جست‌وجوی استاد و پژوهشگر

• Catalysis
• Inorganic Chemistry
• Materials Science
• +۴ مورد دیگر

Prof. Dr. Thomas Müller is a Professor of Inorganic Chemistry at Carl von Ossietzky University Oldenburg, leading the Müller Research Group. His work focuses on Lewis pairs, frustrated Lewis systems, and catalysis using main-group elements like silicon and phosphorus. He has pioneered research on environmentally friendly catalysts for industrial applications, such as hydrogen splitting and CO₂ reduction. His group collaborates internationally with institutions like Tohoku University and the University of Western Ontario. Research Highlights: Frustrierte Lewis-Paare (FLPs), silicium-based catalysts, and sustainable chemistry. Notable Achievements: Co-developed FLPs for hydrogen activation, earned awards for student research, and published in Angewandte Chemie . Key research interests include synthetic inorganic chemistry, materials science, and applications of main-group elements in green chemistry. His team's work on silicium-based Lewis acids has advanced hydrodefluorination and other catalytic processes. Students: Supervised numerous PhD and master’s students, including Marie Würdemann (prize winner), Saskia Rathjen, and Zhaowen Dong (Best PhD Thesis, 2018). Labs/Teams: Active in experimental and theoretical studies of main-group element chemistry, with facilities for advanced spectroscopy and synthesis.

• Space Physics
• Ionospheric Physics
• Magnetosphere-Thermosphere-Ionosphere Coupling
• +۴ مورد دیگر

Daniel Billett is a space physicist specializing in magnetosphere-thermosphere-ionosphere coupling dynamics, currently holding the prestigious ESA Living Planet Fellowship. His research leverages the Super Dual Auroral Radar Network (SuperDARN) alongside Fabry-Perot Interferometers, Incoherent Scatter Radars, and all-sky imagers to investigate energy transfer during space weather events. His educational foundation includes: PhD in Space Physics from Lancaster University (2016-2019), thesis: "The great space weather washing machine: Examining the dynamics of high-latitude ionosphere-thermosphere coupling" PGCE in post-compulsory education from Cardiff University (2015-2016) MPhys in Astrophysics from Aberystwyth University (2011-2015) Billett's research centers on quantifying energy pathways between solar wind drivers and Earth's upper atmosphere, with particular focus on aurorally driven conductivity enhancements and thermospheric wind dynamics . His work examines how geomagnetic storms redistribute energy through frictional heating and Poynting flux, addressing critical questions about atmospheric responses to charged particle bombardment and implications for space weather forecasting. Analysis of his 15 most recent publications reveals consistent emphasis on ion-neutral coupling mechanisms, with recurring methodological themes in multi-instrument validation (SuperDARN with satellite data), high-resolution mapping techniques, and quantification of under-sampled energy transfer scales. Key topical threads include GNSS scintillation during cusp events, thermospheric responses to extreme storms like the 2022 Starlink incident, and turbulence characterization around auroral arcs. His scientific recognition includes: ESA Living Planet Fellowship (2021) JSPS Fellowship for Research in Japan (2019) Lancaster University Dean's Award for PhD excellence (2018) Billett has secured competitive research funding through major international fellowships, with the ESA Living Planet Fellowship supporting his current work on global thermospheric responses. His publications demonstrate extensive collaboration across North American, European, and Japanese institutions, reflecting deep integration within the space physics community. He contributes to infrastructure development through projects like Borealis radar systems and pyDARN software, enhancing community-wide observational capabilities. As a core SuperDARN collaboration member, Billett participates in global networks of radar facilities and complementary instrumentation teams. His recent work with the 2022 Starlink storm response highlights growing focus on space weather impacts on commercial space assets, indicating strategic expansion toward applied space climate research while maintaining fundamental ionospheric physics investigations.

