جست‌وجوی استاد و پژوهشگر

Carsten Mehringمشاهده پروفایل

دانشیار مدعو

• Fluid Dynamics
• Combustion Engineering
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Carsten Mehring is affiliated with the University of Stuttgart as part of the Institute team, holding a contact address at Böblinger Str. 72 in Stuttgart. His academic career includes roles such as Adjunct Associate Professor (2013–2018) at the University of California, Irvine, and Adjunct Professor (2005–2006) at the University of San Diego. He has extensive industry experience, including Engineering Manager positions at Parker Aerospace and UTC Aerospace Systems, focusing on combustion and CFD/thermal analysis. Education highlights include a Ph.D. in Mechanical and Aerospace Engineering from UC Irvine (1999), an M.Sc. in Mechanical Engineering from UC Irvine (1995), and a Dipl.-Ing. in Aerospace Engineering from Universität Stuttgart (1993). He also holds management certifications from MIT and UC San Diego. His research interests span fluid dynamics, combustion, multiphase flows, and thermal systems. Notable contributions include studies on liquid sheet instability, aerosol dispersion, and heat exchanger optimization. Recent publications (2020–2025) emphasize CFD modeling, aerosol dynamics, and advanced atomization techniques. Dr. Mehring has been recognized with eight US patents, the Artur Fischer Inventor Prize, and multiple industry awards. His work bridges academia and industry, with patents addressing inerting systems, fuel injectors, and microfluidic devices.

Tim Rickenمشاهده پروفایل

استاد

• Structural Mechanics
• Finite Element Methods
• Environmental Mechanics
• +۵ مورد دیگر

Prof. Tim Ricken serves as Dean of Studies for Aerospace Engineering and leads the Institute of Statics and Dynamics of Aerospace Structures at the University of Stuttgart. His research focuses on structural mechanics, finite element methods, environmental mechanics (particularly sea ice modeling), biomechanics, and AI-driven computational frameworks. He oversees state-of-the-art experimental labs for material fatigue analysis and collaborates with high-performance computing resources like Vulcan and Hawk clusters. Key research areas include multiphase modeling, porous media mechanics, and multiphysics simulations. His team addresses challenges in aerospace structures, biomedical engineering (e.g., liver and tumor modeling), and climate-related systems such as Antarctic sea ice dynamics. Current projects involve DFG-funded initiatives (e.g., SimLivA for liver injury modeling) and the Cluster of Excellence SimTech. Grants include SPP 1886, SPP 2311, and FOR 5151 (QuaLiPerF). Notable innovations include the FE2M multiscale framework, physics-informed neural networks (e.g., DeepONet), and the Onco* tumor modeling platform. He emphasizes model adaptation via equilibrated fluxes and stress-driven finite element methods. Experimental work spans laser therapy optimization, auxetic material analysis, and biomaterial testing in rolling suitcase labs.

Bernhard Weigandمشاهده پروفایل

استاد

• Heat Transfer
• Droplet Dynamics
• Supersonic Combustion
• +۳ مورد دیگر

Bernhard Weigand is a Professor and Director of the Institute of Aerospace Thermodynamics (ITLR) at the University of Stuttgart's Faculty of Aerospace Engineering and Geodesy. His work focuses on heat transfer, droplet dynamics, and supersonic combustion. He leads research initiatives such as the Collaborative Research Center (Transregio 75) on droplet dynamic processes under extreme conditions. Prof. Weigand has contributed to advancements in fluid mechanics, multiphase flow, and computational modeling, with particular expertise in droplet impact dynamics, microstructured surfaces, and data-driven turbulence models. His research also involves experimental and numerical investigations of aerothermal phenomena in turbine cooling systems and high-speed flows. He has published extensively in top journals and conferences, addressing topics like evaporation, phase change, and the application of machine learning in turbulence modeling. As director, he oversees the ITLR's facilities, including the Multiphase Flow Lab, and collaborates internationally on projects related to aerospace engineering and energy systems. His contributions have been recognized through leadership roles and impactful publications in the field.

