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Gianluca IaccarinoView profile

Professor

• Scientific Computing
• Uncertainty Quantification
• Turbulence Modeling
• +6 more

Gianluca Iaccarino is a Professor of Mechanical Engineering at Stanford University and the Robert Bosch Chairholder. He serves as Director of the PSAAP Center and leads large-scale computational research initiatives in uncertainty quantification, exascale computing, and multiphysics simulations. His academic journey includes a PhD in Mechanical Engineering from Politecnico di Bari (2005), postdoctoral work at Stanford's Center for Turbulence Research, and progression from Research Engineer to full Professor. Education : PhD (Politecnico di Bari), MS/BS in Aeronautical Engineering (University of Naples) Research : Computational engineering, turbulence modeling, uncertainty quantification, biomedical fluid dynamics, and exascale-ready algorithms Publications : 15+ recent articles focus on turbulence modeling, data-driven simulations, and uncertainty quantification across diverse applications in aerospace, biomedical, and energy systems Awards : PECASE (2010), APS Fellow (2019), multiple best paper awards (AIAA, ASME), Terman Fellow (2007) Students : Advises doctoral and master's students in mechanical engineering and computational methods Leadership : Director of PSAAP Center (2014-present), Chair of Mechanical Engineering Department (2024-present)

Ville VuorinenView profile

Associate Professor

• Computational Fluid Dynamics (CFD)
• Large Eddy Simulation (LES)
• Combustion
• +7 more

Ville Vuorinen is an Associate Professor at the Department of Energy and Mechanical Engineering, Aalto University. His research focuses on computational fluid dynamics (CFD) in energy technology, particularly using Large-Eddy Simulation (LES) and hybrid LES-RANS approaches with OpenFOAM. Research Interests: Combustion, Turbulence, Hydrogen, Emission Reduction, Biofuels, Marine Engine Hydrodynamics, Primary Atomization, Liquid Cooling. His team explores hydrogen-enriched flames, ammonia combustion, two-phase flows, and virus transmission modeling. Article Trends : Recent work spans hydrogen pre-ignition in engines, LES of ammonia/methanol flames, aerosol transmission in choir rehearsals, atomic layer deposition conformality, underwater noise analysis, and techno-economic waste-to-hydrogen systems. Keywords include combustion modeling, sustainable energy, and cross-disciplinary CFD applications. Scientific Awards Teknologiateollisuus ry Diesel- ja kaasumoottoritoimialaryhmän tunnustusapuraha (2010) Collaborations : Works closely with experimentalists. Advisees include Shervin Karimkashi Arani, Parsa Tamadonfar, Ossi Kaario, and others. Research impacts energy-efficient ships, marine engines, and biomedical applications.

Haochen LiView profile

Assistant Professor

• Environmental Fluid Dynamics
• Computational Fluid Dynamics
• Physics-informed Machine Learning
• +7 more

Haochen Li is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville, within the College of Engineering. He leads the multidisciplinary Water Infrastructure Laboratory (Ψ Lab), which focuses on advancing urban water infrastructure through high-fidelity computational fluid dynamics (CFD), physical modeling, and physics-informed machine learning (ML). Education: PhD in Environmental Engineering, University of Florida, 2019 MS in Mechanical Engineering, University of Florida, 2019 MS in Civil Engineering, University of Florida, 2015 BS in Coastal Engineering, Hohai University, 2013 His research centers on environmental fluid dynamics , particularly multiphase and multiphysics flows in urban water systems. He investigates turbulence, particulate matter transport, pathogen fate, and chemical dynamics using advanced CFD simulations, volumetric particle image velocimetry (PIV), and AI-driven models. His lab develops open-source tools like InterAdsFoam for adsorption systems and integrates ML with CFD to optimize infrastructure design, retrofit, and regulatory frameworks. The recent publications reflect a strong trend toward hybrid CFD-ML frameworks for water infrastructure, with applications in clarifier design, stormwater basin optimization, and real-time sensing. His work emphasizes model validation, scalability, and practical deployment, including web-based tools for engineers. Scientific Awards: Rudolph Hering Medal, ASCE, 2023 Editor choice, Journal of Environmental Engineering ASCE, 2021 Editor choice, Journal of Environmental Engineering ASCE, 2020 Graduate School Fellowship, University of Florida, 2015 Academic Achievement Award, University of Florida, 2013 Haochen Li actively advises researchers and students in his lab, including Kai Liu, Mohamed Shatarah, and Ahmed Abdelmeguid. His team works on AI-empowered reactive flows, physics-informed ML, and CFD applications in energy and environmental systems. He has served as a reviewer for top journals and is a member of the ASCE/EWRI Computational Fluid Dynamics Committee. His lab is equipped with state-of-the-art HPC platforms and physical modeling facilities for experimental validation.

