جست‌وجوی استاد و پژوهشگر

Kees Vuikمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Computational Fluid Dynamics
• +۴ مورد دیگر

Kees Vuik is a Professor at the Delft Institute of Applied Mathematics within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on developing advanced numerical methods for complex engineering and scientific simulations across multiple domains including energy systems, environmental engineering, and computational physics. His research interests center on Numerical Analysis and Scientific Computing, with specialized expertise in Computational Fluid Dynamics, Reservoir Simulation, and Wave Propagation. He develops innovative preconditioning techniques for large-scale linear systems and creates high-fidelity models for subsurface flow, flood prediction, and energy conversion systems. Recent work integrates graph-based frameworks for electrolyzer modeling and advanced triangulation methods for point cloud processing. Analysis of his 2025 publications reveals a strong interdisciplinary focus on sustainable energy solutions (hydrogen/CO2 storage), environmental resilience (flood modeling), and computational efficiency (parallel preconditioning). His work consistently bridges theoretical numerical methods with practical engineering applications, particularly in energy transition technologies and climate-related simulations. Professor Vuik's scientific contributions have earned significant recognition: Officer of the Order of Orange-Nassau (2021) Professor of Excellence award (Leermeesterprijs) from TU Delft (2022) He has supervised 49 students across bachelor, master, and PhD levels, with notable successes including undergraduate research published in leading medical journals. His collaborative network spans 21 documented activities including industrial partnerships with Fujitsu Laboratories and leadership in academic societies, indicating substantial research funding and mentorship impact. As chair of the Bataafsch Genootschap der Proefondervindelijke Wijsbegeerte (2023-2024) and active member of the Delft Institute of Applied Mathematics, he contributes to both foundational mathematical research and real-world applications through international collaborations and industrial knowledge exchange.

Vitaliy Ogarkoمشاهده پروفایل

پژوهشگر ارشد

• Geophysical Inversion
• Computational Geology
• Geological Modeling
• +۵ مورد دیگر

Vitaliy Ogarko is a Research Fellow at The University of Western Australia's School of Earth and Oceans. He is affiliated with the Centre for Exploration Targeting where he joined in 2021 to work on the MinEx project. His expertise in computational geophysics and high-performance algorithms has established him as a key contributor to geoscience software development and geological modeling. Dr. Ogarko holds a PhD in Computational Physics. His academic background bridges applied mathematics with earth sciences, providing a strong foundation for his computational approach to geophysical problems. His research focuses on: Design and development of high-performance computational algorithms for geophysical inversion Computational geology and 3D geological modeling Open-source software development for geoscience applications Integration of geological and geophysical data for resource exploration Uncertainty quantification in geological interpretations Machine learning applications in earth sciences Recent publications reveal a growing emphasis on integrating machine learning techniques with traditional geophysical methods, particularly for urban geological modeling and stratigraphic data recovery from complex drillhole databases. His work demonstrates increasing sophistication in handling large-scale geophysical datasets with complex constraints. Dr. Ogarko was awarded the MinEx CRC 2019-2020 publication prize for collaborative research. He currently serves as Investigator 02 on the ARC Australian Research Council project 'Loop 3D Linkage-2' (2023-2026), which supports his ongoing research in geological modeling and inversion techniques. He leads the Tomofast-x software framework development, a powerful 3D parallel inversion platform for geophysical data, and contributes to the litho2strat project for automated stratigraphic data extraction. His work is integrated within the broader GeoMos community for collaborative geoscience modeling and simulation.