Peter Münchمشاهده پروفایل

پژوهشگر

• High-performance computing
• Matrix-free computations
• Iterative solvers
• +۷ مورد دیگر

Peter Münch is a postdoctoral researcher at the Chair of Numerical Methods for Partial Differential Equations within the Institute of Mathematics at Technical University of Berlin (TU Berlin), Faculty II - Mathematics and Natural Sciences. He has held research positions at Uppsala University, University of Augsburg, Helmholtz-Zentrum Hereon, and Technical University of Munich. Dr. Münch's research focuses on high-performance scientific computing with expertise in matrix-free computations, dynamic sparse communication patterns, node-level optimization, iterative solvers including multigrid and block preconditioners, and efficient algorithms for high-dimensional partial differential equations. His work spans discontinuous Galerkin methods, computational fluid dynamics, and simulation of additive manufacturing processes including solid-state sintering and melt-pool modeling. He is one of the principal developers of the deal.II finite-element library, which won the SIAM/ACM Prize in Computational Science and Engineering in 2025. His recent publications demonstrate significant contributions to matrix-free finite element methods, multigrid solvers, and applications in computational fluid dynamics and materials science. The research shows a strong trend toward high-performance implementations of numerical methods for extreme-scale computing, with particular emphasis on matrix-free approaches that avoid explicit storage of large sparse matrices. SIAM/ACM Prize in Computational Science and Engineering 2025 (for deal.II) Dr. Münch has supervised numerous student projects including Master's theses, Bachelor's theses, and term papers on topics ranging from immersed boundary methods to high-order discontinuous Galerkin methods. His teaching activities include courses on Numerical Methods for ODEs, PDEs, and High-Performance Parallel Computing. He has contributed to multiple deal.II tutorial programs (steps 19, 68, 75, 76, 87) demonstrating advanced finite element techniques. As a principal developer of the deal.II finite element library, Dr. Münch is actively involved in the open-source scientific computing community, contributing to one of the most widely used finite element frameworks in computational science and engineering. His GitHub profile shows consistent contributions to deal.II and related projects, with significant activity in 2025.

• Multiphase Flows
• Combustion
• Droplet Vaporization
• +۶ مورد دیگر

Professor Eva Gutheil is a distinguished academic at the Interdisciplinary Center for Scientific Computing (IWR) at the University of Heidelberg, where she leads a prominent research group focused on multiphase flows and combustion processes. Her work spans technical combustion systems, atmospheric processes, and biofluid mechanical applications, making significant contributions to both fundamental understanding and practical engineering solutions. Her research interests encompass multiphase flows , combustion processes , droplet vaporization , laminar spray flames , PDF methods , and flamelet modeling . Professor Gutheil's work addresses critical challenges in energy production efficiency, stability, safety, and pollutant emissions across various technical combustion systems including internal engine combustion, industrial furnaces, and gas turbine combustion. Her research extends to atmospheric processes like ozone depletion and biofluid mechanical applications such as particle dispersion in human airways and blood flow in cerebral aneurysms. Analysis of her recent publications reveals a strong focus on computational modeling of complex flow phenomena, with increasing attention to bioreactor hydrodynamics, atmospheric chemistry applications, and advanced nanoparticle synthesis techniques. Her work demonstrates a consistent trajectory toward more sophisticated modeling approaches that integrate multiple physical phenomena across different scales. Professor Gutheil has mentored numerous PhD students and research assistants, as evidenced by the extensive list of current and former group members. Her research group includes specialists in computational fluid dynamics, combustion modeling, and atmospheric chemistry applications. The research group operates within the Interdisciplinary Center for Scientific Computing at the University of Heidelberg, utilizing advanced computational resources for modeling and simulation of complex flow phenomena. Their work bridges fundamental fluid dynamics with practical applications across energy systems, environmental science, and biomedical engineering.

