جست‌وجوی استاد و پژوهشگر

• Applied Dynamical Systems
• Data Science
• Computational Biology
• +۴ مورد دیگر

Björn Sandstede is the Alumni-Alumnae University Professor of Applied Mathematics at Brown University's Division of Applied Mathematics. His research focuses on applied dynamical systems, data science, computational biology, nonlinear waves, and pattern formation. He has held faculty positions at The Ohio State University and the University of Surrey before joining Brown in 2008. Key roles at Brown include Department Chair (nine years) and Director of the Data Science Initiative (two years). He has received prestigious awards such as the SIAM JD Crawford Prize, Royal Society Wolfson Research Merit Award, and teaching excellence awards from Brown. Education: PhD in Mathematics, University of Stuttgart (1993) M.A. in Mathematics, University of Heidelberg (1990) Research Interests: Nonlinear waves and pattern formation Computational and mathematical biology Data science and dynamical systems Applications in mRNA localization, zebrafish stripe formation, and multi-omics data analysis Recent Articles: Focus on nonlinear wave dynamics, optimal transport for multi-omics alignment, and topological data analysis in biological systems. These studies bridge theoretical mathematics with computational and biological applications. Awards: 2025 Fellow of the American Mathematical Society Alfred P. Sloan Research Fellowship (2000–2002) SIAM Outstanding Paper Prize (2007) Grants & Leadership: Leads NSF-funded initiatives such as the Research Training Group in Mathematics of Information and Data Science. Co-founded ICERM, Brown's NSF-funded research institute in computational mathematics. Labs & Teams: Collaborates with interdisciplinary groups on projects involving computational biology, optimal transport, and data-driven modeling.

Insa Neuweilerمشاهده پروفایل

استاد

• Fluid Mechanics
• Environmental Engineering
• Geophysical Fluid Dynamics
• +۵ مورد دیگر

Prof. Dr. Insa Neuweiler is a Professor in the Department of Fluid Mechanics and Environmental Physics at Leibniz University Hannover. Her research focuses on fluid mechanics, environmental physics, and multiphase flow in porous media, with applications in geothermal systems, urban hydrology, and offshore engineering. She leads several high-profile projects funded by institutions like the German Research Foundation (DFG) and the Federal Ministry of Education and Research (BMBF). Research Projects : Development of early warning systems for urban flash floods (2024–2029, Lower Saxony Ministry) Modeling fluid-structure interactions in offshore megastructures (2021–2025, DFG) Two-phase flow in geological fractures (2021–2025, DFG) Education : Not explicitly stated in provided texts, but her academic rank indicates doctoral and post-doctoral qualifications. Advising & Grants : Supervises PhD/Master’s students including Simon Berkhahn, Arne Reinecke, and Rahul Krishna Secured over €10M in funding for projects on hydrological modeling, climate impacts, and energy systems Labs/Teams : Active in interdisciplinary teams at the Institute of Fluid Mechanics and Environmental Physics, collaborating with experts in computational fluid dynamics and environmental engineering.

Valentijn Pauwelsمشاهده پروفایل

دانشیار

• Water Management
• Hydrology
• Flood Forecasting
• +۵ مورد دیگر

Valentijn Pauwels is an Associate Professor in Civil & Environmental Engineering at Monash University, specializing in hydrology, flood management, and water resource systems. He holds a PhD from Princeton University (1999) and has held academic positions at Ghent University (Belgium) before joining Monash in 2012. His research focuses on integrating remote sensing, machine learning, and hydraulic modeling to address challenges in flood forecasting, water market dynamics, and climate resilience. Education: Bachelor's in Agricultural Engineering, Ghent University (1994) PhD in Hydrology, Princeton University (1999) Research Interests: Flood risk management and forecasting Remote sensing for hydrological applications Optimization of water resource systems Climate vulnerability assessment Integration of citizen science in environmental monitoring Notable Projects: CSIRO collaboration on hydrogeological modeling with remote sensing data Development of acoustic rainfall sensing systems Analysis of water-economy linkages through market modeling Awards and Recognition: Australian Research Council Future Fellowship (2013) Advising and Grants: Supervises graduate students in flood modeling and water systems Primary investigator on multiple Australian Research Council and CSIRO projects Labs/Teams: Hydrological Remote Sensing Group at Monash University Collaborations with CSIRO Land and Water division

Elisabeth Ullmannمشاهده پروفایل

دانشیار

• Uncertainty Quantification
• Scientific Computing
• Numerical Analysis
• +۳ مورد دیگر