David Bajnaiمشاهده پروفایل

مدرس

• Geochemistry
• Isotope Geology
• Paleoclimatology
• +۳ مورد دیگر

David Bajnai is a Lecturer (Temporary Academic Councillor) at Georg-August-University Göttingen, where he is a member of the Isotope Geochemistry Group led by Prof. Andreas Pack at the Geoscience Center's Department of Geochemistry and Isotope Geology. He teaches courses on Climate Change Throughout Earth's History, Modern Climate Change, and Mathematics and Statistics for geoscience students. 2021-Present: Temporary Academic Councillor, Georg-August-University Göttingen 2019-2021: Post-doc, University of Cologne 2015-2019: PhD, Goethe University Frankfurt 2013-2015: MSc, Eötvös Loránd University, Budapest 2010-2013: BSc, Eötvös Loránd University, Budapest Dr. Bajnai's research centers on reconstructing environmental conditions, particularly changes in surface temperatures throughout Earth's history. He specializes in dual clumped isotope (Δ47 and Δ48) and triple oxygen isotope (Δ17O) proxies in carbonates to provide accurate temperature reconstructions for archives where traditional proxies are inadequate. His work focuses on disentangling biological and diagenetic signals to fill gaps in Earth's climate record, with applications spanning from Precambrian ecosystems to recent climate change. His publication record shows a strong focus on methodological development in isotope geochemistry, with recent articles examining carbonate formation temperatures, kinetic isotope effects, and paleoclimate reconstructions across various geological periods. His work bridges analytical chemistry, paleoclimatology, and Earth system science, with contributions to understanding temperature gradients, seawater composition, and biogeochemical cycles throughout Earth's history. As a member of the Isotope Geochemistry Group at Göttingen, Dr. Bajnai collaborates with researchers across multiple institutions on projects related to carbonate geochemistry and paleoclimate reconstruction. His work contributes to refining analytical techniques and expanding the applications of clumped and triple oxygen isotope systems for understanding Earth's climate evolution.

• Marine Biogeochemistry
• Geochemistry
• Sediment Dynamics
• +۵ مورد دیگر

Professor Karline Soetaert is a distinguished researcher in the Department of Earth Sciences within the Faculty of Geosciences at Utrecht University. Her extensive career has focused on marine biogeochemistry, particularly examining sediment dynamics, carbon and nitrogen cycling in marine environments, and cold-water coral ecosystems. She maintains an active research profile with numerous publications spanning decades, demonstrating her significant contributions to understanding complex marine systems. Dr. Soetaert's research interests encompass a broad spectrum of marine biogeochemical processes. Her work investigates carbon and nitrogen cycling in various marine environments, including deep-sea ecosystems and coastal zones. She has made significant contributions to understanding cold-water coral mound development and the biogeochemical processes that govern marine sediment dynamics. Her research also explores ocean acidification effects and reactive transport in the hydrosphere, addressing critical environmental challenges facing marine ecosystems today. Analysis of her recent publications reveals a strong focus on deep-sea ecosystems, particularly cold-water coral habitats. Her work demonstrates how hydrodynamic processes interact with biological communities to shape marine landscapes. She has developed innovative approaches to studying carbon and nutrient flows through marine food webs, with applications for understanding ecosystem responses to environmental change. Her research spans from molecular-scale processes to basin-wide patterns, reflecting a comprehensive systems approach to marine biogeochemistry. Professor Soetaert has contributed significantly to methodological advancements in her field, including the development of software packages like 'seacarb' and 'AquaEnv' for seawater carbonate chemistry modeling. Her collaborative work extends across international research teams, addressing global marine challenges through interdisciplinary approaches. Her laboratory and research team focus on marine biogeochemistry, with particular expertise in sediment-water interactions, deep-sea ecosystem functioning, and the development of quantitative models for understanding complex marine processes. The team employs a combination of field observations, laboratory experiments, and mathematical modeling to address fundamental questions in marine science.

• Machine Learning
• Computer Vision
• Distance Metric Learning
• +۴ مورد دیگر

Xiaochen Yang is an Assistant Professor in the Department of Artificial Intelligence at the School of Computer Science and Control Engineering, University of Chinese Academy of Sciences. With a PhD from University College London completed in 2020, Dr. Yang has established a prolific research career spanning machine learning, computer vision, and computational mathematics. Their work bridges theoretical foundations with practical applications across multiple domains. Dr. Yang's research interests focus on advancing machine learning methodologies, particularly in distance metric learning, few-shot learning, and multimodal systems. Their work spans both theoretical aspects of numerical methods for stochastic differential equations and practical applications in computer vision, hyperspectral imaging, and security of large language models. This interdisciplinary approach has led to significant contributions in multiple fields. Analysis of Dr. Yang's recent publications reveals a strong trajectory in developing novel machine learning architectures, with particular emphasis on few-shot learning techniques, multimodal fusion approaches, and applications of diffusion models. Their work demonstrates increasing sophistication in handling complex data modalities while maintaining mathematical rigor, particularly evident in their publications from 2023-2025. Dr. Yang has established productive collaborations across institutions, as evidenced by their extensive co-author network spanning Chinese academic institutions and international partners. Their research has been published in top-tier venues including IEEE Transactions, Pattern Recognition, NeurIPS, and CVPR, reflecting the high impact of their contributions to the field.