• Computational Mechanics
• Numerical Methods (Meshfree/XFEM/Isogeometric)
• Mixed Variational Methods
• +۳ مورد دیگر

Jack HALE is a Research Scientist at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), Department of Engineering. He joined Prof. Stéphane Bordas' team in 2013, focusing on computational mechanics and numerical methods. His work integrates advanced techniques like meshfree methods, XFEM, and isogeometric analysis to address challenges in solid mechanics and high-performance computing. Education : PhD in Aeronautics, Imperial College London (2009-2013), supervised by Dr. Pedro M. Baiz Villafranca. MEng in Engineering, University of Bristol (2004-2008). Research exchange at Rice University (2006-2007) on cross-flow filtration processes. Research Interests : Implicit boundary methods for medical image-based simulations. Development of scalable meshfree/XFEM/isogeometric analysis frameworks. Mixed variational methods to resolve locking phenomena in solid mechanics. High-performance computing for distributed parallel systems. Publications & Software : His 50+ publications emphasize open-access research via ORBilu, with a focus on FEniCSx-based tools (e.g., DOLFINx, FEniCS-shells). Recent work addresses Bayesian model selection, melt instability identification, and SAR data assimilation in aquifer modeling. Collaborations : Open to academic/industrial partnerships in computational mechanics, material science, and biomedical engineering.

Manish Kumarمشاهده پروفایل

دانشیار مدعو

• Health Systems Strengthening
• Digital Health
• Health Information Systems
• +۴ مورد دیگر

Manish Kumar, MPH, PhD, is an Adjunct Associate Professor in the Department of Public Health Leadership and Practice and the Department of Health Behavior at the University of North Carolina at Chapel Hill's Gillings School of Global Public Health. He currently leads the Global Health Finance Data team at Guidehouse, Inc., focusing on strategic data-driven solutions for health systems strengthening and digital health. His prior roles include Technical Lead at the Carolina Population Center and Principal Investigator for USAID-funded projects. Education: PhD (ABD) in Health Informatics from the Carolina Health Informatics Program, University of North Carolina at Chapel Hill; MPH in Public Health Leadership (specializing in public health informatics); MSc degrees from Wageningen University (Netherlands) and Pant University (India). Research interests include health information systems, digital health maturity models, and implementation science. He has contributed to global initiatives such as the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) and malaria surveillance systems. Awards include the Rotary Peace Fellowship (2013-2015), Delta Omega Service Award (2015), and induction into the Frank Porter Graham Graduate Honor Society. His work emphasizes health equity, data utilization, and evidence-based decision-making in low-resource settings.

Lorenzo Polvaniمشاهده پروفایل

استاد

• Atmospheric Dynamics
• Climate Dynamics
• Geophysical Fluid Dynamics
• +۲ مورد دیگر

Lorenzo Polvani is the Maurice Ewing and J. Lamar Worzel Professor of Geophysics at Columbia University, specializing in atmospheric and climate dynamics, geophysical fluid dynamics, and numerical climate modeling. His research explores planetary atmospheres and their complex interactions with external forcings. Education: Ph.D. in Oceanography (MIT, 1988), B.Sc. in Physics (McGill University, 1981) Current research focuses on Arctic amplification, radiative feedbacks, and climate responses to CO2 forcing and volcanic activity. His work bridges geophysical fluid dynamics with practical climate modeling techniques. Recent publications highlight nonlinear climate responses, stratospheric dynamics, and cloud feedback effects on hydrological sensitivity. Key keywords: Arctic Sea Ice, Radiative Forcing, Brewer-Dobson Circulation, Climate Sensitivity, Atmospheric Chemistry, Earth System Modeling. For detailed contact, reach him at lmp3@columbia.edu or visit his lab at Columbia University .

Noemi Petraمشاهده پروفایل

دانشیار

• Large-scale inverse problems
• PDE-constrained optimization
• Uncertainty quantification
• +۴ مورد دیگر

Noemi Petra is an Associate Professor in the Department of Applied Mathematics at the University of California, Merced , with research focusing on large-scale inverse problems , PDE-constrained optimization , uncertainty quantification , and optimal experimental design . Her work bridges mathematical theory with practical applications in geophysics and energy systems. Current Role: Associate Professor at UC Merced Research Interests: Large-scale inverse problems, PDE-constrained optimization, uncertainty quantification Her research has produced significant contributions in Bayesian inference for ice sheet modeling, power system estimation , and scalable optimization algorithms . She has developed open-source software frameworks like hIPPYlib-MUQ for data-model integration. Key research trends include: Bayesian Methods for geophysical inverse problems Optimization Techniques for power systems and ice dynamics Scalable Algorithms for high-dimensional uncertainty quantification Software Development for large-scale inverse problems Scientific awards: NSF CAREER award (2017) for large-scale Bayesian inverse problems She actively collaborates on ice sheet dynamics and power grid modeling , with software tools adopted in academic and industrial applications.