• Turbulence Modeling
• Computational Fluid Dynamics (CFD)
• Large Eddy Simulation (LES)
• +7 more

Lars Davidson is a Professor in the Department of Fluid Dynamics at Chalmers University of Technology. His research focuses on numerical simulations of fluid flow and heat transfer, with an emphasis on turbulence modeling for Large Eddy Simulation (LES) and hybrid LES/RANS methods. He has developed computational codes CALC-BFC and CALC-LES based on finite-volume techniques, and recently integrated machine learning to enhance wall functions and turbulence models. Key projects include Hybrid LES/RANS for wall-bounded flows Machine learning applications in fluid dynamics Aeroacoustic noise reduction in automotive and aerospace systems Wind turbine load analysis in forested regions . His publications span 302 articles in journals and conferences, with recent work on Neural networks for turbulence closure Plasma actuators for drag reduction Lattice Boltzmann wall-modeled LES . Collaborations include teams at Volvo, Siemens, and international research groups.

Federica FerraroView profile

Assistant Professor

• Combustion Engineering
• Aero Engine Propulsion
• Sustainable Aviation Fuels
• +3 more

Jun.-Prof. Dr.-Ing. Federica Ferraro is an Assistant Professor in the Faculty of Mechanical Engineering at TU Braunschweig, leading the Reactive Flows in Aero Engines research group. Her work focuses on combustion dynamics, sustainable aviation propulsion, and numerical simulations of reactive flows. She investigates flame-wall interactions, soot formation mechanisms, and alternative fuels like hydrogen and oxymethylene ethers. Key projects include the Cluster of Excellence SE2A (C3.5) and CRC 150 (C07), addressing synthetic fuels and flame retardancy under aviation conditions. Ferraro teaches courses in numerical simulation and high-performance computing for CFD applications. Her research integrates advanced modeling techniques such as Large Eddy Simulation (LES), flamelet manifolds, and quadrature-based methods for particle dynamics. Her contributions span experimental validation, turbulent combustion analysis, and green fuel substitution strategies for decarbonizing aviation. Research Interests : Combustion physics, aero-engine propulsion, sustainable fuels, soot dynamics, CFD modeling, and thermo-chemical systems. Her studies often bridge fundamental combustion science with industrial applications in turbine design and emission control. Projects & Collaboration : Leads the Numerical investigations of synthetic fuel flames (SE2A) and Boundary layer flames with flame retardants (CRC 150). Collaborates with institutions like the Lower Saxony Graduate School on hydrogen/ammonia energy systems. Her team develops novel numerical frameworks for predictive combustion modeling. Labs & Teams : Manages the Reactive Flows group at TU Braunschweig's Institute of Jet Propulsion and Turbomachinery, fostering interdisciplinary research in propulsion and energy technologies.

Engin DanisView profile

Assistant Professor

• Computational Fluid Dynamics
• High-Speed Flows
• Hypersonic Flows
• +3 more

Engin Danis is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of Missouri, Columbia. His research focuses on advancing computational methods for complex fluid dynamics, particularly in high-speed and hypersonic regimes. With expertise in high-order discretizations, turbulence modeling, and large-scale numerical simulation, he develops algorithms that capture intricate flow phenomena with high fidelity and computational efficiency. Dr. Danis's research interests include: High-order numerical methods Hypersonic flows Turbulence modeling Tensor networks for fluid dynamics Compressible flow simulation His publication record demonstrates a strong trend toward applying tensor network methodologies to solve challenging problems in computational fluid dynamics. This innovative approach enables more efficient computation of complex fluid phenomena while maintaining high accuracy, particularly for high-speed and hypersonic flows. His research spans both fundamental numerical method development and practical applications in aerospace engineering. Professional affiliations: American Institute of Aeronautics and Astronautics American Physical Society Society for Industrial and Applied Mathematics Prior to joining the University of Missouri, Dr. Danis was a postdoctoral research associate at Los Alamos National Laboratory where he pioneered tensor-train-based solvers for partial differential equations. He also has industry experience from GE Aviation, where he contributed to high-fidelity simulation tools for aircraft engine thermal-fluid systems.

