جست‌وجوی استاد و پژوهشگر

• Aerodynamics
• Fluid Mechanics
• Aircraft Configuration Aerodynamics
• +۵ مورد دیگر

Prof. Dr. Christian Breitsamter is a Professor at the Technische Universität München (TUM), leading the Chair of Aerodynamics and Fluid Mechanics within the TUM School of Engineering and Design. He has held this position since 2007 and has been a member of key committees such as the ICAS Programme Committee and STAB-Programmleitung. His research focuses on aerodynamics of aircraft and rotorcraft configurations, including vortex dynamics, aeroelasticity, and fluid-structure interaction. Education: PhD in Aerodynamics (1997) Master’s in Aerospace Engineering (1989) Research Interests: Prof. Breitsamter’s work spans experimental and numerical studies of high-agility aircraft, helicopter aerodynamics, and advanced wing designs. Key areas include leading-edge vortices, gust load mitigation using flexible wings, and flow control techniques. His group investigates cutting-edge topics like deep learning for buffet prediction and hybrid neural networks for aerodynamic modeling. Awards: Willy Messerschmitt Preis (1999) AIAA Associate Fellow (2007) Advising & Grants: While specific student names are not listed, his research involves collaborative projects with industry partners (e.g., RACER Compound Helicopter) and EU initiatives like the FURADO program. His team contributes to the NFDI4ING infrastructure for engineering data. Labs/Teams: Active in the Aerodynamics Wind Tunnel facilities (Windkanäle A/B/C) and leads the SAGITTA flying wing demonstrator project. His group also explores membrane wings and elasto-flexible morphing technologies.

• Applied aerodynamics
• Sustainable aviation
• Distributed propulsion
• +۷ مورد دیگر

Phillip J. Ansell is an Associate Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering. He directs the Center for Sustainable Aviation and the Center for High-Efficiency Electrical Technologies for Aircraft. His academic positions include Assistant Professor (2015–2021) and current role as Associate Professor since 2021. He teaches courses such as AE 416 (Applied Aerodynamics), AE 419 (Aircraft Flight Mechanics), and AE 515 (Wing Theory). Education: BS, The Pennsylvania State University, Aerospace Engineering, 2008 MS, UIUC, Aerospace Engineering, 2010 PhD, UIUC, Aerospace Engineering, 2013 Research Interests: Focuses on applied aerodynamics, sustainable aviation, distributed propulsion, flow control, and aircraft electrification. His work integrates experimental fluid mechanics and computational models to advance aviation sustainability. Key projects include hydrogen propulsion systems, cryogenics in aviation, and unsteady aerodynamics for rotorcraft. Research Contributions: Authored/co-authored books like Aircraft Cryogenics (Springer, 2024). His articles address sustainable aviation frameworks, hydrogen-electric propulsion, and high-lift aerodynamics. Recent trends emphasize decarbonization pathways and system-of-systems analysis. Awards & Honors: Dean's Award for Excellence in Research (2025) NASA Innovative Advanced Concepts Fellow (2025) AIAA Associate Fellow (2024) Forbes 30 Under 30 (2016) Advising & Grants: Advises graduate students on propulsion and aerodynamics. Secured grants from AFOSR, ARO, and NASA. Active in AIAA committees, including Electrified Aircraft Technology Technical Committee (Chair, 2020–2023). Labs & Teams: Leads the Aerodynamics and Unsteady Flows Research Group, using UIUC’s wind tunnel facilities. Collaborates on projects like the Five Circles of Sustainable Aviation framework and cryogenic propulsion systems.

Parviz Moinمشاهده پروفایل

استاد

• Computational Physics
• Turbulent Boundary Layers
• Hypersonic Flows
• +۴ مورد دیگر

Parviz Moin holds the Franklin P. and Caroline M. Johnson Professorship in Stanford University's School of Engineering. As founding director of the Center for Turbulence Research (CTR)—a NASA-Stanford consortium established in 1987—he has pioneered computational methods for turbulence physics, including direct numerical simulation and Large Eddy Simulation (LES) techniques. CTR serves as an international hub for turbulence studies across engineering, mathematics, and physics disciplines. Moin's research encompasses computational physics of turbulent flows, with emphasis on boundary layer control, hypersonic aerodynamics, propulsion systems, and aircraft icing. His recent work advances high-fidelity simulations for aerospace applications, particularly developing wall models for LES that accurately capture separation phenomena under complex pressure gradients and Reynolds number effects. Recent publications demonstrate extensive applications of LES to aircraft design challenges, including transonic buffet prediction, high-lift configuration analysis, and icing aerodynamics. Investigations consistently address fundamental turbulence physics while developing practical computational tools for aerospace engineering, with particular focus on hypersonic boundary layers, flow separation mechanisms, and conjugate heat transfer in iced environments.