Ryan E. Doughertyمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Algorithms
• Evolutionary Algorithms
• +۳ مورد دیگر

Dr. Ryan E. Dougherty is an Assistant Professor at Arizona State University's School of Computing, Informatics, and Decision Systems Engineering, specializing in Computer Science. His research focuses on theoretical computer science, combinatorial algorithms, and evolutionary algorithms applied to software testing and education. Education: Ph.D. in Computer Science (Arizona State University, 2019) B.S. in Computer Science (Arizona State University, 2015) His research interests include t-restrictions , hash families , and genetic algorithms for testing optimization. Recent publications demonstrate interdisciplinary applications from cybersecurity to theoretical mathematics. Scientific Awards: Best Paper Award at GI 2019 Workshop Publications span combinatorial design theory, software testing methodologies, and evolutionary computation applications. Research shows consistent focus on algorithmic optimization and formal testing frameworks.

• High-performance computing
• Special-purpose computing architectures
• Cloud computing
• +۵ مورد دیگر

Volodymyr Kindratenko is a Research Associate Professor at the University of Illinois at Urbana-Champaign and Assistant Director for the Center for Artificial Intelligence Innovation (CAII) at the National Center for Supercomputing Applications (NCSA) . He also holds an Adjunct Associate Professor appointment in the Department of Electrical and Computer Engineering . His academic background includes a D.Sc. in Analytical Chemistry (University of Antwerp, 1997) and an M.Sc. in Mathematics and Informatics (Volodymyr Vynnychenko Central Ukrainian State University, 1993). Dr. Kindratenko's research focuses on High-performance computing (HPC) with computational accelerators Special-purpose computing architectures AI and machine learning systems for scientific applications Cloud computing integration with HPC Transformer-based models for medical imaging Federated learning on heterogeneous resources His work has been funded by NSF, NASA, ONR, DOE, and industry partners. The 15 most recent publications span AI-driven cosmological data analysis, cloud-HPC integration, and GPU-accelerated quantum simulations. Keywords include Machine Learning , High-performance computing , Quantum Chromodynamics , and Cloud Computing , with subfields like Transformers for medical imaging , Federated learning , and GPU clusters . Scientific awards include SRC Award for Excellence in Reconfigurable Computing (2007) Instructure Academic Excellence Award (2025) Outstanding Service Award at the 9th ACS/IEEE Conference (2011) George Anner Excellence in Teaching Award (2022) He serves as department editor of IEEE Computing in Science and Engineering and associate editor of International Journal of Reconfigurable Computing , and mentors students in the SC Student Cluster Competition (2016-2021). Dr. Kindratenko is a Senior Member of IEEE and ACM .

Stefanie Tofeldeمشاهده پروفایل

پژوهشگر

• Sedimentary Geology
• Tectonics
• River Dynamics
• +۳ مورد دیگر

Dr. Stefanie Tofelde is a permanent PostDoctoral Researcher in the Sedimentary Systems group at Freie Universität Berlin's Institute of Geological Sciences since 2023. Previously, she held PostDoc positions at the University of Potsdam in Geological Remote Sensing (2019-2023) and Soil Science/Geomorphology (2018-2019). Education: PhD in Geology (2018), GFZ German Research Centre for Geosciences & University of Potsdam MSc in Geoscience (2014), University of Potsdam Master in Biology (2011), University of Konstanz & Erasmus exchange at University of Tromsø BSc in Biology (2010), University of Konstanz Her research focuses on the interplay between environmental changes and river dynamics, examining how river valleys adjust topographically and produce sedimentary records. She employs analog landscape modeling, digital elevation model analysis, cosmogenic radionuclide dating, and biomarker geochemistry to study these processes across diverse tectonic and climatic settings like the Andes and Himalayas. Recent publications highlight her work on channel belt evolution as random walks, sediment signal propagation in transient landscapes, and elevation-dependent geomorphic processes. Her methodological approach bridges field observations with numerical modeling and geochemical analysis. She contributes to teaching through courses on sedimentary systems analysis and digital elevation model interpretation at both undergraduate and graduate levels.

