematics from the University of Oslo (1997) and a PhD from NTNU (2003). His research focuses on spatio-temporal statistics, computational statistics, and their applications in Earth sciences, including geophysics and oceanography. He leads projects like the Center for Geophysical Forecasting (SFI-CGF) and Maritime Autonomous Sampling and Control (MASCOT). Eidsvik has supervised over 60 graduate students and is an associate editor for *Mathematical Geosciences* and *Statistics and Computing*. His work bridges theory and practice, addressing challenges in data assimilation, value of information analysis, and autonomous systems for environmental monitoring. **Education & Background**: MSc (University of Oslo), PhD (NTNU). Industry experience includes roles at Statoil and the Norwegian Defense Research Establishment. Visiting scholar at Stanford University, Duke University, and SAMSI. **Research Themes**: Spatio-temporal modeling, machine learning for irregular time series, and decision analysis in geological contexts. Key projects include geophysical forecasting, CO₂ storage monitoring, and autonomous underwater vehicle (AUV) sampling strategies. His book *Value of Information in the Earth Sciences* (Cambridge Press) synthesizes methodologies for optimizing data-driven decisions. **Awards & Recognition**: While no specific awards are listed, his editorial roles and project leadership reflect scholarly impact. His work emphasizes interdisciplinary collaboration, with applications in climate science, energy systems, and robotics. **Advising & Grants**: Supervised 60+ MSc students and 12 PhD students. Active in NTNU’s Physics and Mathematics program and Industrial Mathematics initiatives. Projects funded by SFI, EU, and industry partners. **Teams & Labs**: Involved with NTNU’s GEOPARD (data assimilation in geological models), Havvarsel (oceanographic data assimilation), and ML4ITS (machine learning for irregular time series). Collaborates with international institutions like Stanford and Duke.

Pia Addabboمشاهده پروفایل

مدرس

• Remote Sensing
• Geophysics
• Environmental Monitoring
• +۳ مورد دیگر

Pia Addabbo is a Lecturer at the Department of Engineering , University of Sannio , with expertise in remote sensing and satellite data analysis. Her work focuses on GNSS reflectometry, wind speed estimation, and hyperspectral imaging applications. Department: Engineering Academic Rank: Lecturer Research Interests: Addabbo's research spans Remote Sensing , Geophysics , Environmental Monitoring , and Signal Processing . She has contributed to: GNSS reflectometry for ocean wind speed retrieval UAV systems in photovoltaic plant maintenance Phase altimetry techniques for surface height measurement Sparse learning algorithms in radar profiling Publication Trends (2015–2024): 15 articles highlight her focus on satellite-based environmental monitoring (CYGNSS, Sentinel-1), microwave reflectometry , and machine learning applications in remote sensing. Key collaborations include Silvia Ullo, Maurizio Di Bisceglie, and Carmela Galdi.

Pin Shuaiمشاهده پروفایل

استادیار

• Hydrology
• Groundwater-Surface Water Interactions
• Integrated Hydrologic Modeling
• +۷ مورد دیگر

Dr. Pin Shuai is an Assistant Professor in the Department of Civil and Environmental Engineering at Utah State University, affiliated with the Utah Water Research Laboratory (UWRL) within the College of Engineering. He leads the Shuai Computational and Integrated Hydrology (SCI-Hy) research group, focusing on advancing the understanding of complex hydrological systems through computational modeling and data integration. Dr. Shuai holds a PhD in Geology (Hydrogeology) from Texas A&M University (2017), an MS in Water Resources Engineering from Wuhan University (2013), and a BS in the same field from Wuhan University (2011). His academic journey was followed by a postdoctoral and staff scientist position at the Pacific Northwest National Laboratory from 2017 to 2022. His research interests are centered on groundwater-surface water interactions, nutrient and contaminant transport, watershed biogeochemistry, and integrated hydrologic modeling. He employs a model-data integrative approach combining field observations, laboratory data, remote sensing, and numerical models powered by high-performance computing. His group emphasizes open-source and reproducible science, addressing critical environmental challenges such as human-water interactions and the impacts of disturbances like drought and land use change on watershed processes. The recent publications of Dr. Shuai reflect a strong trend toward computational hydrology, with a focus on high-resolution watershed modeling, the role of streambed representation, the impact of meteorological forcing resolution, and the application of machine learning and deep neural networks for model calibration and permeability estimation. His work bridges traditional hydrological modeling with modern data science techniques, aiming to improve predictive capabilities in complex hydrological systems. Dr. Shuai has mentored several graduate students, including Collins Stephenson, Ehsan Ebrahimi, Pamela Claure, and Jihad Othman, guiding them through thesis research in civil and environmental engineering. While no scientific awards are listed in the provided text, his active research program, consistent publication record in high-impact journals, and leadership of a growing research group indicate a strong trajectory in the field. He teaches courses such as Groundwater Engineering, Hydrologic Modeling, and GIS for Civil Engineers, contributing to both graduate and undergraduate education. The SCI-Hy group, under Dr. Shuai’s leadership, is actively engaged in projects that integrate advanced modeling tools like the Advanced Terrestrial Simulator (ATS) and Watershed Workflow to parameterize and simulate watershed processes. The group welcomes passionate students and recently advertised for a postdoctoral position focused on ML/AI applications in hydrology, highlighting its forward-looking research direction.

