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Marcus Herrmann is a Professor of Aerospace and Mechanical Engineering at Arizona State University's School for Engineering of Matter, Transport and Energy. He is also affiliated with the Center for Negative Carbon Emissions. His research focuses on fluid mechanics, multiphase flows, atomization processes, and numerical methods for discontinuous interfaces. Herrmann holds a PhD in Mechanical Engineering from RWTH Aachen University (2001) and a Diplom (1995). His career includes a postdoctoral fellowship at Stanford University's Center for Turbulence Research (CTR) and a visiting scientist position at the University of Technology Eindhoven, Netherlands. He has secured major grants from NASA, NSF, and industry partners like Honeywell, focusing on atomization modeling, supersonic crossflows, and turbulence simulations. Research interests span computational fluid dynamics, multiphase flow simulation, and LES/DNS methodologies. His recent work emphasizes high-fidelity numerical techniques for particle-resolved simulations and phase interface dynamics. Teaching includes courses like MAE 561 (Computational Fluid Dynamics) and MAE 384 (Advanced Math Methods for Engineers). He actively advises students through research and dissertation roles. Notable projects include modeling wax deposition in pipelines and developing novel approaches for interface dynamics in turbulent flows. His work bridges fundamental fluid mechanics with industrial applications like combustion systems and porous media modeling.

• Fluid Mechanics
• Multiphase Flow Modeling
• Numerical Simulation
• +3 more

Ali Mani is an Associate Professor of Mechanical Engineering at Stanford University and a faculty affiliate at the Institute for Computational and Mathematical Engineering. He earned his PhD in Mechanical Engineering from Stanford in 2009, following an M.S. (2004) and B.S. (2002) from Stanford and Sharif University of Technology, respectively. His research focuses on fluid mechanics, turbulence, and numerical simulations, with applications in multiphase flows, electrokinetic systems, and applied mathematics. His group develops high-fidelity simulation tools and reduced-order models to understand transport processes in turbulent and chaotic systems. Research interests include turbulence modeling, two-phase flow dynamics, and electrochemical transport. Recent work explores eddy viscosity operators, nonlocal transport phenomena, and computational methods for multiphase systems. The group's studies often bridge experimental validation and numerical analysis to improve predictive engineering models. Key contributions span electrokinetic transport in porous media, superhydrophobic surface slip effects, and phase field modeling. His lab’s work is supported by grants focusing on fluid dynamics, renewable energy systems, and advanced simulation frameworks.

• Fluid Mechanics
• Turbulence Modeling
• Numerical Simulations
• +3 more

Professor Manolis Gavaises is a leading academic in the field of mechanical engineering and computational fluid dynamics at City St George's, University of London, where he holds the position of Professor in the School of Engineering and Mathematical Sciences. He earned his PhD from Imperial College London and has been a faculty member since 2001, progressing to full Professor in 2009. His research is centered on advanced modeling of multi-phase flows, cavitation, and fuel injection systems, with extensive collaborations across Europe and industry partners such as Delphi, Caterpillar, and BP. Education: DIC, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 PhD, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 Diploma (5 years), Mechanical Engineering, National Technical University of Athens, 1992 His research interests span computational fluid dynamics, cavitation, fuel injection, atomization, high-pressure and supercritical flows, and alternative fuels . He has developed advanced numerical models and experimental techniques, including X-ray phase contrast imaging and high-pressure test rigs. His work integrates fundamental DNS and LES simulations with industrial applications in automotive, marine, aerospace, and medical devices such as heart valves. The recent publications reflect a strong trend toward real-fluid thermodynamic modeling (e.g., PC-SAFT), multi-component fuel behavior, cavitation erosion, and advanced diagnostics . His research increasingly incorporates machine learning and high-fidelity imaging to understand complex flow phenomena across energy, transportation, and biomedical domains. Scientific Awards and Recognitions: Richard Way Prize (1998) Arch T. Collwell Merit Award (1998) Best Oral Paper, SAE World Congress (2006) PE Publication Award, IMechE (2007) Best Presentation Award, Engine Combustion Processes (2009) Fellow, IMechE (2013) Fellow, IMA (2015) As a dedicated mentor, Professor Gavaises has supervised 13 PhDs to completion and currently guides 23 doctoral students. He has secured over €16 million in EU and UK funding, including multiple Horizon 2020 Marie Skłodowska-Curie ITN projects (CAFÉ, HAOS, IPPAD), which support 46 early-career researchers globally. He has created academic opportunities for post-docs and junior faculty, significantly advancing the research profile of his institution. He leads the International Institute of Cavitation Research (IICR), co-founded in 2011 with partners from Loughborough University, TU Delft, and Imperial College, supported by The Lloyd’s Register Foundation. His lab maintains strong experimental capabilities, including a 2000bar pressure flow rig with micro-transparent nozzles and collaborations with Argonne National Laboratory for X-ray imaging.