• Rhizosphere modeling
• Plant-Soil Nutrient Interactions
• Mathematical Modeling
• +۶ مورد دیگر

Dr. Christian Kuppe is a researcher at Forschungszentrum Jülich working within the Institute of Bio- and Geosciences (IBG), specifically in the Plant Sciences department (IBG-2). His office is located in Building 06.1, Room 013 at the Jülich research campus in Germany. He contributes to the institute's mission of developing sustainable solutions for plant production and agriculture through interdisciplinary research approaches that integrate molecular, physiological, and ecological perspectives. Dr. Kuppe specializes in mathematical modeling of plant-environment interactions, with particular focus on resource-efficient agricultural systems. His research program centers on rhizosphere modeling, plant-soil nutrient interactions, and numerical simulations of water flow and solute transport in unsaturated porous media. He develops computational models to understand complex non-linear processes in plant systems that would be difficult to study through experimental methods alone. This work aims to discover novel traits in resource-efficient plants that can contribute to adaptation in changing climate conditions and support the bioeconomy. At Forschungszentrum Jülich, Dr. Kuppe collaborates within a multidisciplinary environment that bridges theoretical modeling with practical agricultural applications. His mathematical approaches provide critical insights into plant nutrient and water uptake mechanisms, with potential implications for improving crop resilience and productivity in resource-constrained environments. The research conducted in IBG-2 combines experimental and computational methods to address sustainability challenges in agriculture through innovative scientific approaches.

Shizue Matsubaraمشاهده پروفایل

پژوهشگر

• Biology
• Plant Research
• Bioeconomy
• +۷ مورد دیگر

Dr. Shizue Matsubara is a researcher at the Institute of Bio- and Geosciences (IBG-2) at Forschungszentrum Jülich, Germany. Her work focuses on plant sciences, particularly the dynamics of photosynthesis under fluctuating environmental conditions and its implications for sustainable agriculture and bioeconomy. Key research areas: Photosynthesis regulation, photoprotection, light fluctuation adaptation Methodologies: Non-invasive fluorescence imaging, genomic prediction, field phenotyping Recent research trends from 2025–2020 highlight her expertise in: Quantifying genotype-phenotype links under dynamic light regimes Developing mathematical models for photoinhibition and quenching processes Investigating frequency-dependent photosynthetic responses Advancing luminescence macroscope technologies for plant analysis Her group integrates molecular, physiological, and ecological approaches to improve crop yield breeding through photosynthetic efficiency. Forschungszentrum Jülich's IBG-2 provides interdisciplinary infrastructure for studying plant-environment interactions at multiple scales.

Viktor Sydorukمشاهده پروفایل

پژوهشگر

• Plant Science
• Bioeconomy
• Radiophysics
• +۴ مورد دیگر

Dr. Viktor Sydoruk is a Researcher at the Plant Sciences (IBG-2) department within the Institute of Bio- and Geosciences at Forschungszentrum Jülich GmbH. His work focuses on sustainable agriculture through plant phenotyping, plant-environment interactions, and technologies for alternative biomass utilization. Research interests include: Noninvasive biomass determination using phenoCave resonators Development of sensors like microstrip patch antennas and acoustic volumeters 3D reconstruction of seeds via phenoSeeder and micro-CT analysis Seed trait quantification (volume, surface area, genotype/phenotype impacts) Technologies he works with are applied to seeds, soil columns, and plant analysis, integrating molecular, physiological, and ecological approaches to support resource efficiency and climate adaptation in agriculture.

• Spatial Data Science
• Geostatistics
• Machine Learning
• +۵ مورد دیگر

Professor Peter M. Atkinson is Distinguished Professor of Spatial Data Science at Lancaster University and Executive Dean of the Faculty of Science and Technology since 2015. He also served as Executive Dean of the Faculty of Health and Medicine (2018–2019) and is currently Visiting Professor at the University of Southampton and the Chinese Academy of Sciences in Beijing. Education and Career: Head of School (Geography), University of Southampton (2007–2012) Director of REF Strategy, University of Southampton (2012–2014) Visiting Fellow, Green-Templeton College, Oxford University (2012–2014) Belle van Zuylen Chair, Utrecht University (2015–2016) Research Interests: Professor Atkinson is an interdisciplinary scientist whose work integrates spatial data science , geostatistics , machine learning , and Earth observation to address complex environmental and societal challenges. His research spans: Disease transmission systems (e.g., COVID-19, malaria) Climate change impacts on vegetation and land cover Natural hazard risk assessment (e.g., floods, landslides, asteroid impacts) Spatiotemporal sampling and change-of-support problems Scientific Contributions: With over 300 peer-reviewed journal articles , 9 books , and 50 book chapters , Professor Atkinson has made foundational contributions to geospatial science. His work is widely cited, with an H-index of 78 (Google Scholar) and 57 (Web of Science). Awards and Recognition: Peter Burrough Medal, International Spatial Accuracy Research Association (2016) Distinguished Lecturer, International Association of Mathematical Geosciences (2020) Editor-in-Chief, Science of Remote Sensing Associate Editor, Environmetrics PhD Supervision and Grants: Professor Atkinson has supervised approximately 60 PhD students and led numerous large-scale research grants. He is currently supervising students in Earth Science, Geospatial Data Science, and STOR-i Centre for Doctoral Training. Research Groups and Labs: Centre of Excellence in Environmental Data Science Lancaster Intelligent, Robotic and Autonomous Systems Centre (LIRA) STOR-i Centre for Doctoral Training DSI – Environment Geospatial Data Science

