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Hendrik RanochaView profile

Professor

• Numerical Analysis
• Computational Mathematics
• Partial Differential Equations
• +6 more

Hendrik Ranocha is a Professor in Numerical Mathematics at Johannes Gutenberg University Mainz, Germany. His research focuses on the analysis and development of numerical methods for partial and ordinary differential equations, with particular emphasis on stability and structure-preserving techniques that transfer results from continuous to discrete levels. His educational background includes: PhD in Mathematics from TU Braunschweig (2016-2018), advised by Thomas Sonar MSc in Mathematics from TU Braunschweig (2014-2016) BSc in Mathematics from TU Braunschweig (2011-2014) Exchange student at Yonsei University, Seoul (2013) BSc in Physics from TU Braunschweig (2010-2013) Hendrik Ranocha's research spans Numerical Analysis and Scientific Computing . His work focuses on developing numerical schemes for hyperbolic balance laws and dispersive-dissipative equations, including Discontinuous Galerkin methods, spectral element methods, finite difference schemes, and flux reconstruction. He specializes in structure-preserving methods that conserve entropy/energy, utilizing summation by parts operators and mimetic properties. His research also encompasses Runge-Kutta methods, stability of time integration schemes, adaptivity in time and space, data-driven approaches, and uncertainty quantification. His recent publications demonstrate a strong focus on entropy-stable numerical methods, structure-preserving discretizations, and high-performance computing implementations in Julia. The research trends show increasing emphasis on practical software implementations (Trixi.jl, SummationByPartsOperators.jl), applications to physical systems like compressible Euler equations and shallow water equations, and addressing fundamental numerical challenges in stability and convergence. Hendrik Ranocha leads a research group at Johannes Gutenberg University Mainz with several PhD students and postdocs, including Louis Petri, Marco Artiano, Sebastian Bleecke, Saurav Samantaray, Arpit Babbar, and Valentin Churavy. He collaborates extensively with researchers such as Gregor Gassner, Andrew R. Winters, Michael Schlottke-Lakemper, and Jesse Chan on numerical methods and software development. He is actively involved in open-source scientific computing, contributing to projects like Trixi.jl (a Julia package for adaptive high-order numerical simulations of conservation laws), SummationByPartsOperators.jl, OrdinaryDiffEq.jl, NodePy, and RK-Opt. He is part of the SciML organization, which develops high-performance Julia libraries for scientific machine learning and computational science.

Michael PlexousakisView profile

Assistant Professor

• Numerical Analysis
• Partial Differential Equations
• Finite Element Methods
• +3 more

Michael Plexousakis is an Assistant Professor in the Department of Mathematics & Applied Mathematics at the University of Crete. He received his PhD from the University of Tennessee, Knoxville and joined the University of Crete in 2010. He maintains research affiliations with the Institute of Applied and Computational Mathematics at the Foundation for Research and Technology, Hellas (FO.R.T.H.) and the Archimedes Center for Modeling, Analysis and Computations (ACMAC). His research focuses on: Numerical solution of partial differential equations with finite element and finite volume methods A posteriori error estimation and adaptivity Singular solutions of evolution equations Scientific computing and visualization Dr. Plexousakis has secured significant research funding including the SYNERGASIA program (2011-2013) studying extreme weather phenomena, the THALIS program (2012-2014) on optimal management of economic and environmental systems, and research on seismic protection of existing buildings. His teaching portfolio spans computational mathematics with courses including: Computer Programming II Design and Analysis of Algorithms Numerical Algorithms Numerical Analysis Numerical Solution of PDEs Mathematical Biology He has co-authored two textbooks: "Numerical Analysis" (2023) for postgraduate studies and "Numerical Solution of Partial Differential Equations" (2015) for undergraduate students, both published through Kallipos, Open Academic Editions. Dr. Plexousakis's publication record demonstrates expertise across multiple domains of computational mathematics, with particular emphasis on numerical methods for Helmholtz equations, Schrödinger equations, and parabolic equations. His work bridges theoretical numerical analysis with practical applications in atmospheric science, quantum mechanics, and materials science, showing consistent contributions to high-impact journals in applied mathematics.