• Scientific Computing
• Numerical Analysis of PDEs
• High-Performance Computing
• +۷ مورد دیگر

PD Dr. Florian Frank is Privatdozent (senior lecturer with full teaching licence) for Applied Mathematics at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and heads the Bavarian research project „Parallel mesh loading and partitioning for large-scale simulation“ . His expertise spans high-performance computing, phase-field and discontinuous Galerkin methods, digital-rock physics, and reactive transport in porous media. Education & career 2022 – Venia legendi (private lecturer), Mathematics, FAU 2019 – Dr. habil., Mathematics, FAU 2013 – Dr. rer. nat., Applied Mathematics, FAU 2008 – Graduate Mathematician, University of Frankfurt 2021-2022 (acting) W2 Professor Scientific Computing, FAU 2018-2021 (acting) W2 Professor Mathematical Modelling, FAU 2017-2018 Senior Postdoc, CAAM, Rice University, USA 2014-2017 Postdoc, CAAM, Rice University, USA Research interests Frank focuses on the development and analysis of numerical schemes for partial differential equations that govern multiphase, multicomponent and reactive processes in porous or biological media. Key themes include discontinuous Galerkin and finite-volume methods , physics-preserving discretizations , high-performance computing , and digital-rock-based pore-scale simulations . He couples phase-field approaches with (Navier–)Stokes, Cahn–Hilliard, Nernst–Planck and density-gradient equations to quantify flow, transport, colloid dynamics and interfacial phenomena. Recent publications reveal a clear trend toward data-driven modelling : convolutional neural networks are trained with direct numerical simulation data to predict permeability and diffusion coefficients from 3-D micro-CT images, while advanced preconditioners and regularization techniques accelerate multiphase thermodynamic computations. Awards & recognition 2020 – Emmy-Noether-Prize der Naturwissenschaftlichen Fakultät, FAU 2017 – Promotion to Senior Postdoctoral Research Associate , George R. Brown School of Engineering, Rice University Projects, tools & supervision Frank currently leads a Bavarian state-funded project on parallel mesh handling for large-scale simulations. Together with collaborators he maintains the open-source MATLAB/GNU Octave toolbox FESTUNG for discontinuous Galerkin methods. Since 2018 he has (co-)supervised ten BSc and MSc theses on topics ranging from Stokes preconditioning to enriched Galerkin shallow-water solvers, regularly serves as reviewer for more than a dozen international journals, and is guest editor of special issues in Computational Geosciences and Oil & Gas Science and Technology .

Katarzyna Mirekمشاهده پروفایل

استادیار

• Geoinformatics
• Web Technologies
• Applied Computer Science
• +۳ مورد دیگر

Dr. Katarzyna Mirek is an Assistant Professor at the Department of Geoinformatics and Applied Computer Science, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology in Kraków. Her contact details include email kmirek@agh.edu.pl and office location at room 319 (A-0 building). Teaching: Courses include Internet Techniques , Web Application Programming (PHP) , Advanced Internet Techniques , and Satellite Radar Interferometry for full-time studies, plus Website Design for postgraduate programs. Consultations: Tuesdays 11:00-12:00 in room 319 (A-0). Her research focuses on geoinformatics applications in environmental protection, web technologies for geospatial data, and software development for scientific computing. This aligns with her teaching of internet-based geospatial tools and advanced web programming.

• Digital Rock Physics
• Computational Pore-Scale Physics
• Tomographic Imaging
• +۹ مورد دیگر

Professor Christoph Arns is a full Professor at the University of New South Wales (UNSW) School of Engineering, specializing in Mineral and Energy Resources Engineering. He has been at UNSW since 2008 and has held the position of full Professor since 2014. Currently, he leads the Geoenergy and Geostorage discipline within the school. Prior to joining UNSW, he was a research fellow at the Australian National University from 2001-2008. Professor Arns obtained his Dipl. Phys. from RWTH Aachen, Germany in 1996 and his PhD in Petroleum Engineering from UNSW Sydney in 2002. His academic background combines physics and petroleum engineering, creating a unique interdisciplinary perspective for his research. His primary research focus is on Digital Rock Physics, where he has pioneered computational pore-scale physics based on tomographic images. He specializes in integrating 3D tomographic imaging technology with NMR techniques for petrophysical applications, with particular emphasis on heterogeneity analysis. His work spans multiple sub-disciplines including pore-scale modeling, digital core analysis, rock physics, reservoir characterization, and Minkowski functionals for structural analysis. Professor Arns has developed the MPI-parallel software package 'morphy' for computational physics operating on segmented tomographic images, which includes sophisticated NMR response modeling, electrical property calculations, permeability estimation, elastic moduli determination, and morphological property analysis. His research has substantial industry relevance, as evidenced by his role as a founding member of Digital Core Pty Ltd, an ANU/UNSW spin-off that was sold to FEI for $76 million in 2014 and is now part of ThermoFisher. He has received significant research support through three successive Australian Research Council (ARC) fellowships. His scholarly contributions are reflected in numerous publications spanning from 2000 to 2025, with recent work focusing on advanced computational methods, machine learning applications in rock physics, and detailed analysis of fluid-rock interactions at the pore scale. Professor Arns maintains active leadership roles in multiple professional societies including Interpore (lifetime member, former council chair 2016-2019), Society of Core Analysts (Australasia Regional Director since 2016), Society of Petrophysicists & Well Log Analysts, Society of Exploration Geophysicists, and Society of Petroleum Engineers.