Idunn Aamnes Mostueمشاهده پروفایل

پژوهشگر ارشد

• Sustainable Energy Systems
• Climate Change
• Meteorology
• +۳ مورد دیگر

Idunn Aamnes Mostue is a Doctoral Research Fellow at the Energy Systems Section of the Institute of Transport Economics (ITS), affiliated with the Faculty of Mathematics and Natural Sciences at the University of Oslo. She is part of the Energy Systems Modelling Group, where she develops and explores the highRES open-source power system model to analyze future sustainable European energy systems. Academic Background MSc in Meteorology, University of Oslo BSc in Meteorology, University of Oslo Research Focus Her work addresses energy system resilience to extreme weather events, integrating climate science with power grid modeling. She actively collaborates with the NextGen Energy Climate Group under Reading University, organizing annual workshops. Publications Her recent research (2024) examines climate feedback mechanisms, including ice-albedo dynamics in Greenland and mixed-phase cloud impacts on warming projections, published in The Cryosphere and Communications Earth & Environment . Groups & Collaborations Energy Systems Modelling Group (ITS, University of Oslo) NextGen Energy Climate Group (coordinated by Reading University)

Sofie Hildegard Ryenمشاهده پروفایل

پژوهشگر ارشد

• Paleomagnetism
• Planetary Habitability
• Geophysics
• +۳ مورد دیگر

Sofie Hildegard Ryen is a Research Fellow at the Department of Geosciences , University of Oslo , affiliated with the Center for Planetary Habitability (PHAB) and the Faculty of Mathematics and Natural Sciences . Her research focuses on resolving the 100-million-year paleomagnetic data gap in the Middle Paleozoic and analyzing Earth's magnetic field anomalies. PhD candidate (ongoing), University of Oslo MSc in Geosciences (2020), University of Oslo Her scientific work bridges planetary habitability studies and structural geology, with a particular emphasis on tectonic structures in the Oslo Region, such as imbricate fans, strike-slip faults, and tear faults. She collaborates on the PANDA project and contributes to the DEEP Research School . Recent publications highlight her expertise in Caledonian orogeny, Permo-Carboniferous geology, and magnetic field dynamics. She has co-authored studies with researchers like Annique van der Boon, Mathew Domeier, Anders Lundmark, and Lars Augland. Projects: PANDA (Paleomagnetic Data Gap Analysis), DEEP (Dynamics and Evolution of Earth and Planets) Affiliations: PHAB, Department of Geosciences

Jakub Nowosadمشاهده پروفایل

دانشیار

• Remote Sensing
• Spatial Data Analysis
• Landscape Ecology
• +۳ مورد دیگر

Dr. Jakub Nowosad is an Associate Professor at Adam Mickiewicz University in Poznan, Poland, with a strong affiliation to the Institute of Landscape Ecology at the University of Münster, Germany. As a computational geographer, he specializes in spatial pattern analysis, remote sensing, and geospatial software development. Primary Affiliation: Adam Mickiewicz University, Poznan, Poland Secondary Affiliation: University of Münster, Faculty of Geosciences His research spans spatial data science , focusing on machine learning applications in geography, landscape metrics , and open-source geocomputation . He actively develops and maintains R packages for spatial analysis, including tools for landscape pattern quantification and colorblind-accessible visualization . Recent publications highlight his work on spatial autocorrelation , remote sensing data analysis , and computational ecology . He co-authored key resources such as Geocomputation with R and Geocomputation with Python , emphasizing reproducible workflows. Dr. Nowosad contributes to spatial data education as a co-author of open-source books and instructor at summer schools like OpenGeoHub and EON. He organizes workshops on spatial machine learning and thematic mapping , often involving collaborative R package development. Email: jakub.nowosad@uni-muenster.de