• Computational Fluid Dynamics (CFD)
• Fluid Dynamics
• Turbomachinery
• +5 more

Giovanni Caramia is an Assistant Professor in the Department of Mechanics, Mathematics & Management at Polytechnic University of Bari (Poliba), specializing in fluid dynamics and computational modeling. His work bridges theoretical and applied engineering, focusing on advanced CFD techniques, renewable energy systems, and turbomachinery optimization. Academic Rank: Assistant Professor (ING-IND/08 - Fluid Machinery) Email: giovanni.caramia@poliba.it Research Interests Caramia's research spans computational fluid dynamics, energy transition strategies, and mechanical system optimization. Key areas include: Hydrogen combustion and fuel systems Cavitation and multiphase flow modeling OpenFOAM® software implementation Wind turbine and offshore energy systems Carbon neutrality pathways for Southern Italy Recent Publications Trends His 2023-2025 work emphasizes energy transition (green hydrogen, biomass), advanced CFD simulations (cavitation, floating wind turbines), and numerical method development. Articles highlight practical applications in renewable energy systems and industrial fluid machinery. Labs & Teams Current affiliations include Poliba's research groups focused on fluid machinery and energy systems, though specific lab names are not detailed in available texts.

• Scientific Computing
• Numerical Analysis of PDEs
• High-Performance Computing
• +7 more

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 .

• Applied Mathematics
• Theoretical Mechanics
• Computational Mechanics
• +7 more

Dr. Luis Espath is an Assistant Professor of Applied Mathematics at the University of Nottingham, affiliated with the School of Mathematical Sciences. His research spans theoretical and computational mechanics, uncertainty quantification, and machine learning. He has held postdoctoral and research scientist roles at KAUST and RWTH Aachen, respectively, and authored the Springer Nature book Mechanics & Geometry of Enriched Continua . Education : Engineering Diploma (2007) at PUCRS, Brazil; Master’s and Ph.D. (2013) at UFRGS, Brazil; Habilitation in Mathematics (2021) at RWTH Aachen, Germany. Dr. Espath’s research focuses on the application of phase-field and continuum mechanics to model complex systems, with an emphasis on thermodynamic consistency and computational efficiency. He integrates stochastic optimization and machine learning into fluid dynamics and structural modeling. His recent publications highlight expertise in phase-field gradient theory, fluid-structure interaction, and Bayesian experimental design. The 2021 articles reflect his work on Navier-Stokes equations, reactive Cahn-Hilliard systems, and divergence-free fluid flow approximations.

• Mechanical Engineering
• Solid Mechanics
• Finite Element Methods
• +4 more

Prof. Recep Gümrük is a full-time Professor at Karadeniz Technical University's Faculty of Engineering, Department of Mechanical Engineering, where he has held academic positions since 2013. He advanced from Assistant Professor (2013-2017) to Associate Professor (2017-2022) before attaining his current professorship in 2022. Since 2014, he has concurrently served as Deputy Head of the Department. Education: Doctorate in Mechanical Engineering, Karadeniz Technical University (2006-2012) Postgraduate studies in Mechanical Engineering, Karadeniz Technical University (2001-2006) Undergraduate degree in Mechanical Engineering, Karadeniz Technical University (1997-2001) Research Focus: His expertise spans solid mechanics, composite materials, additive manufacturing, and computational methods. Primary research domains include: Advanced 3D printing of thermoplastic composites (PEEK, ABS blends) Mechanical behavior of micro-lattice structures and pressurized tubes Fatigue analysis and optimization of polymer blends Finite element modeling of energy-absorbing structures Project Leadership: Directs multiple funded initiatives including: TUBITAK projects on continuous fiber-reinforced thermoplastic composites (2021-2023) University-supported research on biomedical materials via selective laser melting (2020-2023) Development of 3D printing extruders for composite fabrication (2018-2021) Advising & Innovation: Supervises postgraduate theses on additive manufacturing and mechanical testing. Holds patents for: Continuous fiber composite 3D printing extruders (2021) Impact-absorbing pressure vessels (2021)

Markus RenoldnerView profile

Research Fellow

• Numerical Analysis
• Partial Differential Equations
• Finite Element Methods
• +3 more