David Chelidzeمشاهده پروفایل

استاد

• Nonlinear Vibrations
• Structural Health Monitoring
• Dynamical Systems
• +۳ مورد دیگر

Professor David Chelidze is a faculty member in the Mechanical, Industrial and Systems Engineering department at the University of Rhode Island . His research spans nonlinear vibrations, structural health monitoring, and fatigue evolution in engineered systems. He is the director of the Nonlinear Dynamics Laboratory , where he explores topics like modal testing, dynamical systems theory, and damage prognosis. Education: Ph.D., Engineering Science and Mechanics, Pennsylvania State University, 2000 M.S., Mechanical Engineering, Southern Illinois University, 1995 Diploma in Mechanical Engineering, Georgian Technical University, 1992 Research Interests focus on nonlinear dynamics, particularly vibration-based structural health monitoring, smooth mode decomposition for modal analysis, and phase space warping for fatigue damage detection. His work bridges theoretical advancements with practical applications in materials science, offshore engineering, and biomedical diagnostics. Publication Trends emphasize fatigue life estimation under variable loading, nonlinear model reduction techniques, and vortex-induced vibration analysis. Key subfields include 3D printing structural integrity , biomechanical fatigue monitoring , and hydrodynamic stability of flexible cylinders . Scientific Awards: NSF Career Award, 2009 U.S. Patent: General Method for Tracking Hidden Damage in Machinery Components (with Cusumano J, Chatterjee A), 2003 Grants include projects funded by the RI Commerce Corporation (2022) and collaborative efforts with the University of Connecticut/Office of Naval Research (2021). His lab also engages in digital twinning and physics-informed reduced-order modeling . Laboratory : The Nonlinear Dynamics Laboratory at URI develops tools for damage diagnosis in engineered, geophysical, and biological systems. The lab contributes to software like Smooth Mode Decomposition and Geometry-informed Phase Space Warping , with applications in fatigue monitoring and nonlinear system identification.

• Time series
• Modeling
• Forecasting
• +۲ مورد دیگر

Dr. Salim Jibrin Danbatta is an Assistant Professor in the Department of Computer Engineering at Uskudar University. Born on May 13, 1987, in Kano State, Nigeria, he has established himself as a researcher specializing in time series analysis, modeling, and forecasting techniques with applications across multiple domains. His educational background includes: BSc in Information Technology from Limkokwing University of Creative Technology, Malaysia (2011) MSc in Information System Engineering from Near East University, Cyprus (2014) Ph.D. in Software Engineering from Firat University, Turkey (2022) Dr. Danbatta's research focuses on time series data, covering modeling, forecasting, analysis, and Monte Carlo simulation schemes. His work spans applications in environmental science, tourism, rainfall prediction, and software engineering. He has published papers in SSCI, SCI/E, ESCI journals and IEEE conference proceedings, with an h-index of 5 and 218 total citations according to Scopus metrics. His recent publications demonstrate a consistent application of hybrid time-series models and Monte Carlo simulation techniques to address practical challenges, particularly in environmental monitoring and prediction in Nigeria. His research shows increasing sophistication in combining multiple modeling approaches to improve forecasting accuracy while addressing uncertainty. Dr. Danbatta serves in several administrative roles including Student Adviser, Member of the Education Commission, and Member of the Erasmus and Foreign Relations Commission at Uskudar University. Prior to his current position, he taught at the Kano State Institute for Information Technology and worked as a computer officer at the Kano State Ministry of Science and Technology for three years.