• Atmospheric Chemistry
• Aerosol Science
• Climate Change
• +۳ مورد دیگر

Uwe Kuhn is a Researcher at the Multiphase Chemistry Department of the Max Planck Institute for Chemistry since 2016. His career spans postdoctoral and senior scientist roles in Germany, Switzerland, and Brazil, focusing on atmospheric trace gases and aerosols. Education: Ph.D. and Diploma in Biology from Johannes Gutenberg-University Mainz. Research Interests: Uwe investigates the sources, transformations, and sinks of climatically relevant trace gases, emphasizing their role in aerosol formation, tropospheric oxidant cycles, and greenhouse gas dynamics. His work integrates chemical, physical, and biological methods to understand atmospheric multiphase processes across molecular to tropospheric scales. Recent Projects: He leads field campaigns such as Meteor Cruise 203 (Pacific-Ocean/Atmosphere trace gas exchange), Eugen Seibold (Research Yacht studies), and ATTO (Amazon Tall Tower Observatory: Aerosol Nucleation Project). Past projects include McFAN (Multiphase chemistry in Chinese fog), CARIBIC (aircraft-based atmospheric studies), and PEGASOS (European gas-aerosol-climate interactions). Scientific Awards: Senior Scientist Fellow, EU Marie Curie Program (2008–2010) Labs & Collaborations: Uwe contributes to the Multiphase Chemistry Department at the Max Planck Institute for Chemistry, collaborating with global institutions on atmospheric research.

Sascha Heitkamمشاهده پروفایل

پژوهشگر ارشد

• Multiphase Flow
• Foam Physics
• Fluid Dynamics
• +۳ مورد دیگر

Dr. Sascha Heitkam serves as Group Leader of Multiphase Flow at Dresden University of Technology's Institute of Process and Environmental Engineering, directing the Emmy-Noether Junior Research Group 'Towards Fluid Dynamics of Foam and Froth Flow' since 2020. His academic foundation includes: Diploma in Mechanical Engineering, Energy Technology (TU Dresden, 2009) PhD in Fluid Mechanics (TU Dresden, 2014) with thesis on 'Manipulation of liquid metal foam with electromagnetic fields: a numerical study' Heitkam's research pioneers foam and froth dynamics through numerical modeling and experimental techniques. His work spans liquid metal foam manipulation under electromagnetic fields, convective instability in liquid foams, and industrial applications like fine particle flotation and enzyme separation via bubble adsorption. Current methodologies integrate ultrasonic sensing for real-time foam characterization in mineral processing. Awarded the prestigious Emmy-Noether Fellowship by the German Research Foundation, his funded projects demonstrate significant scientific impact: Numerical simulation of metal foam formation under magnetic fields (DFG, 2010-2014) Convective instability in liquid foams (2015-2018) EU H2020 FineFuture project on fine particle flotation (2019-2022) Ultrasonic sensors for ore flotation foams (2020-2023) Emmy-Noether project 'Towards Fluid Dynamics of Foam and Froth' (2020-2026) He leads experimental efforts in foam physics while teaching specialized courses on bubble phenomena, advancing both fundamental understanding and industrial process optimization in metallurgical and environmental engineering contexts.

• 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 .