• Computational Fluid Dynamics
• Internal Combustion Engines
• Cavitation
• +13 more

Philipp Schlatter is a Professor in the Department of Mechanics at KTH Royal Institute of Technology. His research focuses on fluid mechanics, turbulence, and computational fluid dynamics (CFD), with expertise in high-performance computing and direct numerical simulations (DNS). He leads projects involving scalable CFD frameworks like Neko and Nek5000, and investigates turbulent boundary layers, flow control, and coherent flow structures. His work includes experimental and numerical studies of wing profiles, rotating systems, and transition dynamics. Schlatter teaches courses on computational fluid dynamics and turbulence, emphasizing both theoretical and practical aspects of fluid mechanics. Key research interests include developing numerical methods for high-fidelity simulations, understanding turbulence mechanisms, and optimizing flow control strategies. His contributions span aerodynamics, heat transfer, and the application of machine learning to fluid dynamics problems. Schlatter collaborates extensively on interdisciplinary projects, leveraging advanced computing resources to address complex fluid flow phenomena. Publications highlight advancements in DNS frameworks, Bayesian optimization for flow control, and analysis of turbulent structures in pipe and boundary layer flows. His research also addresses challenges in measurement techniques and uncertainty quantification in CFD simulations.

• Fluid Mechanics
• Turbulence
• Computational Fluid Dynamics (CFD)
• +4 more

Brian Vermeire is an Associate Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His research focuses on computational fluid dynamics, aerodynamics, high-performance computing, turbulence modeling, numerical methods, and optimization. He leads the Computational Aerodynamics Laboratory, emphasizing scale-resolving simulations and high-order numerical techniques. Key interests include large eddy simulation (LES), direct numerical simulation (DNS), and gradient-free optimization. His work often involves developing advanced algorithms for unstructured grids and high-performance computing platforms. Research Interests: High-order numerical methods Implicit/explicit time integration schemes Polynomial adaptation for adaptive meshing Aeroacoustic shape optimization Large eddy simulation (LES) and direct numerical simulation (DNS) Software development for CFD (e.g., PyFR) Recent work trends show strong focus on hybridized flux reconstruction methods, energy-conservative algorithms, and industrial adoption of high-fidelity simulations. Major contributions include scalable implementations for petascale computing and open-source tools like PyFR. His group collaborates on applications such as wind turbine aerodynamics and low-pressure turbine design. Labs/Teams: Computational Aerodynamics Laboratory (website: link )

• Computational Fluid Dynamics
• Aerodynamics
• High-Performance Computing
• +6 more

Professor Michael Manhart is affiliated with the Technical University of Munich (TUM) as an Extraordinary Professor in the Department of Hydromechanics . His research focuses on fluid mechanics, turbulent flow dynamics, and computational fluid dynamics (CFD) simulations, particularly in porous media and environmental fluid mechanics. Education: Not explicitly stated in the provided text. His recent publications investigate turbulent flow over random sphere packs, scalar transport at porous-turbulent interfaces, acoustic resonances in HVAC systems, and nonlinear oscillatory flow modeling. He employs advanced numerical techniques like direct numerical simulations (DNS) and large-eddy simulations (LES) to study flow structures, energy budgets, and particle transport mechanisms. Professor Manhart collaborates with researchers such as Yoshiyuki Sakai, Simon Wenczowski, and Daniel Quosdorf. His work addresses applications in environmental engineering, hydraulic modeling, and industrial fluid dynamics, with a strong emphasis on validating computational models against experimental data (e.g., PIV measurements). He leads the Professorship for Hydromechanics at TUM, conducting high-fidelity simulations and experimental studies on topics like wall shear stress estimation, sediment erosion around cylinders, and turbulence decomposition in complex flows.