Markus Renoldner is a Doctoral Assistant at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences, Institute of Mathematics, specifically within the Chair of Numerical Modelling and Simulation (MNS) and the Picasso Group. His office is located at MA C2 622 in Building MA, Station 8, 1015 Lausanne. His educational background includes Doctoral studies in Mathematics at EPFL (2023-present), MSc in Computational Science and Engineering at TU Wien (2021-2023), Master's Thesis in Applied Mathematics at ETH Zürich (2022-2023), and an Exchange semester in Applied and Computational Mathematics at KTH Stockholm (2022). Renoldner specializes in numerical analysis of partial differential equations (PDEs) , with current research focusing on Finite Element approximation of solutions to PDEs in fusion plasma physics. His work spans PDE theory and control systems engineering, as evidenced by his GitHub repositories containing numerical implementations for Navier-Stokes equations and shallow water models. His publications demonstrate expertise in developing mass, energy, and helicity conserving discretization methods for fluid dynamics problems. His professional experience includes simulation engineering at Team Tumbleweed (2021-2024), a visiting associate position at Boston Consulting Group (2021), systems engineering at RUAG Space (2020), and data analysis at KPMG (2017). He has also held leadership roles including CEO for one month at Adecco Group (2020) and Vorstand/Consultant at icons - consulting by students (2017-2020).

• Quantum Field Theory
• Condensed Matter Physics
• Theoretical Physics
• +3 more

Marton Lajer is a postdoctoral research associate in the Condensed Matter Theory group at Brookhaven National Laboratory's Condensed Matter Physics and Materials Science Department since 2022. He previously worked as an independent contractor at Brookhaven (2021-2022) and held junior research fellowships at Hungary's Wigner Research Centre for Physics (2016-2020, part-time). His expertise spans quantum field theory, nonperturbative methods, and computational physics. Education: PhD (2020) and MSc (2016) in Physics from Eötvös Loránd University, supervised by Zoltan Bajnok Research Focus: Hamiltonian truncation techniques, finite-volume physics, and quantum many-body systems His work bridges theoretical physics and materials science through advanced computational methods in Wolfram Language, C++, and Python. His research has implications for understanding strongly interacting systems and quantum computer applications in field theory. Scientific Contributions Developed finite volume methods for sinh-Gordon and other integrable QFTs Extended Hamiltonian truncation to higher dimensions Investigated quantum computer implementations of field theory methods

Hadi HajibeygiView profile

Professor

• Multiphase Flow in Porous Media
• Multiscale Modeling and Simulation
• Subsurface Hydrogen Storage
• +8 more

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.

Jan Dirk JansenView profile

Professor

• Reservoir Engineering
• Geomechanics
• Induced Seismicity
• +4 more

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

Denis VoskovView profile

Associate Professor

• Reservoir Simulation
• CO2 Sequestration
• Geothermal Energy
• +4 more

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.

• Dynamical Systems
• Geometric Group Theory
• Rational Billiards
• +5 more

Alex Eskin is the Arthur Holly Compton Distinguished Service Professor in the Department of Mathematics at the University of Chicago. He has been a faculty member at the University of Chicago since 1999 and is a leading researcher in dynamical systems, geometric group theory, and the theory of moduli spaces. His educational background includes: Undergraduate studies at UCLA PhD from Princeton University (1993) under Peter Sarnak Eskin's research focuses on rational billiards, geometric group theory, and the dynamics of the SL(2,R) action on moduli spaces of translation surfaces. His work bridges several areas of mathematics including ergodic theory, geometry, and number theory. He is particularly known for his breakthrough results on the classification of invariant and stationary measures for the SL(2,R) action on moduli spaces, which led to his Breakthrough Prize in 2020. Eskin's recent publications demonstrate a continued focus on measure rigidity, Lyapunov exponents, and the geometry of moduli spaces. His work often involves deep collaborations with other leading mathematicians such as Maryam Mirzakhani (until her passing), Amir Mohammadi, and others. The research spans from foundational theoretical work to applications in counting problems and effective estimates. His major scientific achievements include: Clay Research Award (2007) for work on quasi-isometric rigidity of solvable groups Fellow of the American Mathematical Society (2012) Election to the National Academy of Sciences (2015) Breakthrough Prize in Mathematics (2020) for classification of P-invariant and stationary measures for the moduli of translation surfaces Eskin has advised several PhD students including Moon Duchin and Simion Filip. His research has been supported by major grants from the National Science Foundation and the Simons Foundation. He has been an influential figure in the field, giving invited talks at the International Congress of Mathematicians in 1998 and 2010. His work has opened new directions in the study of dynamics on moduli spaces and has deep connections to other areas of mathematics. While not explicitly mentioned in the provided texts, Eskin is likely involved in research groups or seminars at the University of Chicago related to geometry, topology, and dynamical systems. His extensive collaboration network suggests active participation in the broader mathematical community through workshops, conferences, and collaborative research projects.