Nadja Rayمشاهده پروفایل

استاد

• Multiscale modeling
• Upscaling
• Homogenization
• +۵ مورد دیگر

Nadja Ray is a Professor for Geomatics and Geomathematics at the School of Mathematics, Information, Data Science (MIDS) at Katholische Universität Eichstätt-Ingolstadt since September 2022. She also serves as Head of a Junior Research Group at Friedrich-Alexander Universität Erlangen-Nürnberg and is Principal Investigator for multiple research projects including DFG SPP 2089, DAAD PPP Finland, and DFG RTG 2339. Her educational background includes a Habilitation in Applied Mathematics (2016-2020), a PhD in Applied Mathematics (2008-2013), and a Diploma in Mathematics with minor in theoretical physics (2002-2008), all from Friedrich-Alexander Universität Erlangen-Nürnberg. Dr. Ray's research focuses on multiscale modeling, upscaling, and homogenization with applications in porous media, particularly soil microaggregates and electrohydrodynamics. Her work bridges mathematical theory with practical applications in soil science, environmental engineering, and geosciences. She develops mechanistic models that incorporate evolving microstructures to understand complex phenomena in porous media. Her recent publications demonstrate a strong focus on micro-macro modeling approaches for reactive transport in porous media, permeability estimation using machine learning techniques, and pore-scale modeling of soil processes. Her work spans mathematical analysis, numerical methods, and interdisciplinary applications in soil science and geosciences. Habilitation prize from Friedrich-Alexander Universität Erlangen-Nürnberg for outstanding habilitation Women's prize from the faculty of natural sciences at Friedrich-Alexander Universität Erlangen-Nürnberg Dr.-Körper-Preis 2014 from GAMM for outstanding PhD thesis Multiple prestigious scholarships including from Studienstiftung des Deutschen Volkes and Deutsche Telekom Stiftung Dr. Ray has secured significant research funding as Principal Investigator for multiple DFG and DAAD projects. She regularly presents her research at international conferences including the SIAM Conference on Mathematical and Computational Issues in the Geosciences and the European Geosciences Union General Assembly. She teaches in the B.Sc. Data Science program at KU Eichstätt-Ingolstadt and has completed the Certificate for Teaching in Higher Education of the Bavarian Universities. Her international collaborations include research visits to institutions in Belgium, Slovakia, Norway, and the Netherlands, demonstrating her strong international research network.

• Computational Engineering
• Model-Based Development
• Production Engineering
• +۳ مورد دیگر

Julia Kowalski serves as Professor and Chair of the Department of Methods of Model-Based Development in Computational Engineering at RWTH Aachen University's Faculty of Mechanical Engineering. She holds dual appointments on the Steering Committees for the university's Profile Areas in Production Engineering (ProdE) and Modeling & Simulation Sciences, operating from the Collective Building of Mechanical Engineering in Aachen, Germany. Her research integrates computational engineering with geohazard prediction and cryorobotics, developing advanced numerical methods for multiphysics problems including ice-penetration probes, landslide susceptibility mapping, and wind-energy systems. She pioneers machine learning applications that bridge physical models with engineering design while championing FAIR data principles across cryosphere and geohazard research domains. Current projects focus on model coupling techniques for environmental flows and space exploration technologies. Analysis of her 15 most recent publications reveals dominant trends in surrogate modeling for geotechnical stability, cryorobotic exploration systems, and FAIR data frameworks for environmental science. Her work consistently bridges machine learning with physical modeling across renewable energy, planetary science, and natural hazard mitigation through international collaborations like the TRIPLE project. Scientific awards are not documented in provided materials, though her leadership in DLR-funded space exploration initiatives and editorial roles in topical collections indicates significant recognition. As department chair, she oversees graduate advising and research direction within her computational engineering group, with active grant funding evidenced by German Space Agency collaborations and multi-institutional projects targeting geohazard prediction and cryosphere exploration. Her work demonstrates strong industry-academia-government partnerships. Kowalski leads the Methods of Model-Based Development research group, which operates as an integrated lab for numerical simulation, model coupling, and data-driven engineering solutions. Future work focuses on enhancing uncertainty quantification in geohazard models, advancing cryorobotic technologies for extraterrestrial environments, and developing robust frameworks for FAIR geoscientific data.