• Fluid Mechanics
• Turbulent Flow
• Porous Media Dynamics
• +3 more

James Massey is a Senior Research Fellow at the University of Cambridge, affiliated with the Department of Engineering under the Energy Group. His research focuses on computational fluid dynamics (CFD), turbulent reacting flows, and hydrogen combustion, supported by funding from Mitsubishi Heavy Industries (MHI). He holds a PhD in Engineering (2015-2019) and an MEng in Mechanical Engineering (2011-2015) from The University of Manchester. PhD in Engineering, University of Cambridge (2015-2019) MEng in Mechanical Engineering, The University of Manchester (2011-2015) His work spans hydrogen combustion , thermo-acoustics , and large eddy simulation (LES) , targeting emissions prediction, flame stabilization, and combustion instability. Key themes include mitigating CO/NOx emissions, analyzing swirl-stabilized flames, and developing skeletal mechanisms for hydrogen-hydrocarbon blends. Recent publications emphasize multi-regime combustion modeling , thermo-acoustic instability analysis , and machine learning applications in LES. His research often involves cross-institutional collaboration with MHI and contributions to combustion physics through DNS and LES frameworks. Sugden Award (2024) for best paper in The Combustion Institute British Section James contributes to teaching as a lecturer for courses like 4A13 Combustion and Engines (2023-2025) and ETB-1 Clean Fossil Fuels (2022-2023). He is a fellow of Robinson College and an active member of the Institute of Physics Combustion Physics Group and The Combustion Institute British Section.

• Computational Fluid Dynamics
• Turbulent Combustion
• Hydrogen Combustion
• +3 more

Johan Meyers is a full Professor at KU Leuven's Faculty of Engineering Science, Department of Mechanical Engineering, where he heads the Applied Mechanics and Energy conversion (TME) research unit. He serves as a contact person for TME and is an active member of the KIES – KU Leuven Institute for Energy and Society. His administrative roles include membership on the Council of the Faculty of Engineering Science, the Mechanical Engineering Department Council and Board, and chairing the HPC Steering Committee. Professor Meyers' research focuses on turbulent flow simulation and optimization, with particular emphasis on wind energy applications, atmospheric pollutant dispersion, and computational methods. His work spans Direct Numerical Simulation (DNS), Large-Eddy Simulation (LES), and model reduction techniques for applications in energy engineering. Current research categories include flow control & optimization, wind farm engineering, and atmospheric pollutant dispersion modeling, with specific applications in radioactive release scenarios and wind turbine system optimization. His recent publications demonstrate a strong trend toward wind energy applications, particularly in optimizing wind farm layouts and operations through advanced computational methods. The research shows significant emphasis on Large-Eddy Simulation techniques to study atmospheric boundary layer interactions with wind farms, with growing interest in hybrid wind-solar energy systems and the effects of surface temperature heterogeneity on flow patterns. His work increasingly integrates machine learning approaches to enhance computational efficiency in wind farm modeling. Professor Meyers actively supervises numerous PhD students including Bon, T., Janssens, N., Jamaer, S., and ALREWENY, A., among others. His research is supported by multiple ongoing projects through 2028, including 'Wind-farm co-design in the North-Sea basin given climate and market uncertainty' and 'Reconstruction of turbulence from partial observations,' primarily funded by research councils and industry partnerships. He leads the Turbulent Flow Simulation and Optimization (TFSO) research group, which develops efficient supercomputing simulation tools for turbulent flow applications in energy engineering. The group specializes in wind farm optimization, atmospheric pollutant dispersion modeling, and airborne wind energy systems, with a particular focus on LES studies of wind farm interactions with the atmospheric boundary layer.

• Wind Energy
• Turbulent Flow Simulation
• Flow Control & Optimization
• +5 more

Diego Donzis is a Professor in the Department of Aerospace Engineering at Texas A&M University, affiliated with the College of Engineering. He holds the Presidential Impact Fellow title. His work focuses on high-performance computing for fluid dynamics, particularly compressible turbulence, turbulent mixing, and shock-turbulence interactions. Donzis earned his Ph.D. and M.S. in Aerospace Engineering from the Georgia Institute of Technology. Research interests include large-scale simulations of turbulent flows, thermal boundary condition effects on turbulence, and the development of advanced numerical methods like Selected-Eddy Simulations (SES) for extreme-scale computing. His studies explore universality in turbulence scaling, energy spectra dynamics, and the interplay between compressibility and fluid mixing. Publications emphasize turbulence decay laws, shock-turbulence interactions, and the role of thermal non-equilibrium in turbulent flows. Notable contributions include advancing asynchronous algorithms for exascale CFD and analyzing density gradient statistics in compressible turbulence. Awards include the Presidential Impact Fellow distinction. Donzis collaborates on grants such as the Frontera Travel Grant for compressible turbulence research. His work bridges computational methods with fundamental fluid dynamics, addressing challenges in both numerical accuracy and physical modeling.

