Parallel Computing in Geosciences Professors and Supervisors

Oubay Hassanمشاهده پروفایل

استاد

Swansea UniversityUnited Kingdom

Professor Oubay Hassan is a Personal Professor in Civil Engineering at Swansea University's School of Aerospace, Civil, Electrical and Mechanical Engineering. He has been with the university since 2002, advancing from Lecturer to Senior Lecturer to Reader before becoming a Professor. His research focuses on computational methods for engineering analysis and design, particularly in computational fluid dynamics (CFD), computational electromagnetism, and unstructured mesh generation. He co-developed the FLITE system with BAE Systems and Airbus, pivotal for aerodynamic design of supersonic vehicles like Thrust SSC (1997 World Land Speed Record) and Bloodhound SSC. Hassan has led projects funded by grants such as 'Advanced Mesh Generation' and 'CFD Technologies for Bloodhound.' His career highlights include an MBE (1998), Catherine Richards Prize (1999), and Royal Academy of Engineering Fellowship (2012). He teaches modules like Advanced Fluid Flow Simulation and Structural Mechanics, and supervises PhD research in areas like Mach-Uniform schemes and AI-driven mesh optimization. Collaborations span industries and institutions, emphasizing public engagement through projects like Bloodhound's educational outreach. Research Interests: CFD, mesh adaptation, high-speed flows, parallel processing, and aerospace engineering applications. Awards: MBE, Catherine Richards Prize, Royal Academy of Engineering Fellowship. Grants/Projects: Includes collaborations with BAE Systems, Airbus, and projects like 'Unstructured Mesh Technology for Viscous Flows.' Labs/Teams: Leads Swansea's computational engineering teams, integrating CFD, electromagnetics, and meshing innovations.

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Jason Phipps-Morganمشاهده پروفایل

استاد

Cornell UniversityUnited States

Jason Phipps-Morgan is a Professor in the Department of Earth and Atmospheric Sciences at the College of Engineering, Cornell University. His work bridges geodynamics, computational modeling, and Earth system processes, with a focus on large-scale mantle and crustal dynamics. Research Interests: His research centers on geodynamic modeling of mantle convection, particularly the role of a plume-fed asthenosphere, as well as fluid and melt migration in subduction zones and mid-ocean ridges. He develops advanced 3D parallel computational tools to simulate highly nonlinear interactions between deformation, fluid flow, and chemical reactions. His recent publications reflect a strong trend in multiscale, multiphysics numerical modeling applied to fundamental Earth processes, including hydrothermal circulation, carbon sequestration, and bend-faulting in subducting plates. Scientific Awards: Professeur, College de France (1996) James B. Macelwane Award, American Geophysical Union (1995) Cecil and Ida Green Scholar (1985) Education: Brown University, 1985 Jason Phipps-Morgan has led significant research initiatives in geodynamics and has contributed to major advancements in numerical modeling of Earth systems. His work has been supported by prestigious fellowships and awards, and he continues to develop innovative computational platforms for exploring planetary dynamics. While no formal advising or grant details are listed, his collaborative publications suggest active engagement with national and international research teams.

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Steffen Winterمشاهده پروفایل

مدرس

Karlsruhe Institute of TechnologyGermany

Steffen Winter is a Lecturer (PD Dr.) at the Institute of Stochastics, Karlsruhe Institute of Technology (KIT). His research specializes in Fractal Geometry, Geometric Measure Theory, Stochastic Geometry, and Dynamical Systems. He leads the DFG-funded project Scaling of curvature measures and the modified Weyl-Berry conjecture and serves as Principal Investigator for project 12 ( Morphometric Roughness of Nanostructured Surfaces ) within the DFG Priority Programme 2265 (Random Geometric Systems). Winter's work explores the mathematical foundations of fractals, stochastic processes, and geometric measurements. Key themes include Minkowski content, curvature measures, self-similar sets, percolation models, and applications to materials science and geoscience. Recent publications emphasize fractal dimensionality, surface roughness quantification, and stochastic convergence in complex systems. He teaches advanced courses including Stochastic Geometry , Fractal Geometry , and Markov Chains , and mentors students through seminars and proseminars. No awards or research grants besides DFG projects are documented.