• Computational Mechanics
• Material Science
• Biomechanics
• +۵ مورد دیگر

Prof. Bernd Markert serves as Professor and Head of the Institute of General Mechanics at RWTH Aachen University's Faculty of Mechanical Engineering. He concurrently holds critical university-wide roles including Rector's Representative for Alumni and Rectorate Mandate for Mexico Cooperation, based in Aachen's Faculty of Mechanical Engineering building. His research spans computational mechanics with emphasis on phase-field modeling, molecular dynamics, and machine learning integration. Key focus areas include biodegradable magnesium alloys for biomedical implants, multiscale composite material behavior, and AI-enhanced structural failure prediction. Recent work bridges physics-based simulations with neural networks for constitutive modeling and corrosion prediction. Analysis of his 2022-2025 publications reveals accelerating convergence of mechanics and artificial intelligence, particularly in physics-informed neural networks for crystal plasticity and phase-field frameworks. His team demonstrates consistent innovation in modeling porous media, network materials, and biomechanical systems while maintaining strong industry-relevant applications in additive manufacturing and biomedical engineering. As Institute Head, Markert leads the Chair and Institute of General Mechanics (IAM), directing research on fundamental mechanics principles applied to advanced materials and structural systems through computational and experimental methodologies.

• Mathematical Analysis
• Numerical Analysis
• Computational Fluid Dynamics
• +۱ مورد دیگر

Jun Liu is a Researcher in the Department of Mathematics at Technische Universität Darmstadt's Faculty of Mathematics, Computer Science, and Data Science. Based in the Mathematical Methods in Mechanics (MMA) group at Peter-Grünberg-Straße 10, Darmstadt, Germany, Liu focuses on advanced numerical methods for fluid dynamics problems. Research centers on mathematical analysis and computational techniques for fluid flow simulation, particularly addressing challenges in momentum conservation with variable density ratios. Key expertise includes: Development of unstructured finite volume methods Numerical stability for multiphase flows Density-driven flow modeling Recent work demonstrates specialized focus on simulation solutions for strongly varying density ratios in computational fluid dynamics. Liu maintains active research output with publications in high-precision numerical methods. Contact: liu@mma.tu-darmstadt.de | Work: +49 6151 16-21464

• Chemical Engineering
• Process Intensification
• Biotechnology
• +۳ مورد دیگر

Prof. Dr.-Ing. Andreas Jupke is a University Professor at the Department of Fluid Process Engineering of the School of Mechanical Engineering , RWTH Aachen University, since September 2014. His research focuses on purification strategies for biotechnological processes and innovative approaches for intensifying extraction processes . He leads a team conducting interdisciplinary research in chemical engineering, biotechnology, and sustainable process design. Education: Studied Chemical Engineering at TU Dortmund (1988–1994) Diploma in Chemical Engineering (1994) Doctorate (Dr.-Ing.) in preparative chromatography at TU Dortmund (2003) His work spans liquid-liquid extraction , reactive extraction , electrochemical separations , and process modeling with applications in biofuels, bioproducts, and sustainable chemical synthesis. Recent publications emphasize solvent design , digital twins for extraction columns , and integration of microbial/enzymatic/organometallic catalysis . Scientific Trends: His research integrates thermodynamic modeling , computational fluid dynamics , and data-driven hybrid approaches to optimize extraction processes, crystallization, and biorefinery systems. Publications frequently address pH-shift separations , microbial product recovery , and process intensification via multiphase reactors . Students & Collaborations: While direct advisees are not explicitly listed, his work involves collaborations with researchers at TU Dortmund, Bayer Technology Services, and interdisciplinary teams in projects like MIX-UP and Carbon2Chem.

Tobias Kasper Skovborg Ritschelمشاهده پروفایل

استادیار

• Control theory
• Model predictive control
• Stochastic adaptive control
• +۹ مورد دیگر