Prof. Elisabeth Ullmann is an Associate Professor for Scientific Computing and Uncertainty Quantification at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information, and Technology and the Department of Mathematics. She holds a PhD from TU Bergakademie Freiberg (2008) and has held academic roles including postdoctoral positions at the University of Bath, University of Hamburg, and University of Maryland. Her research focuses on developing efficient algorithms for uncertainty quantification in partial differential equations with random coefficients, Bayesian inverse problems, and rare event simulation. She is an Associate Editor for the SIAM Journal on Scientific Computing and SIAM/ASA Journal on Uncertainty Quantification , and teaches courses on numerical methods for uncertainty quantification and partial differential equations. Her work emphasizes multilevel Monte Carlo methods, stochastic Galerkin discretizations, and probabilistic numerical methods. Notable contributions include error analysis for rare event probabilities and multilevel estimators for high-dimensional problems. She collaborates internationally and maintains an active research group in Scientific Computing & Uncertainty Quantification at TUM.

Jonathan Pragمشاهده پروفایل

استاد

• Ancient Sicily
• Roman Republic
• Epigraphic Culture
• +۴ مورد دیگر

Professor Jonathan Prag is a leading scholar of ancient Sicily and Roman Republican history, holding dual roles as Tutor in Ancient History at Merton College and Professor of Ancient History at the University of Oxford. His research integrates classical epigraphy with digital humanities, focusing on the cultural and political dynamics of ancient Sicily under Roman rule. Education: MA (Oxon), PhD (London) Research Interests: His work explores Roman imperialism, epigraphic culture, and the application of computational methods to ancient texts. Key projects include the ERC-funded CROSSREADS initiative, the I.Sicily digital epigraphic corpus, and excavations at Halaesa (Sicily). He advocates for open-access scholarship and FAIR data practices in epigraphy. Articles Trends: Recent publications emphasize digital methodologies (e.g., AI-driven text restoration in Nature ), epigraphic analysis of Roman provincial governance, and re-evaluations of Hellenistic-Western Mediterranean cultural interactions. His work bridges archaeology, linguistics, and political history. Awards/Grants: ERC Advanced Grant (CROSSREADS, 2020–2026) AHRC-DFG FAIR Epigraphy co-directorship Leadership in international archaeological and epigraphic projects Grants & Labs: Manages the I.Sicily project and collaborates on the Halaesa excavations. His work involves interdisciplinary teams and digital infrastructure for epigraphic research. Labs/Teams: Collaborates with institutions like the University of Messina and CNRS on epigraphy, archaeology, and computational history.

Sankar Arumugamمشاهده پروفایل

استاد

• Hydroclimatology
• Water Management
• Climate Modeling
• +۷ مورد دیگر

Sankar Arumugam is a Professor and University Faculty Scholar in the Department of Civil, Construction and Environmental Engineering at North Carolina State University (NC State), where he leads the Climate, Hydrology and Water Resources Modeling and Synthesis Group. His research focuses on integrating geospatial data and probabilistic climate information to improve decision-making in water and energy sectors, with expertise in hydroclimatology, spatio-temporal modeling, and large-scale nexus issues like food-water-energy systems. Education: Ph.D. in Water Resources Engineering (Tufts University), M.Sc. in Civil Engineering (IIT Madras), B.E. in Agricultural Engineering (Tamil Nadu Agricultural University). Research interests include: Multi-timescale streamflow forecasting Climate elasticity and hydrological modeling Remote sensing applications for flood prediction Reservoir operations optimization Urban heat island effects Publications highlight advancements in probabilistic hydrological forecasting, climate-water-energy nexus analysis, and reservoir storage optimization. He has pioneered frameworks like GRAPS and COREGS for multi-reservoir systems and seasonal water-power system co-optimization. His work bridges academia and practice through collaborations with institutions like the International Research Institute for Climate and Society (Columbia University) and the World Bank.

• Catchment Hydrology
• Hydrological Partitioning
• Remote Sensing
• +۵ مورد دیگر

Peter A Troch is a Professor in the Department of Hydrology and Atmospheric Sciences at the University of Arizona's College of Science. He specializes in catchment hydrology, with research focusing on hydrological partitioning, remote sensing, and physically-based modeling. His work addresses questions about hydrological processes across scales, including climate-vegetation-soil interactions and landscape evolution. Teaches core courses like Hydrology and Water Resources (HWRS 519 and HWRS 630), emphasizing scientific approaches over engineering methods. Recipient of prestigious awards including the John Dalton Medal (EGU, 2022) and the Agnese Nelms Haury Chair (2014). Conducts research at the Landscape Evolution Observatory (LEO), studying water-rock-biota interactions and ecohydrological processes. His research integrates field experiments, numerical modeling, and data assimilation to improve understanding of water availability, catchment classification, and climate change impacts. Collaborations with interdisciplinary teams address topics like basalt weathering, CO2 sequestration, and soil formation.