Denis Voskovمشاهده پروفایل

دانشیار

• Reservoir Simulation
• CO2 Sequestration
• Geothermal Energy
• +۴ مورد دیگر

Denis Voskov is an Associate Professor at Delft University of Technology (Faculty of Civil Engineering and Geosciences, Department of Geoscience & Engineering). He also holds an Adjunct Professor position at Stanford University (Department of Energy Resources Engineering, USA). His academic career spans roles as Senior Researcher (2007-2015) and Research Associate (2005-2007) at Stanford, CTO of Rock Flow Dynamic (2005-2008), and engineering positions in oil companies and research institutions in Russia (2000-2005). Current: Head of Reservoir Engineering Section (2024-present) Current: Associate Professor at TU Delft (2015-present) Current: Adjunct Professor at Stanford University (2016-present) Voskov specializes in modeling complex subsurface systems , focusing on reactive flow and transport in altering porous media, scale translation for physical processes, high-performance computing for forward/inverse problems, thermal/geothermal process simulation, CO2 sequestration, and nonlinear solver analysis. His work bridges computational methods (finite volume frameworks, augmented flash calculations, operator-based linearization) with energy transition applications like geological carbon storage and geothermal resource management. Key trends in his recent publications (2024-2025) include: advanced CO2 storage mechanisms (capillary pinning, halite precipitation), multiphysics simulation frameworks (thermal-hydro-mechanical-compositional models), data assimilation for geothermal reservoirs, physics-informed neural networks for subsurface problems, and open-source tools like DARTS-well. Topics frequently intersect with energy transition, reservoir heterogeneity, and numerical robustness. Voskov's lab and team activities center on subsurface energy systems at TU Delft, including the campus geothermal project for direct-use heating and digital twin development for geothermal reservoirs. He collaborates internationally, particularly with Stanford University, and leads initiatives in GPU-based Monte Carlo simulations for uncertainty quantification.

• Condensed Matter Physics
• Materials Science
• Lattice Dynamics
• +۵ مورد دیگر

Martin Dove is Professor of Condensed Matter and Materials Physics at the School of Physics and Astronomy, Queen Mary University of London, where he conducts research on structural properties of materials using neutron and X-ray scattering techniques. His work bridges fundamental physics and materials engineering with applications in energy technologies and functional materials. His primary research focuses on negative thermal expansion mechanisms, lattice dynamics of framework materials, and the development of computational methods like reverse Monte Carlo modeling. He investigates phase transitions in perovskites, thermal expansion anomalies in ceramics, and structural properties of disordered systems through total scattering analysis and molecular simulations. Analysis of his 2023-2025 publications reveals sustained leadership in negative thermal expansion research, with significant contributions to understanding scandium trifluoride systems and copper pyrophosphate transitions. His recent work extends to perovskite materials for energy applications, metal-organic frameworks, and advanced scattering data analysis techniques, demonstrating consistent innovation in materials characterization methods.

• Geophysics
• Earth Science
• Information Technology
• +۳ مورد دیگر

Johann Boudot is a Researcher in the IT Department at the Institut de Physique du Globe de Paris (IPGP), part of Université Paris Cité . His work focuses on computational infrastructure and data management for geophysical research. Contact: Phone: 0183957800 Office: Bureau 243, 1, rue Jussieu, 75238 Paris cedex 05 Research Interests: Geophysical data systems Scientific computing IT infrastructure for research

Ali GÜLBAĞمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Neural Networks
• FPGA Design
• +۳ مورد دیگر

Assoc. Prof. Dr. Ali GÜLBAĞ is an academic at the Faculty of Computer and Information Sciences , Sakarya University , specializing in Computer Engineering . His career spans over two decades, focusing on FPGA-based hardware design, machine learning applications, and educational methodologies in computer architecture. Doctorate (2003-2006): Quantitative determination of volatile organic compounds using artificial neural network and fuzzy logic-based algorithms MSc (1998-2000): Building automation using telephone lines BSc (1994-1998): Electrical-Electronics Engineering His research interests include Artificial Neural Networks , FPGA Design , and Water Resource Management , with applications in seismic event differentiation, environmental modeling, and educational technologies. Recent work emphasizes water consumption prediction using machine learning. Key projects: BZK.SAU.FPGA microcomputer architecture , Remote FPGA laboratories Publications demonstrate expertise in combining machine learning techniques (ANNs, gradient boosting, random forests) with hardware implementations for real-world problem-solving.