Tobias Kasper Skovborg Ritschel serves as Assistant Professor (Tenure Track) in the Department of Applied Mathematics and Computer Science (DTU Compute) at the Technical University of Denmark. His research bridges theoretical advances in control systems with practical implementation across energy systems, bioreactors, epidemiology, and medical applications. Ritschel directs a productive research program focusing on computational methods for complex dynamical systems with rigorous thermodynamic foundations. His educational background demonstrates deep technical training: PhD in Applied Mathematics (2015-2018), Technical University of Denmark MSc in Mathematical Modeling and Computation (2013-2015), Technical University of Denmark BSc in Mathematics and Technology (2010-2013), Technical University of Denmark Ritschel's research expertise spans multiple domains of control theory and mathematical modeling. His core competencies include stochastic adaptive control, model predictive control, and optimal control frameworks applied to nonlinear dynamical systems. He specializes in numerical methods for differential equations (stochastic, partial, delay, and differential-algebraic) with computational implementations in MATLAB, C/C++, and Python. His application areas demonstrate remarkable breadth: from oil reservoir management and nuclear power systems to bioreactor operations, epidemiological modeling, and diabetes management technologies. Analysis of his publication trajectory reveals a strategic evolution from foundational work on thermodynamically rigorous reservoir simulation toward increasingly diverse applications. Early publications (2017-2019) focused on oil and gas applications with rigorous phase equilibrium modeling, while recent work (2020-2024) addresses pressing societal challenges including pandemic response strategies, power grid flexibility for renewable integration, and biomedical control systems. This demonstrates his ability to transfer core methodological expertise across disparate application domains while maintaining mathematical rigor. Dr. Ritschel actively supervises numerous students across all academic levels, with recent BSc projects focusing on molten salt reactors and demand-side flexibility in power systems. His teaching portfolio includes advanced graduate courses in stochastic adaptive control, dynamical systems, and time series analysis. He maintains strong industry connections through EU-funded projects including COCOP (Horizon 2020) and OPTION (Innovation Fund Denmark).

Thorsten Zirwesمشاهده پروفایل

استادیار

• Combustion Engineering
• Reactive Flows
• Hydrogen Combustion
• +۵ مورد دیگر

Dr. Thorsten Zirwes serves as Deputy Head of Institute at the Institute for Reactive Currents (IRST) at the University of Stuttgart, where he leads research in combustion engineering and reactive flows. With a strong background in chemical engineering from Karlsruhe Institute of Technology (KIT), where he completed his B.Sc., M.Sc., and PhD, Dr. Zirwes has established himself as a leading researcher in computational combustion. Deputy Head of Institute, Institute for Reactive Currents, University of Stuttgart (2023-present) DAAD PRIME Fellow & Visiting Postdoctoral Scholar, Stanford University (2022) PhD in Chemical Engineering and Process Engineering, Karlsruhe Institute of Technology (2016-2021) Dr. Zirwes' research focuses on advancing computational methods for understanding and modeling complex combustion processes, with particular emphasis on carbon-free fuels like hydrogen and ammonia. His work spans fundamental flame dynamics, turbulent combustion, and the development of efficient numerical algorithms for high-performance computing environments. He has made significant contributions to the understanding of thermodiffusion effects, flame instabilities, and porous media combustion for clean energy applications. His extensive publication record shows a clear trend toward sustainable energy solutions, with increasing focus on hydrogen and ammonia combustion as carbon-free alternatives. The research spans fundamental fluid dynamics, practical combustion applications, and computational method development, demonstrating both theoretical depth and practical relevance to energy transition challenges. Jürgen Warnatz Prize (German Section Combustion Institute, 2023) Distinguished Paper Award from the Combustion Institute (2023) Bernard-Lewis Fellowship of the Combustion Institute (2022) Most downloaded author of the Springer Journal FTaC (2022) Doctorate at KIT with summa cum laude (2021) Dr. Zirwes actively supervises research projects and collaborates with both academic and industrial partners. His group develops and maintains the EBI-DNS solver, an OpenFOAM extension for direct numerical simulation of combustion processes. Current research emphasizes carbon-free combustion technologies crucial for achieving climate goals, with strong connections to industry partners working on sustainable energy solutions. His research group maintains strong connections with international institutions, including Stanford University, and participates in major collaborative projects focused on advancing clean combustion technologies. The team combines expertise in fluid dynamics, numerical methods, and high-performance computing to tackle challenging problems in sustainable energy.