Andrew Melatosمشاهده پروفایل

استاد

• Gravitational Waves
• Neutron Stars
• Pulsar Timing
• +۷ مورد دیگر

Andrew Melatos is a Professor in the School of Physics at the University of Melbourne, Australia. His research focuses on gravitational waves, neutron star astrophysics, superfluid dynamics, and interdisciplinary topics like econophysics and art-science collaboration. He has held senior roles in major collaborations such as OzGrav, LIGO, and the Texas Symposium Series. Melatos leads a dynamic research group producing cutting-edge work on pulsar glitches, magnetic mountains, and gravitational wave detection algorithms. His group has pioneered simulations of superfluid vortex avalanches and developed novel statistical methods for LIGO data analysis. Melatos has advised over 40 PhD and Master's students, many of whom now hold academic or industry leadership roles globally. His work bridges fundamental physics with applications in climate science, finance, and public outreach. Education: BSc (University Medal), University of Sydney (1988-1991) PhD in Physics, University of Sydney (1992-1995) Miller Fellow, UC Berkeley (1997-2000) Research Fellow, Caltech (1995-1997) Key Appointments: Chair, Texas Symposium Steering Committee (2006-2008) LIGO Scientific Collaboration Council (2014-present) Australia Telescope Time Assignment Committee (2002-2004) Research Themes: Melatos' work spans gravitational wave astrophysics, pulsar timing anomalies, superfluid turbulence in neutron stars, and interdisciplinary projects like econophysics modeling and art-science collaborations with visual artist Briony Barr. His group's recent breakthroughs include explaining pulsar glitch recovery via superfluid vortex dynamics and developing hidden Markov models for glitch detection. Publications & Impact: Over 15 key articles in areas like neutron star magnetospheres, LIGO signal processing, and econophysics. Notable collaborations include simulations of magnetic mountains and contributions to the historic 2017 gravitational wave-neutrino electromagnetic counterpart discovery.

Sean Flemingمشاهده پروفایل

عضو هیئت علمی

• Hydrology
• Hydrometeorology
• Climate Change Impacts
• +۹ مورد دیگر

Sean Fleming is a Courtesy Professor at Oregon State University in the College of Earth, Ocean, and Atmospheric Sciences and the Water Resources Graduate Program. He also holds an adjunct position at the University of British Columbia. His work bridges academia, government, and industry, with a focus on data science applications in environmental science and hydrometeorology. B.Sc., Geophysics, University of British Columbia, 1994 M.S., Geophysics, Oregon State University, 1997 M.S., Geology (major), Civil Engineering (minor), Oregon State University, 1998 Ph.D., Geophysics, University of British Columbia, 2004 Sean Fleming's research centers on advancing data science, machine learning, and AI applications to environmental forecasting, particularly in hydrology and climate. He integrates process physics, remote sensing, and expert knowledge into predictive models. His work emphasizes operational implementation in real-world water management systems. His recent publications focus on AI-driven water supply forecasting, satellite remote sensing for snow monitoring, climate change impacts on glaciers and rivers, and complex systems theory in environmental dynamics. He has contributed to improving operational river forecast systems using explainable AI and ensemble modeling. Associate Editor, Water Resources Research World Meteorological Organization (WMO) Commission for Hydrology member Invited expert reviewer, IPCC reports Invited expert reviewer, US National Climate Assessment Fleming serves on graduate student supervisory committees at OSU and UBC, providing industry and policy perspectives to academic research. He has led significant projects such as the NASA Western Water Action Office, supporting the use of Earth observations in water management. His work often involves multi-institutional and international collaborations. He is actively involved in public outreach, having authored the book Where the River Runs , given lectures at the Smithsonian, and appeared in media outlets like NPR and Scientific American.

Lai-yung Leungمشاهده پروفایل

استاد

• Climate Modeling
• Hydrological Cycle
• Land-Atmosphere Interactions
• +۶ مورد دیگر