• Fluid Dynamics
• Turbulence
• Turbulent Mixing
• +3 more

Rohith Jayaram is a Postdoctoral Fellow in the Department of Chemical Engineering at the Norwegian University of Science and Technology (NTNU), specializing in multi-phase flows and turbulence dynamics. His research focuses on particle-laden flows, bubble-turbulence interactions, and computational fluid dynamics. Education: PhD in Particle suspensions from NTNU MSc in Aerospace Mechanics from ISAE-SUPAERO, France BEng in Mechanical Engineering from BMS College of Engineering, India His work investigates Lagrangian dynamics of solid particles and spheroids in evolving Taylor-Green vortex flows, with recent emphasis on bubble-turbulence interactions. He develops numerical algorithms for flow simulations and contributes to turbulence modeling in both 2D and 3D systems. Research trends include computational modeling of multi-phase flows, DNS validation of particle behavior in unsteady vortices, and extension to spheroid alignment dynamics. Publications span leading journals like Physics of Fluids and Physical Review E . Scientific Awards: Selected as Featured Article in Physics of Fluids (2020) Outreach activities include conference lectures at the European Fluid Dynamics Conference (2024) and European Turbulence Conference (2019). Contact: 238 Kjemiblokk 5 Gløshaugen, Trondheim; rohith.jayaram@ntnu.no

• Multi-Phase Flow
• Turbulence
• Lagrangian Dynamics
• +3 more

Professor Stuart Bruce Dalziel is a Professor of Fluid Mechanics at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge, where he has held academic roles since 2001. He leads the GK Batchelor Laboratory, a world-leading facility for experimental fluid dynamics. His research focuses on geophysical, environmental, and industrial fluid mechanics, employing theoretical, numerical, and experimental methods. Key areas include internal gravity waves, granular flows, turbulence, and building ventilation. Recent projects involve buoyant plumes, reactive flows, and applications like decontamination and hydrogen gas pipeline management. He is actively involved in supervising PhD students and has earmarked funding for projects on skipping stone dynamics and hydrogen gas purging in pipelines. Education and Career: Professor of Fluid Mechanics (2016–present) Reader in Fluid Mechanics (2012–2016) University Senior Lecturer (2001–2012) Director of the GK Batchelor Laboratory (1997–present) Research Interests: Dalziel’s work bridges experimental, numerical, and theoretical approaches to address challenges in fluid mechanics. Recent projects include studying stratified turbulence, Rayleigh-Taylor instabilities, and fluid dynamics in rotating systems. His applied research extends to environmental engineering, such as improving building ventilation systems and mitigating airborne disease transmission. Advising and Grants: He mentors PhD students from diverse backgrounds (mathematics, engineering, physics) and oversees funded projects combining experimental and computational methods. Current opportunities focus on novel fluid dynamics problems with practical applications. Labs and Facilities: The GK Batchelor Laboratory, under his leadership, develops advanced diagnostics and software for fluid dynamics research, widely adopted in the scientific community.

• Fluid Mechanics
• Environmental Fluid Dynamics
• Geophysical Fluid Dynamics
• +6 more

Abani Patra is a Professor of Computer Science, Mathematics, Mechanical Engineering, and Civil and Environmental Engineering at Tufts University. He also serves as the Center Director for Data Science at the Tufts Institute for Artificial Intelligence (TIAI). His research focuses on computational sciences and data-driven modeling, with applications spanning environmental systems, biomedical imaging, and geophysical hazards. He has directed major initiatives at the National Science Foundation (NSF) and U.S. Department of Energy (DOE), and previously founded the Institute for Computational and Data Sciences at the University at Buffalo. Education: PhD in Mathematics, University of Texas, 1995 MS in Mechanical Engineering, University of Missouri, 1990 BSc in Engineering, Birla Institute of Technology & Science, India Research Interests: Large-scale computational modeling and uncertainty quantification Data-driven approaches for geophysical hazards (e.g., debris flows, volcanic eruptions) Biomedical imaging and metabolic analysis Open science platforms for glaciology and volcanology Key Projects: Developed the Ghub platform for open cryosphere research Launched VICTOR, a cyberinfrastructure for volcanology Advanced AI-driven techniques for postfire debris flow prediction Grants & Leadership: Directed NSF and DOE programs in computational science PI for NSF Cyberinfrastructure grants Former director of the Institute for Computational and Data Sciences