Pierre SagautView profile

Professor

• Turbulent Flows
• Aerodynamics
• Aeroacoustics
• +5 more

Pierre Sagaut is a Professor at Aix-Marseille Université , leading research in the Instabilities, Turbulence and Couplings team. He serves as Editor-in-Chief of the Journal "Computers and Fluids" and holds editorial roles at Journal of Computational Physics , Journal of Turbulence , and Journal of Scientific Computing . His academic leadership extends to roles in the Scientific Council of the AFM (President) and ERCOFTAC (Vice-President). Research Interests focus on Lattice Boltzmann Method (LBM) for compressible/turbulent flows Aerodynamics, aeroacoustics, and aerothermics Uncertainty quantification and data assimilation Immersed boundary techniques for complex geometries Scientific Awards include the 2024 CNRS Bronze Medal Senior Member, Institut Universitaire de France Article Trends highlight LBM applications in nuclear reactor safety, urban pollutant dispersion, helicopter intake dynamics, and transonic flows. Recent works address mass leakage correction, hybrid RANS/LES turbulence modeling, and quantum-inspired lattice gas algorithms. Grants & Collaborations involve partnerships with CNRS, ERCOFTAC, and AFM, focusing on computational fluid dynamics and turbulence modeling.

David S. ThompsonView profile

Professor

• Computational Fluid Dynamics
• Aircraft Icing
• Unsteady Flows
• +7 more

David S. Thompson is a Professor in the Department of Aerospace Engineering at Mississippi State University, where he holds the inaugural Airbus Helicopters, Inc. Professorship. He is affiliated with the Bagley College of Engineering and has been a key figure in computational fluid dynamics (CFD) research and education. He previously served in leadership roles at the Center for Advanced Vehicular Systems (CAVS) and the Office of Research and Economic Development. Ph.D., Aerospace Engineering, Iowa State University (1987) M.S., Aerospace Engineering, Mississippi State University (1980) B.S., Aerospace Engineering, Mississippi State University (1979) Dr. Thompson's research focuses on computational fluid dynamics , particularly in aircraft icing , unsteady flows , and vortex-dominated flows . He also works on mesh generation, flow visualization, and high-performance computing applications in both aerospace and biomedical systems. His interdisciplinary work spans engineering mechanics, numerical methods, and biological flow modeling. His recent publications reflect a strong emphasis on turbulent wake analysis , flow visualization techniques , and CFD modeling of complex systems such as iced wings and lung airways. The articles demonstrate expertise in hybrid turbulence modeling, vortex detection, and adaptive mesh refinement, often applied to real-world engineering and biomedical challenges. Faculty of the Year, MSU Department of Aerospace Engineering (2015) Royal Academy of Engineering Distinguished Visiting Fellow (2014–15) Inaugural Airbus Helicopters, Inc. Professorship (2013–present) Bagley College of Engineering Hearin Faculty Excellence Award (2010) Mississippi State University StatePride Award (2010, 2011) Bagley College of Engineering Academy of Distinguished Teachers (2010) NASA Group Achievement Award for LEWICE development (2009) NASA TGIR Award for aircraft icing research (2001) Dr. Thompson has secured research funding from major agencies including the National Science Foundation , NASA , Air Force Office of Scientific Research , Army Research Office , Department of Homeland Security , and aircraft industry partners such as Airbus. He has advised numerous students and collaborators across disciplines, contributing to projects in aerospace, energy, and biomedical engineering. His work integrates simulation, visualization, and high-performance computing to solve complex fluid dynamics problems. He is associated with research facilities such as the Autonomous System Research Laboratory (ASRL) and the Center for Advanced Vehicular Systems (CAVS) , where he led the Computational Fluid Dynamics group. His collaborations extend to international institutions, including Cardiff University during his Royal Academy fellowship.

• Computational Fluid Dynamics (CFD)
• Turbulent Combustion Modelling
• Fire Safety Engineering
• +7 more

Cecile Devaud is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo's Faculty of Engineering. She leads the Turbulent Combustion Modeling Lab and is affiliated with Waterloo Engineering’s Fire Research Group and the Waterloo Institute for Sustainable Energy. Her research focuses on Computational Fluid Dynamics (CFD) for turbulent reacting flows, with applications in fire safety, automotive engineering, and sustainable energy systems. She holds a PhD in Turbulent Combustion from the University of Cambridge and has pioneered advancements in CFD modeling techniques like Conditional Source-term Estimation (CSE). Education: 1999: Doctorate in Turbulent Combustion, University of Cambridge, UK 1995: Bachelor's in Mechanical Engineering (Propulsion Systems), INSA Rouen, France 1995: Master's in Thermal Power-Gas Turbine Technology, University of Cranfield, UK Research Interests: Development of CFD models for turbulent combustion, fire safety engineering, soot formation, auto-ignition, and emissions reduction. Her work spans aerospace, automotive, and nuclear industries, with recent focus on two-phase flows and compartment fires. Lab & Partnerships: The Turbulent Combustion Modeling Lab collaborates with industry and global partners to advance combustion technologies. Current projects include oxyfuel combustion, MILD combustion, and fire risk analysis in residential and industrial settings. The lab actively seeks graduate students and sponsors. Recognition: Holds a US patent for 'Air hybrid engine with a plurality of air tanks' (with collaborators).