Lai-yung (Ruby) Leung is a Battelle Fellow at Pacific Northwest National Laboratory with a courtesy appointment at Oregon State University's College of Earth, Ocean, and Atmospheric Sciences. She serves as Chief Scientist of the Energy Exascale Earth System Model (E3SM) supported by the U.S. Department of Energy and has organized key workshops sponsored by major scientific agencies including DOE, NSF, NOAA, and NASA. Dr. Leung's research spans climate and hydrological cycle modeling, land-atmosphere interactions, orographic processes, monsoon climate, climate extremes, land surface processes, and aerosol-cloud interactions. Her work on climate change impacts has been featured in Science, Popular Science, Wall Street Journal, National Public Radio, and major newspapers worldwide. She has published over 500 peer-reviewed papers and serves as editor for the American Meteorological Society's Journal of Hydrometeorology. Her recent publications demonstrate expertise in high-resolution climate modeling, mesoscale convective systems, land-atmosphere feedbacks, and climate extremes. Her work increasingly incorporates machine learning approaches for climate prediction and model evaluation, while maintaining focus on fundamental physical processes in Earth system models. Elected Member, National Academy of Engineering Elected Member, Washington State Academy of Sciences Fellow, American Geophysical Union Fellow, American Meteorological Society Fellow, American Association for the Advancement of Science AMS Hydrologic Sciences Medal, 2022 U.S. Department of Energy Office of Science Distinguished Scientist Fellow, 2021 Reuter's Hot List of top 1,000 climate scientists, 2021 Dr. Leung serves on advisory panels and National Academies committees defining future priorities in Digital Twin, AI/ML, climate modeling, hydroclimate, and water cycle research. She has been invited to deliver numerous distinguished lectures globally, including the Snoeyink Distinguished Lecturer at University of Illinois and Inaugural Leaders in Discovery Lecture Series at University of Iowa.

• Forest Biometrics
• Forest Ecosystem Carbon Cycle
• Forest Ecosystem Simulation Model
• +۲ مورد دیگر

Dr. Xinyuan Wei is an Assistant Research Professor in Forest Ecosystem Modeling at the School of Forest Resources, University of Maine, having joined in July 2023. Previously, he conducted research at Oak Ridge National Laboratory. His educational background includes a PhD in Forest Resources from the University of Maine, an MS in Geography from the University at Buffalo, and a BE in Geographic Information System from Nanjing Forest University. His research integrates quantitative approaches to study forest ecosystems, with core interests in: Forest Biometrics : Statistical modeling of forest structure and growth. Carbon Cycle Dynamics : Quantifying carbon fluxes in terrestrial and aquatic systems. Ecosystem Simulation : Developing models to predict climate change impacts. Geospatial Technologies : Applying remote sensing and GIS for landscape analysis. His publications (2018-2024) demonstrate a consistent focus on carbon cycling, climate impacts on forests, and ecosystem modeling. Trends include watershed-scale dissolved organic carbon transport, climate-forest interactions, and carbon sequestration in wood products, leveraging interdisciplinary methods from biogeochemistry, remote sensing, and statistical modeling.

Alex Rybchukمشاهده پروفایل

پژوهشگر

• Computational Fluid Dynamics
• Boundary Layer Meteorology
• Data Assimilation
• +۵ مورد دیگر

Alex Rybchuk serves as a Researcher III in Computational Science at the National Wind Technology Center (NWTC), part of the National Renewable Energy Laboratory (NREL). His work focuses on advancing understanding of the lower atmosphere with direct applications to wind energy systems, particularly through computational modeling and data-driven approaches. Education: Bachelor of Mechanical Engineering from Cooper Union for the Advancement of Science and Art Master of Science in Mechanical Engineering from University of Colorado Boulder PhD in Mechanical Engineering from University of Colorado Boulder Rybchuk's research integrates Computational Fluid Dynamics with Boundary Layer Meteorology to address wind energy challenges. His core expertise spans Data Assimilation techniques and Machine Learning applications for atmospheric modeling, with rigorous emphasis on Model Validation, Verification, and Uncertainty Quantification . Recent work targets offshore wind resource assessment in California and turbine inflow characterization using generative AI. His fingerprint reveals deep specialization in Wind Resources (100%), Offshore Wind (97%), and California-specific wind phenomena (73%), with significant contributions to Resource Assessment methodologies. Analysis of his 2024-2025 publications shows convergent themes: machine learning applications for hurricane modeling (2025), generative AI reconstruction of turbine inflow (2025), and mesoscale model validation for California wind corridors (2025). These works consistently address wind speed bias correction, atmospheric boundary layer dynamics, and offshore resource assessment - reflecting his focus on bridging observational data with high-fidelity simulations. Rybchuk actively collaborates through NREL's National Wind Technology Center on field campaigns like RAAW, where he develops machine learning frameworks to connect turbine inflow observations with simulations. His technical reports and peer-reviewed articles demonstrate sustained contributions to wind energy science without mention of formal advising roles or external grants in the provided materials.