• Seismology
• Geophysics
• Seismic Event Discrimination
• +۳ مورد دیگر

Timo Tiira is a Researcher at the Institute of Seismology, University of Helsinki , and Supervisor for the Doctoral Programme in Geosciences. His work focuses on seismology and geophysics, particularly seismic event discrimination using Finnish station networks. PhD in Geophysics (Discrimination of seismic events using Finnish station network) MSc in Physics (Seismisten signaalien havaitseminen Hutt&Murdock-detektorin ja digitaalisen suodatuksen avulla) Research Interests: Seismology and geophysics with emphasis on seismic event discrimination, crustal structure analysis, ambient noise tomography, and seismic hazard assessment for critical infrastructure like nuclear power plants. Key Contributions: Leadership in establishing the Finnish Seismic Instrument Pool (FINNSIP) , development of 3D shear wave velocity models for Helsinki, and automated seismic event classification systems. Collaborative work spans Finland, Russia, and Ukraine with 103+ activities and 187+ research outputs. Scientific Awards: Recipient of Best GFF Articles award (2014) Projects: Active in SCARCE: Scandinavian Arctic Continental Experiment (2023–2028) and Monitoring the monitoring (2020–2025). Key roles in seismic networks for geothermal and nuclear facility monitoring.

• Seismology
• Earth's Interior
• Inverse Theory
• +۵ مورد دیگر

Professor Jeannot Trampert is a leading seismologist at Utrecht University's Faculty of Geosciences, where he serves as Professor of Seismology within the Department of Earth Sciences. His research group focuses on extracting information from ground motion recorded at global and regional seismic networks to produce three-dimensional models of the Earth's interior and seismic sources, primarily using high-performance computing approaches. With over 250 publications spanning decades, Trampert maintains an active research program with recent works published through 2025. Trampert's research expertise encompasses several critical areas of modern seismology: Theoretical and computational seismology Earthquake physics and analysis Earth's deep interior structure Inverse theory applications Machine learning in geophysical data analysis Mineral physics and Earth composition His recent publications demonstrate an increasing integration of machine learning techniques with traditional seismological methods, particularly for analyzing seismic data from the Groningen gas field in the Netherlands. Trampert's work bridges theoretical seismology with practical applications in monitoring induced seismicity, pore pressure changes, and temperature effects on seismic wave propagation. His research group actively collaborates with international partners on projects involving full-waveform inversion, mantle structure analysis, and seismic monitoring systems. Professor Trampert has supervised numerous students throughout his career, with university records indicating 29 supervised works. His research receives consistent funding through multiple grants, supporting both fundamental research and applied projects related to geohazards and resource extraction. He maintains active collaborations with institutions across Europe and participates in major research initiatives like EPOS-NL, the Dutch solid earth science infrastructure for georesources and geohazards research.

Josselin Garnierمشاهده پروفایل

استاد

• Waves in Random Media
• Imaging in Complex Media
• Uncertainty Quantification
• +۶ مورد دیگر

Josselin Garnier is a Professor at Ecole Polytechnique, France, affiliated with the Center for Applied Mathematics. His research focuses on wave propagation in random media, imaging techniques, uncertainty quantification, and inverse problems. He has authored/co-authored multiple influential books including Wave Propagation and Time Reversal in Randomly Layered Media (2007) and Multi-Wave Medical Imaging (2017). His work bridges mathematical theory with applications in optics, seismology, and nuclear engineering. Research interests emphasize stochastic dynamics, nonlinear wave interactions, and Bayesian methods for parameter estimation. He leads a large research group with over 30 PhD students, many working on interdisciplinary projects such as thermalization in optical fibers and seismic fragility analysis. His contributions include developing reduced order modeling approaches for inverse problems and advancing methodologies for uncertainty quantification in nuclear reactor simulations. Key collaborations involve institutions like the French Mathematical Society and the Ciroquo Research & Industry Consortium. His educational contributions include the widely used All-in-one Mathematics textbook series for undergraduate students.