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Flavio SARTORETTOمشاهده پروفایل

دانشیار

Ca' Foscari University of VeniceItaly

Flavio SARTORETTO is an Associate Professor in Scientific Computing at Ca' Foscari University of Venice. He holds a Mathematics degree from the University of Padua and has held academic positions at University of Padua (1982-1992) and Sapienza University of Rome (1992-1993) before joining Ca' Foscari in 1993. His research focuses on numerical analysis, computational methods, and interdisciplinary applications including environmental modeling, cognitive processes, and assistive technologies. Key research areas include numerical solutions of PDEs, meshless methods, EEG signal analysis, and e-learning tools for impaired individuals. He has participated in major research projects such as EC Network (1992-1995), PRIN initiatives (1997-2010), and contributed to software development for geomechanical models and air quality systems. His work spans computational fluid dynamics, robotics applications, and cognitive studies. Recent publications highlight advancements in mesh refinement strategies, robotic assistive devices, and spatial cognition research. He has reviewed for prestigious journals and served in academic committees for state examinations and international conferences. He maintains active involvement in academic service, including roles in evaluation committees and contributions to professional societies like SIAM and CICAP.

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Florian Frankمشاهده پروفایل

مدرس ارشد

University of Erlangen–NurembergGermany

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 .

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Maciej Woźniakمشاهده پروفایل

استاد

AGH University of KrakowPoland

Maciej Woźniak serves as a university professor at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, actively contributing to research and teaching staff while participating in the Computer Science Discipline Council and College of the Faculty. His office is located at D-17, ul. Kawiory 21, III, 4.58, with primary contact via macwozni@agh.edu.pl. His research spans computational mathematics and high-performance computing, specializing in parallel algorithms for numerical simulations including isogeometric analysis, finite element methods, and multi-frontal solvers. Key applications address environmental challenges like hail suppression and urban smog reduction, alongside biomedical modeling of tumor growth and airborne pathogen dispersion. Methodological innovations focus on GPU acceleration, shared-memory architectures, and efficient integration techniques for partial differential equations. Analysis of his 2019-2024 publications reveals consistent advancement in parallel computational frameworks for environmental and biomedical applications, demonstrating interdisciplinary impact through experimental validation of hail cannons, smog reduction technologies, and pathogen dispersion modeling during the COVID-19 pandemic. His work bridges theoretical algorithm development with real-world problem solving across physics, engineering, and life sciences. Scientific Awards: No specific awards were documented in the provided sources. Student advising, research grants, laboratory affiliations, and educational background details beyond his PhD, DSc, and Eng. titles remain unspecified in the available materials, though his extensive publication record suggests active mentorship and collaborative research leadership.

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Piotr Szymczykمشاهده پروفایل

استاد

AGH University of KrakowPoland

Piotr Szymczyk is a Professor at the Department of Biocybernetics and Biomedical Engineering , AGH University of Science and Technology in Kraków. His research focuses on artificial intelligence , embedded systems , and real-time data processing , with applications in biomedical engineering, georadar analysis, and energy systems. Key research areas: Neural networks (Laplace/Z-transform), real-time systems , parallel computing , and georadar data classification Projects: NCN grants for 'Intelligent embedded systems' and 'Digital georadar data processing' His work spans embedded Linux , microcontroller programming (ARM, STM32), and wireless technologies (LoRa, Bluetooth LE). He has supervised doctoral and master's theses in these fields. Scientific awards: NCN Agreement No. 6693/B/T02/2011/40 Ministry of Science and Higher Education grant 0128/R/t00/2010/12

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Hadi Hajibeygiمشاهده پروفایل

استاد

Delft University of TechnologyNetherlands

Hadi Hajibeygi is a Professor of Geo-Energy Solid and Fluid Mechanics at Delft University of Technology, leading subsurface storage research and multiscale modeling initiatives. He serves as the Subsurface Storage Theme Lead (2016–present) and Energi Simulation Chair holder (2022–present), with a focus on underground hydrogen storage, CO2 sequestration, and geothermal energy systems. His research integrates multiphase flow in porous media , multiscale simulation , and geomechanical stability , supported by NWO-Vidi and Interpore awards. He leads the DARSim and ADMIRE projects, developing frameworks like Adaptive Dynamic Multiscale Integration and pEDFM-U for fractured reservoirs. Key awards include: Interpore Award for Porous Media Research (2021) NWO-Vidi Laureate (2019) Interpore Rosette (2017) ETH Zurich PhD Medal (2012) TU Delft Innovative Teaching Talent (2018) His teaching portfolio spans Dynamics of Solids and Fluids , Numerical Methods for Subsurface Simulation , and Multiscale Modeling , while advising a team of postdocs and PhD candidates on projects spanning induced seismicity, microbial interactions, and fractured reservoir mechanics.