• Mathematics
• Computer Science
• Applied Mathematics
• +۶ مورد دیگر

Anthony Nouy is a Professor at the Department of Mathematics, Computer Science, and Biology (MIB) at École Centrale de Nantes. His research spans Mathematics, Computer Science, and Computational Biology, with a focus on approximation theory, tensor networks, and stochastic optimization. His work explores nonlinear manifold approximation dimension reduction in feature spaces stochastic gradient descent optimization moment methods for optimal transport and PDEs model reduction and tensor geometry Recent publications highlight trends in machine learning, numerical analysis, and computational mathematics, particularly through compositional polynomial networks, Poincaré inequality surrogates, and tree tensor formats. Collaborations include researchers like Alexandre Pasco, Philipp Trunschke, and Mazen Ali. He is affiliated with the Jean Leray Mathematics Laboratory and maintains a personal webpage for updates. Co-authors of recent publications include Antoine Bensalah, Joel Soffo, and Alexandre Pasco (2025) Robert Gruhlke, Philipp Trunschke (2024) Clément Cardoen, Swann Marx, Nicolas Seguin (2024) Mazen Ali, Antonio Falcó, Wolfgang Hackbusch (2023)

• Plant Metabolism
• Metabolomics
• Plant Stress Physiology
• +۳ مورد دیگر

Prof. Dr. Alisdair Fernie serves as a Research Group Leader within the Department of Root Biology and Symbiosis at the Max Planck Institute of Molecular Plant Physiology in Potsdam, Germany. His position as a full Professor reflects his leadership in plant metabolic research, where he directs the Central Metabolism research group investigating fundamental biochemical processes in plants. His research spans Plant Metabolism, Metabolomics, Plant Stress Physiology, Molecular Plant Biology, Plant Biochemistry, and Photosynthesis. Fernie employs advanced omics technologies to dissect metabolic networks, particularly focusing on how plants reconfigure their biochemistry in response to environmental stresses and developmental cues. His work integrates systems biology approaches to understand metabolic fluxes and regulatory mechanisms across diverse plant species. Analysis of his 2024-2025 publications reveals dominant themes in plant metabolomics, stress adaptation mechanisms, and biotechnological applications for crop improvement. His research frequently utilizes model systems like Arabidopsis alongside economically important crops including tomato, rice, maize, and citrus, with particular emphasis on postharvest physiology, nutrient signaling, and the molecular basis of specialized metabolism. Prof. Fernie leads the Central Metabolism research group, which investigates core metabolic pathways and their regulation through innovative combinations of biochemical, genetic, and computational approaches. His team's work on organelle interactions, lipid metabolism, and stress-responsive metabolic reprogramming has positioned them at the forefront of plant systems biology research.

Arnold Heeminkمشاهده پروفایل

استاد

• Large-scale systems
• Data assimilation
• Inverse problems
• +۱ مورد دیگر

Arnold Heemink is a full professor of Applied Analysis at the Delft Institute of Applied Mathematics, part of the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. He has maintained this position since 1993, having previously served as a part-time professor at the same institution from 1990-1993 while also working at Rijkswaterstaat where he was Head of the Mathematical Modeling section. His educational background includes a B.Sc. in Applied Mathematics (Systems Theory) from the University of Twente (1974-1978), followed by an M.Sc. in Applied Mathematics (Mathematical Physics) from the same institution (1978-1980), and finally a PhD in Applied Mathematics completed in 1986. 1974-1978: University of Twente, B.Sc. Applied Mathematics (Systems Theory) 1978-1980: University of Twente, M.Sc. Applied Mathematics (Mathematical Physics) 1980-1986: University of Twente, PhD in Applied Mathematics Professor Heemink's research focuses on large-scale systems, data assimilation, inverse problems, and numerical schemes for stochastic differential equations. His work bridges theoretical mathematics with practical environmental and physical applications, particularly in atmospheric and oceanic modeling. Recent publications demonstrate his expertise in applying advanced mathematical techniques to real-world problems including air quality monitoring, wave data assimilation, and magnetic state prediction. His publication record shows consistent output with multiple high-impact papers in 2023-2025, primarily focusing on environmental applications of data assimilation techniques. These works span diverse domains from atmospheric transport modeling to ocean wave prediction and magnetic field analysis, all united by his core expertise in mathematical modeling and data assimilation. While specific awards are not listed in the available information, Professor Heemink maintains an active research profile with collaborations spanning multiple countries and institutions, as evidenced by his international co-authorship patterns. His current work appears focused on advancing data assimilation methodologies for environmental monitoring systems, with particular attention to air quality networks, ocean wave prediction, and atmospheric modeling. He continues to supervise research activities within the Mathematical Physics section of the Delft Institute of Applied Mathematics.