Chen Zengمشاهده پروفایل

استادیار

• Autonomous Robotics
• Multidisciplinary Optimization
• Aerospace Engineering
• +۵ مورد دیگر

Chen Zeng is an Assistant Professor of Teaching in the Department of Mechanical and Aerospace Engineering at the University at Buffalo. Their research focuses on autonomous robotics, multidisciplinary optimization, and advanced UAV systems design. Dr. Zeng holds a PhD in Mechanical Engineering from the University at Buffalo (2022), an MS in Mechanical Engineering from the same institution (2018), and a BS in Geophysics and Seismology from Tongji University (2015). Key research areas include space debris capture systems using tether-net technologies, cyber-physical systems control, and bio-inspired design for unmanned aerial vehicles. Their work bridges robotics, aerospace engineering, and machine learning to develop intelligent systems with robust operational capabilities. Recent studies emphasize optimizing system performance under uncertainties and creating physics-aware learning frameworks. Publications highlight contributions to concurrent design optimization of robotic systems, program synthesis for embedded systems, and multi-modal sensing for autonomous vehicles. Dr. Zeng's research demonstrates a strong focus on practical applications in aerospace and robotics, with a particular interest in real-world challenges like space debris mitigation and swarm intelligence.

• Smart Textiles
• Occupational Safety
• Ergonomics
• +۵ مورد دیگر

George Priniotakis is a Professor in the Department of Industrial Production Systems at the University of West Attica. He specializes in innovative textile technologies for multifunctional clothing, with a focus on medical and military applications, wearable sensors, and sustainable materials. His work bridges engineering, ergonomics, and environmental stewardship. University of Leeds – M.Sc. in Fiber Science and Technology (1992) University of Ghent – PhD in Conductive Textile Materials His research interests include: Smart systems using conductive textiles Risk management via wearable sensors Recyclable yarn development Innovative educational tools for engineering Professor Priniotakis has led numerous research projects as a scientific director and coordinator, participated in over 100 international conferences, and maintains an H-index of 12. He serves as President of the Organizing Committee for the biennial AITAE conference.

Jack B. Muirمشاهده پروفایل

پژوهشگر ارشد

• Seismology
• Geophysics
• Inverse Problems
• +۳ مورد دیگر

Jack B. Muir is a Marie Skłodowska-Curie Fellow at the University of Oxford's Department of Earth Sciences and Junior Research Fellow at Wolfson College. His research integrates advanced mathematics with seismology to address inverse problems in Earth imaging and hazard assessment. Education: PhD in Geophysics, Caltech Seismolab (2021) Research focuses on physics-informed neural networks for seismic wavefield simulation (TerraPINN project), nonparametric seismicity rate modeling using deep Gaussian processes, geologically-constrained tomography, and Bayesian methods for wavefield reconstruction. His work targets applications from near-surface structures to Earth's core, emphasizing machine learning acceleration and uncertainty quantification in inverse problems. Recent projects include Distributed Acoustic Sensing (DAS) optimization and seismic swarm analysis. Publication trends (2022-2025) reveal strong emphasis on machine learning integration (PINNs, Gaussian processes) with geophysical inverse problems, particularly for DAS data processing, deep Earth imaging, and probabilistic hazard assessment. Key themes include multi-scale analysis, instrument response calibration, and computational efficiency. Scientific Awards: Marie Skłodowska-Curie Fellowship John Monash Scholarship Junior Research Fellowship at Wolfson College, Oxford Grant-funded projects include TerraPINN for physics-based seismic hazard assessment and collaborations leveraging Caltech's Community Seismic Network. He actively develops open-source tools for core-mantle boundary modeling and DAS data processing. Labs and teams involve Oxford's Seismology group (Tarje Nissen-Meyer), Caltech (Zach Ross), Australian National University (Hrvoje Tkalčić), and JAMSTEC (Satoru Tanaka), with fieldwork utilizing ocean-bottom seismometers and urban sensor networks.

Sebastian Bucheltمشاهده پروفایل

پژوهشگر

• Remote Sensing
• Earth Observation
• Geography
• +۱۲ مورد دیگر

Sebastian Buchelt is a doctoral student at the Chair of Remote Sensing , part of the Institute of Geography and Geology under the Faculty of Philosophy at the University of Würzburg. His research focuses on applying SAR remote sensing and time series analysis to study periglacial processes in alpine environments. Current affiliation: University of Würzburg (since 2020) Education: B.Sc. in Geography and Experimental Physics (University of Munich), M.Sc. in Applied Earth Observation and Geoanalysis (University of Würzburg) Research interests include: SAR remote sensing for periglacial monitoring Climate change impacts on alpine geosystems Time series analysis of geospatial data Integration of radar and geophysical field methods Recent publications highlight his work on: Rock glacier dynamics via multi-sensor data fusion Permafrost degradation assessments using historical ERT Alpine snow cover detection algorithms Sentinel-1 applications for Arctic snowmelt analysis Contact: sebastian.buchelt@uni-wuerzburg.de