• Computational Sciences
• Data Driven Modeling
• Computer Science
• +5 more

Paul Fischer is a Professor at the University of Illinois, holding dual appointments in the Siebel School of Computing and Data Science and the Mechanical Science and Engineering department. His research focuses on advanced numerical methods for fluid dynamics, particularly leveraging spectral element techniques and high-performance computing. He is a core contributor to the Nek5000/NekRS computational frameworks. Recent work emphasizes turbulence modeling, exascale CFD simulations, and multiphase flow dynamics in complex systems like pebble bed reactors. His research interests span spectral methods, large eddy simulation (LES), direct numerical simulation (DNS), and parallel computing architectures. Key projects include developing scalable algorithms for Reynolds-averaged Navier-Stokes (RANS) models and exploring non-conforming domain decomposition approaches for reacting flows. His contributions bridge computational methodology and engineering applications, with a focus on exascale-ready solutions. Publications from 2024-2025 highlight advancements in energy-efficient CFD simulations, turbulence transition mechanisms in granular media, and reduced order modeling for turbulent flows. Collaborations involve cross-disciplinary teams focusing on combustion, fluid-structure interaction, and high-fidelity flow analysis. He maintains active involvement in computational fluid dynamics communities and contributes to open-source software tools critical for industrial and academic research. Current efforts prioritize scalability, accuracy, and adaptability in numerical methods for next-generation supercomputing platforms.

• Computational Fluid Dynamics
• Spectral Element Method
• Large Eddy Simulation
• +3 more

Rudie P.J. Kunnen is an Associate Professor at the Faculty of Applied Physics and Science Education , Eindhoven University of Technology, leading the Turbulent and Multiphase Flows group. His research focuses on heat, mass, and particulate transport in turbulent flows, with applications in geophysics and industry. Active in UN Sustainable Development Goals related to environmental protection Collaborator in projects like Active Contamination Control for Equipment and SubstrateS Research Interests : Turbulent flow dynamics, rotating convection, vortex structures, thermophoresis, plasma-liquid interactions, and geostrophic turbulence. His work combines experimental and numerical approaches (e.g., direct numerical simulation, particle image velocimetry). Scientific Awards : NWO Vici Prize (2024) Advising and Collaborations : Supervised multiple BSc and MSc theses at TU/e. Collaborates with researchers like F. Toschi and H.J.H. Clercx on turbulence projects.

• Turbulent Flow
• Multiphase Flow
• Heat Transfer
• +7 more

Ricardo Martinez-Botas is a Professor of Turbomachinery and Associate Dean for Industry Partnerships at the Department of Mechanical Engineering, Imperial College London. He holds affiliations with the Electrochemical Science and Engineering, Energy Materials, Grantham Institute, Mechanics of Materials, and Network of Excellence in Air Quality. His academic career includes a DPhil from the Rolls Royce University Technology Center at the University of Oxford (1993) and an MEng in Aeronautical Engineering from Imperial College London. He also serves as a Visiting Professor at University Teknologi Malaysia. His research focuses on unsteady flow aerodynamics in turbochargers, supercritical CO2 systems, and thermal-fluids engineering. Notable contributions include advancements in turbine aerodynamics, pulsating flow control, and generative AI-driven design methodologies. He leads the Thermofluids Division and the Hybrid and Electric Vehicles Theme at the Energy Futures Lab. His work integrates computational fluid dynamics (CFD), experimental methods, and one-dimensional modeling for turbomachinery optimization. Key Awards: Dugald Clerk Prize (2011), ASME Turbomachinery Best Paper Awards (2010, 2009). Editorial Roles: Associate Editor of the Journal of Turbomachinery (ASME) and Journal of Mechanical Engineering Science (IMechE). Facility Leadership: Developed the TURBODYNA dynamic simulator for radial turbomachinery and commissioned a blowdown facility for dense gas vapor research. His research portfolio spans interdisciplinary topics like battery technology, organic Rankine cycle turbines, and sustainable automotive emissions control. He actively collaborates with industry partners to translate academic innovations into real-world applications, emphasizing energy efficiency, waste heat recovery, and low-carbon transportation solutions.

• Mechanical Engineering
• Aerospace Engineering
• Automotive Engineering
• +12 more