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Jan Dirk Jansenمشاهده پروفایل

استاد

Delft University of TechnologyNetherlands

Prof. Jan Dirk Jansen (Delft University of Technology) specializes in systems and control theory applied to subsurface flow and geomechanics. His research spans induced seismicity , geothermal energy , reservoir simulation , and data assimilation . Current projects include co-leading the NWO-funded NEPTUNUS initiative on transient induced seismicity and previously researching seismicity mitigation in Dutch gas fields through the Science4Steer program. Expertise in numerical reservoir simulation History matching & model-order reduction Optimization of fluid injection/production He authored the textbook Nodal Analysis of Oil and Gas Production Systems , with significant contributions to closed-form geomechanical solutions and scalable numerical schemes . Contact: J.D.Jansen@tudelft.nl

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Miriam Schulteمشاهده پروفایل

استاد

University of StuttgartGermany

Miriam Schulte is a Professor at the Institute for Parallel and Distributed Systems (IPVS) at the University of Stuttgart . As Dean of Studies SimTech , she leads academic programs in simulation technology. Her research focuses on high-performance computing , multi-physics simulations , and scientific software development , with significant contributions to coupling libraries like preCICE and biophysical frameworks like OpenDiHu . Key Research Areas: High-Performance Computing (HPC) Multi-physics and Fluid-Structure Interaction (FSI) Sparse Grids and Hierarchical Numerical Methods Machine Learning in Simulation Software Parallel and GPU-Accelerated Algorithms Advising: Guided student projects on quantum neural networks , GPU-optimized sparse grids , and SYCL-based HPC frameworks . Coordinated SimTech Research Modules and IPVS/SGS team initiatives. Software Leadership: Maintains preCICE (coupling library for multi-physics) Develops OpenDiHu (neuromuscular simulations) Advances PLSSVM (parallel SVM library) and SG++ (sparse grids) Her recent publications (2022–2025) emphasize machine learning integration with multi-physics simulations , including groundwater heat pumps , brain tumor modeling , and neuromuscular EMG prediction . She actively promotes open-source software sustainability and collaborative research infrastructure at the University of Stuttgart.

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Magnus Bruasetمشاهده پروفایل

استاد

University of OsloNorway

Magnus Bruaset is a Professor and Director of the Software & AI Department at Simula Research Laboratory , with expertise in computational geosciences, numerical methods, and quantum computing. His work spans geological modeling, PDE solvers, and software development frameworks like Diffpack. Education : PhD in preconditioned iterative methods for elliptic problems (1992), Master's in preconditioning symmetric systems (1988). Research Interests : Focus on numerical analysis, GPU acceleration of geological simulations, stochastic modeling for uncertainty quantification, and quantum computing strategy. Key projects include Hamilton-Jacobi solvers, particle-based flow models, and contributions to digital contact tracing systems. Advising & Collaboration : Co-developed PhD training workshops for scientific communication and contributed to industrial-academic partnerships. Collaborated with institutions including ChevronTexaco, Wolfram Research, and University of Oslo.

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Anne C. Elsterمشاهده پروفایل

استاد

University of Texas at AustinUnited States

Anne C. Elster is a Professor and Director of the Heterogeneous and Parallel Computing Lab (HPC-Lab) at NTNU's Department of Computer Science, with additional roles as HPC Leader at the Center for Geophysical Forecasting and Senior Research Fellow at the Oden Institute. She holds board positions at NTNU and its Faculty of Information Technology. Her research spans: High-Performance Computing : GPU acceleration, auto-tuning, and heterogeneous systems Machine Learning : Applied to optimization and computational geosciences Parallel Algorithms : For scientific computing and real-time simulations Her recent publications (2021-2024) focus on GPU auto-tuning, quantum-HPC integration, distributed systems, and ML-driven geophysical data analysis, with strong emphasis on performance optimization across architectures. Awards and honors: IEEE Computer Society Distinguished Contributor (2021) IEEE Distinguished Speaker (2019-2022) IEEE Senior Member (2000) She has supervised 100+ master's students, 15+ PhDs, and secured major grants including EU H2020 projects. Current Post Docs focus on HPC acceleration and AI applications. Her HPC-Lab collaborates with CERN, Equinor, and international universities, specializing in GPU-accelerated scientific computing and tools for performance portability.

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