Jaime Peraireمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Finite Element Methods
• Aerodynamics
• +۷ مورد دیگر

Jaime Peraire is the H.N. Slater Professor of Aeronautics and Astronautics at MIT, affiliated with the School of Engineering. He leads research in computational mechanics, aerodynamics, and numerical methods for partial differential equations, with key roles as former Department Head (2011-2018) and Director of the Aerospace Computational Design Lab (1993-2011). His expertise spans finite element methods, shock capturing algorithms, and high-order numerical techniques applied to hypersonic flows, space weather, and metamaterials. Education includes a Ph.D. from the University of Wales (1986) and engineering degrees from the University of Barcelona (1983, 1987). He holds prestigious awards like the T.J. Hughes Medal (2015) and the Ildefons Cerdá Medal (2015). His work bridges computational science and engineering, with contributions to discontinuous Galerkin methods, mesh adaptivity, and GPU-accelerated simulations. Research interests emphasize high-fidelity modeling of compressible flows, plasma dynamics, and terahertz spectroscopy. Notable projects include MIT’s space weather modeling initiative and metamaterial fabrication using atomic layer lithography. His labs collaborate across MIT’s Schwarzman College of Computing, IDSS, and CCSE to advance computational tools for aerospace and environmental systems. Awards: Over 10 major prizes, including NASA Exceptional Achievement (1997) and IACM Young Researchers Award (1998). Grants/Advising: Led NSF-funded space weather projects and advised numerous PhD students in computational engineering. Labs: Aerospace Computational Design Lab, MIT Schwarzman College of Computing collaborations.

• Computational Fluid Dynamics
• Scientific Machine Learning
• Data-Driven Modeling
• +۳ مورد دیگر

Shaowu Pan is an Assistant Professor of Aerospace Engineering at Rensselaer Polytechnic Institute (RPI), affiliated with the Future of Computing Institute (FOCI) and the Scientific Computation Research Center (SCOREC). He holds a Ph.D. in Aerospace Engineering and Scientific Computing from the University of Michigan and completed a postdoctoral fellowship at the University of Washington’s AI Institute in Dynamic Systems. Education: Ph.D., University of Michigan, 2021 M.S., University of Michigan, 2015 B.E. & B.S., Beihang University, 2013 Research Interests: His work focuses on the intersection of computational fluid dynamics, data-driven modeling, and scientific machine learning. Key areas include operator-theoretic modeling of fluid flows, generative AI for physical systems, and physics-informed neural networks. He develops novel algorithms for reduced-order modeling and stability-preserving surrogate models, with applications in turbulence, plasma physics, and aerodynamics. Key Contributions: Developed PyKoopman , an open-source Python package for Koopman operator approximation. Pioneered mesh-agnostic representation methods like Neural Implicit Flow for spatio-temporal data. Advanced physics-informed neural networks for solving Grad-Shafranov equations and plasma equilibrium problems. Awards & Recognition: John Tichy Junior Faculty Travel Grant (2024) Chinese Outstanding Student Abroad Award (2021) Richard and Eleanor Towner Prize Nominee (2019) Teaching & Mentorship: He teaches courses like MANE 2110: Numerical Methods and Programming for Engineers and mentors multiple Ph.D., master’s, and undergraduate students. His doctoral committee involvement spans interdisciplinary projects in fluid dynamics and AI. Grants & Software: Lead PI for NSF-funded projects on neural representation learning for turbulent flows. Developed software tools like spKDMD and Warp-DG for dynamics analysis and CFD simulations. Labs & Collaborations: Collaborates with institutions like Los Alamos National Laboratory and actively participates in conferences (e.g., AIAA SciTech, SIAM). His research bridges computational science, machine learning, and fluid dynamics to address complex nonlinear systems.