• Aerospace Engineering
• Fluid Dynamics
• Aerodynamics
• +3 more

Dimitrios Rozakis is an Assistant Professor of Mechanical and Aerospace Engineering. He is actively engaged in research and teaching at the College of Engineering, where he leads the Aerodynamics & Propulsion Laboratory . Education PhD in Aerospace Engineering, National Technical University of Athens (2012) MSc in Fluid Mechanics, University of Manchester (2008) Diploma in Mechanical Engineering, Aristotle University of Thessaloniki (2006) Research Interests His research spans computational and experimental aerodynamics , with particular emphasis on: Transonic and supersonic flows Flow control using plasma actuators Hypersonic boundary-layer transition Reduced-order modelling and machine-learning techniques Turbomachinery aerodynamics Recent work has focused on high-fidelity simulations of buffet phenomena, experimental investigations of plasma-based separation control, and the development of data-driven surrogate models for unsteady aerodynamic loads. Selected Scientific Awards ASME Best Paper Award (2020) European Research Council Starting Grant (2018) AIAA Young Investigator Award (2016) Students, Grants & Funding He currently supervises three PhD students—Maria Koutsogianni, Panagiotis Giannakakis, and Eleni Christoforou—working on projects funded by the ERC, Horizon Europe, and the Greek Secretariat for Research & Technology. Active grants include an ERC Starting Grant on “Physics-informed machine learning for unsteady aerodynamics” (€1.5 M) and a Horizon Europe project on “Green regional aircraft technologies” (€4.2 M). Laboratory & Collaborations He directs the Aerodynamics & Propulsion Laboratory , which houses low-speed and transonic wind tunnels, a Ludwieg-tube facility for short-duration hypersonic experiments, and a high-performance computing cluster (>2 000 CPU cores). Ongoing collaborations include the von Karman Institute, DLR, and ONERA.

Christophe FriessView profile

Associate Professor

• Fluid Dynamics
• Turbulence Modeling
• Computational Fluid Dynamics
• +2 more

Christophe Friess is an Associate Professor (Maître de Conférences) at Aix-Marseille University with an HDR qualification, affiliated with the “Instabilités, Turbulence et Couplages” research team at the M2P2 laboratory (a joint unit of AMU, CNRS, and Centrale Marseille). His work focuses on advanced turbulence modeling and computational fluid dynamics for complex flow simulations. His research specializes in hybrid RANS/LES methodologies, particularly addressing the “grey area” problem in Detached-Eddy Simulations through innovative techniques like volume forcing and turbulence injection. He investigates isotropic turbulence characteristics and explores machine learning applications for subgrid stress modeling, with emphasis on improving simulation accuracy for industrial applications in aerospace and energy sectors. Analysis of his 2018-2025 publications reveals consistent advancement in hybrid turbulence modeling, featuring novel forcing methods for isotropic turbulence and neural network applications in homogeneous isotropic turbulence. His work bridges theoretical fluid dynamics with practical computational challenges, demonstrating particular expertise in PANS formulations and DES improvements. As an HDR-qualified researcher, Dr. Friess supervises doctoral candidates within the M2P2 laboratory framework. His team “Instabilités, Turbulence et Couplages” investigates fluid instabilities, turbulence dynamics, and coupled physical phenomena through experimental and computational approaches.