Jean-Baptiste ColliatView profile

Professor

• Numerical Simulation of Materials and Structures
• Civil Engineering
• Mechanical Behavior of Heterogeneous Materials
• +7 more

Jean-Baptiste Colliat is a Full Professor at Polytech Lille , Lille University, specialized in Numerical Simulation of Materials and Structures within Civil Engineering. His work bridges computational mechanics with practical applications in concrete durability, geothermal systems, and biomedical simulations. Develops Enriched Finite Element Methods for heterogeneous materials Focuses on Uncertainty Quantification in multi-scale systems Key applications: Nuclear Waste Containment , Rockfill Stability , and Obstetric Biomechanics Recent research trends include 3D fracture network modeling, stress-permeability coupling in porous media, and stochastic analysis of material heterogeneity. His work integrates X-ray Micro-CT , DEM , and Multiscale Homogenization techniques. Professor Colliat leads computational frameworks for Embedded Finite Element Methods and Excursion Set Theory applications. He actively collaborates with LaMcube (Laboratoire de Mécanique Multi-physique Multiéchelle) on problems ranging from microstructural evolution to large-scale infrastructure failure.

Kenneth Aksel Hvistendahl KarlsenView profile

Professor

• Nonlinear Partial Differential Equations
• Stochastic Partial Differential Equations
• Numerical Analysis
• +3 more

Kenneth Aksel Hvistendahl Karlsen is a Professor in the Department of Mathematics at the University of Oslo. His research focuses on nonlinear partial differential equations (PDEs) and stochastic PDEs , with applications to porous media flow (oil recovery), sedimentation processes, traffic flow, water waves, finance, and biomedical modeling. Key research questions: Solution existence/uniqueness, stability, numerical computation Editorial roles: SIAM Journal on Mathematical Analysis (2021–), SIAM Journal on Numerical Analysis (2007–) Research trends from recent publications show emphasis on stochastic conservation laws on manifolds, nonlocal traffic flow models, dynamic capillarity equations with noise, and well-posedness analysis of peakon systems. His work bridges theoretical PDE analysis with numerical methods for real-world applications. Computational projects include the NASTRAN initiative (Numerical Analysis of Stochastic Transport), with extensive contributions to finite difference/volume schemes for degenerate equations.

Fan ZhangView profile

Research Fellow

• Solar Physics
• Computational Fluid Dynamics
• Magnetohydrodynamics
• +3 more

Fan Zhang is a Postdoctoral Fellow at the Rosseland Center for Solar Physics, University of Oslo, specializing in computational fluid dynamics and solar plasma modeling. His research bridges high-order numerical methods with astrophysical applications, particularly in magnetohydrodynamics (MHD) for solar corona and wave propagation studies. University of Oslo Rosseland Center for Solar Physics Research Interests Zhang's work focuses on advancing numerical techniques for shock-capturing and MHD simulations, enabling precise modeling of solar phenomena like coronal mass ejections (CMEs), Alfvén waves, and plasma dynamics. He develops finite-volume and compact nonlinear schemes tailored for unstructured grids, addressing challenges in numerical stability and accuracy. Recent Publications His 15 most recent articles (2025–2021) highlight innovations in time-accurate MHD models (e.g., SIP-IFVM, COCONUT), mesh topology effects on solar simulations, and algorithms for overshooting oscillation suppression. Key themes include computational efficiency, high-order numerical schemes, and two-fluid modeling of solar plasmas. Collaborative Work Zhang frequently collaborates with international researchers on projects like COCONUT, which optimizes preprocessing of magnetic maps for space-weather forecasting and solar cycle modeling. His contributions span algorithm design, model validation, and cross-disciplinary computational frameworks.