• Atmospheric Physics
• Cloud Physics
• Atmospheric Turbulence
• +۵ مورد دیگر

Szymon P. Malinowski is a full Professor at the Department of Atmospheric Physics, Institute of Geophysics, Faculty of Physics, University of Warsaw, and a corresponding member of the Polish Academy of Sciences since 2020. He served as Director of the Institute of Geophysics from 2016 to 2024 and previously as Head of the Department of Atmospheric Physics (2002-2013). His institutional affiliations include the Polish Academy of Sciences (2020-present) and research collaborations with institutions like Université de Lille (2023-2024) and Johannes Gutenberg-Universität Mainz (2013-2014). Master of Science in Physics (University of Warsaw, 1982) Doctor of Natural Sciences in Geophysics (Institute of Geophysics PAN, 1988) Habilitation in Physical Sciences (Institute of Geophysics PAN, 1998) Professor of Earth Sciences (2008) Malinowski's research centers on atmospheric physics with emphasis on cloud processes and turbulence. His work integrates laboratory experiments (e.g., Π Chamber), field campaigns (EUREC 4 A, ACORES), and numerical modeling to investigate turbulence dynamics in boundary layers, cloud microphysics using shadowgraph imaging, and climate-relevant processes like aerosol-cloud interactions. He pioneered fractal reconstruction techniques for turbulence modeling and developed novel optical hygrometers for airborne measurements. His experimental approach bridges fundamental fluid dynamics with atmospheric applications, particularly in marine stratocumulus systems. Analysis of his 15 most recent publications (2022-2025) reveals three dominant research thrusts: (1) High-resolution turbulence characterization using aircraft and laboratory data, focusing on dissipation scaling and non-equilibrium states; (2) Advanced measurement techniques for cloud microphysics, including low-cost optical sensors and shadowgraph systems; (3) Climate science communication through book chapters on Earth's energy balance and climate crisis mitigation. His work increasingly integrates machine learning approaches for turbulence analysis while maintaining strong connections to observational campaigns. 2017: National 'Science Popularizer' award (team category) for naukaoklimacie.pl 2022: Foundation for Polish Science Award for public science communication 2023: Honorary membership in Chapter Zero Poland Malinowski has supervised 14 PhD students across atmospheric physics and cloud dynamics, with recent graduates including Stanisław Król (2025) on turbulent mixing and Moein Mohammadi (2023) on shadowgraph imaging. He leads the Climate Education Foundation (founded 2021) which produces educational materials reaching over 500,000 annual visitors. His grant portfolio includes EU-funded projects like EUREC 4 A and national initiatives on climate crisis mitigation. He co-founded and directs the Climate Education Foundation, which operates the naukaoklimacie.pl platform and develops educational materials for schools. His research group participates in the European Turbulence Conference organizational committee and conducts field work at the Umweltforschungsstation Schneefernerhaus. Current projects focus on turbulence-cloud interactions in marine environments using data from the EUREC 4 A campaign and developing machine learning tools for atmospheric data analysis.

Monika Korteمشاهده پروفایل

استاد پژوهشی

• Geomagnetism
• Paleomagnetism
• Geophysical Modeling
• +۷ مورد دیگر

Dr. Monika Korte is the Acting Head of the Geomagnetism Section (Section 2.3) at the GFZ German Research Centre for Geosciences. She leads the working group on the 'Evolution of the Earth's Magnetic Field' and has been instrumental in advancing research on geomagnetic field reversals, secular variation, and space weather effects. Her work integrates paleomagnetic data, satellite observations, and computational modeling to understand Earth's core dynamics and their climatic impacts. Education & Career: PhD in Geophysics, Free University of Berlin (1999) Diploma in Geophysics, Ludwig Maximilian University (1996) Acting Head of Section 2.3 since 2021 Leadership roles in international projects, including the ERC Synergy Grant GERACLE (2024–2030) Research Interests: Geomagnetic field reversals/excursions Global and regional magnetic field modeling Geomagnetic observatory networks Cosmogenic isotope analysis Machine learning applications in geophysics Awards & Grants: ERC Synergy Grant (2024): €10M for GERACLE project GFZ Research Award (2003) Feodor-Lynen Fellowship (2001) Labs & Collaborations: Leading the Niemegk Geomagnetic Observatory Coordinating the GERACLE international consortium Member of IAGA Executive Committee and AGU editorial boards