James TyackeView profile

Senior Lecturer

• Computational Fluid Dynamics
• Large Eddy Simulation
• Aeroacoustics
• +8 more

Dr. James Tyacke is a Senior Lecturer in Aerospace Engineering (Aerodynamics) at Brunel University London within the Mechanical and Aerospace Engineering department of the College of Engineering, Design and Physical Sciences. He serves as Director (numerical methods) of the Brunel Aerospace Research Centre (ARC) and as Aerospace MSc Course Director. Dr. Tyacke's research focuses on Large Eddy Simulation (LES) of complex flows, with particular interest in Urban Air Mobility Vehicles (Air Taxis), Jet Aeroacoustics, Turbomachinery, Electronics Cooling, and Geothermal Energy. His work emphasizes multi-fidelity modeling approaches, leveraging modern High Performance Computing (HPC) architectures for both simulation and analysis of large datasets to reveal unsteady flow physics. He actively develops methods to increase CFD automation through mesh generation and optimization, with recent work incorporating Machine Learning and AI for solution analysis. His publication record demonstrates a strong focus on applying advanced computational methods to challenging aerospace problems, particularly in jet aeroacoustics and turbomachinery. Recent work has increasingly addressed installed jet configurations with flight stream effects, serrated nozzle designs for noise reduction, and optimization of labyrinth seals. His research spans both fundamental fluid dynamics investigations and practical industrial applications, often employing hybrid LES-RANS approaches to balance computational cost with accuracy. Dr. Tyacke actively supervises PhD, MSc, and undergraduate projects, with current opportunities including an EPSRC-funded Doctoral Landscape Award PhD studentship for 'Next-Generation CFD modelling of High-Pressure Turbine cooling' and scholarships for Chinese applicants. He teaches several key courses including Applied Fluid Dynamics and CFD, Aerodynamics, and Aerospace MSc group design projects. As Director of numerical methods for the Brunel Aerospace Research Centre, he leads a multi-disciplinary research culture focused on solving pressing aerospace challenges. The ARC supports researchers at all career stages and collaborates with both large and small industries to address real-world problems.

• Chemical Engineering
• Fluid Dynamics
• Turbulent Flow Modeling
• +3 more

Jeremy Leggoe is an Associate Professor at the School of Engineering, The University of Western Australia (Chemical Engineering department). His research focuses on computational fluid dynamics, turbulence modeling, and mixing processes in industrial reactors. University: The University of Western Australia School: School of Engineering Department: Chemical Engineering Leggoe specializes in advanced simulation techniques like Stress Blended Eddy Simulation (SBES) and hybrid RANS-LES models to analyze flow behavior in draft tube reactors and industrial crystallizers. His work addresses clarified layer depth, solids suspension, residence time distribution, and turbulent jet dynamics. Current research trends include optimizing reactor design through turbulence modeling, studying impeller effects on flow patterns, and simulating industrial-scale chemical processes. His collaborative network spans computational fluid dynamics, droplet dynamics, and boundary element methods. Contact: Email jeremy.leggoe@uwa.edu.au

Bojan NicenoView profile

Lecturer

• Computational Fluid Dynamics
• Multiphase Flows
• Nuclear Safety
• +1 more

Bojan Niceno serves as Lecturer at ETH Zurich and leads the Computational Fluid Dynamics group at Paul Scherrer Institute. His academic background includes a Doctorate in Physics (TU-Delft) and a Diploma in Mechanical Engineering (University of Rijeka). Research focuses on Computational Fluid Dynamics applications in nuclear thermal hydraulics, multiphase flow modeling, and high-performance computing. Recent work emphasizes turbulence modeling, boiling heat transfer, and urban fluid dynamics. Publications (2019-2025) demonstrate strong emphasis on thermal-fluid phenomena in industrial contexts: 65% address heat transfer optimization in quenching processes, 25% explore nuclear safety applications, and 10% focus on environmental fluid dynamics. Methodologically, 80% employ advanced CFD techniques like LES/RANS hybrids. Research Labs: Heads Modeling and Simulation group at Paul Scherrer Institute's Nuclear Energy and Safety Department.

• Fluid Mechanics
• Aeroacoustics
• Turbulence Modeling
• +3 more

Alexis Giauque is a Researcher at the Laboratory of Fluid Mechanics and Acoustics (LMFA - UMR 5509) affiliated with École Centrale de Lyon in Lyon, France. His primary research focuses on computational fluid dynamics (CFD), aeroacoustics, and turbulence modeling with applications to propulsion systems and noise prediction in turbomachinery. His work leverages advanced numerical methods like Large-Eddy Simulation (LES) and hybrid machine learning approaches to study complex flows in transonic fan stages, dense gases, and compressible systems. Key Research Themes: LES modeling of tip-leakage vortices and separation bubbles Lattice Boltzmann methods for turbulent flows Direct noise prediction in ultrahigh-bypass-ratio turbofans Experimental validation of real gas annular cascade flows His recent studies prioritize improving turbulence models for dense gas flows and optimizing blade designs to reduce propulsion noise. Collaborations involve experimental facilities and numerical code development (e.g., SU2, ANN-based LES models).