Kshitij Sabnisمشاهده پروفایل

مدرس

• Experimental Aerodynamics
• High-Speed Aerodynamics
• Vehicle Aerodynamics
• +۷ مورد دیگر

Kshitij Sabnis is a Lecturer in Aerospace Engineering at the School of Engineering and Materials Science, Queen Mary University of London. He serves as Admissions Lead and Outreach & Recruitment Lead for Aerospace Engineering, and Deputy Director of Industrial Engagement (Graduate Attributes). He is affiliated with the Centre for Intelligent Transport and conducts experimental research in high-speed aerodynamics. Education: PhD in Experimental Aerodynamics, University of Cambridge Master’s in Physics Dr Sabnis's research focuses on experimental aerodynamics across various speed regimes, particularly shock/boundary-layer interactions, vortex dynamics, and supersonic flows. His work involves wind tunnel experiments on simplified models to understand complex fluid mechanics in applications ranging from racecar wings to supersonic aircraft intakes. He employs advanced diagnostics and develops novel experimental setups to enhance physical insight into flow phenomena. His recent publications (2019–2025) reflect a strong emphasis on high-speed flow behavior, including shock-induced separation, vortex interactions, and nacelle aerodynamics. Key themes include flow control, wind tunnel design, and validation of turbulence models. His work bridges fundamental fluid dynamics with practical aerospace engineering challenges. Scientific Awards: FHEA (Fellow of the Higher Education Academy) Dr Sabnis actively supervises PhD students and leads externally funded research projects. He has secured grants from EPSRC and the Royal Society, supporting work on schlieren imaging enhancement and small-scale wind turbines for rural energy. He teaches advanced aerodynamics modules and contributes to curriculum and industrial engagement. He leads a research group focused on experimental high-speed aerodynamics and is involved in developing new diagnostic techniques and test rigs. His team investigates vortex interactions and aerodynamic performance under extreme flow conditions.

Wing Ngمشاهده پروفایل

استاد

• Aeroacoustics
• Turbomachinery
• Heat Transfer
• +۶ مورد دیگر

Wing Ng serves as Alumni Distinguished Professor and Chris C. Kraft Endowed Professor in Virginia Tech's Department of Mechanical Engineering within the College of Engineering. His career spans over four decades with continuous contributions to aerospace thermal systems and fluid dynamics research since joining Virginia Tech in 1984. Dr. Ng's academic foundation includes: Ph.D. in Mechanical Engineering from Massachusetts Institute of Technology (1984) M.S. in Mechanical Engineering from Massachusetts Institute of Technology (1980) B.S. in Mechanical Engineering from Northeastern University (1979) His pioneering research focuses on aeroacoustics of drones and jet engines, where he develops advanced diagnostics for turbine flow measurements and investigates transonic turbine blade aerodynamics. Current work explores aerothermal particle interactions in gas turbines and clean energy applications for wind turbines. His experimental approach bridges fundamental fluid dynamics with practical aerospace engineering solutions, particularly in cooling systems for high-temperature components. Analysis of recent publications (2024-2025) reveals three dominant research thrusts: turbine cooling optimization (film/phantom cooling configurations), particle dynamics in gas paths (impact/rebound mechanics), and novel measurement techniques (strain sensors, multiphase flow diagnostics). These studies consistently target performance enhancement and durability improvement in turbomachinery through experimental validation. Dr. Ng's exceptional contributions are recognized through: Virginia Tech Faculty Entrepreneur Hall of Fame (2017) William E. Wine Award for teaching excellence (2014) Multiple Certificates of Teaching Excellence (1985,1988,2011,2014) Dean's Award for Research Excellence (2013) Consecutive Best Paper Awards from ASME/AIAA (2001-2013) Fellow of ASME (1996) and Associate Fellow of AIAA (1992) As director of the Ng Lab, he maintains active collaborations with industry partners through Techsburg, Inc. (where he serves as Chairman) to translate research into commercial applications. His work on drone aeroacoustics and turbine diagnostics directly informs next-generation propulsion systems while addressing critical challenges in particle ingestion and thermal management.

• Aeroacoustics
• Computational Fluid Dynamics (CFD)
• Noise Propagation Modeling
• +۳ مورد دیگر

Professor Alec Wilson holds the position of Professor in Computational Aeroacoustics at the University of Southampton, where he serves as Director of the Rolls-Royce University Technology Centre (UTC) in Propulsion Systems Noise within the Faculty of Engineering and Physical Sciences. His career spans academic research and industrial collaboration, focusing on aeroengine noise sources, sound propagation modeling, and computational fluid dynamics (CFD) applications for aerospace systems. University of Southampton (2016–present): Professor in Computational Aeroacoustics Rolls-Royce (prior to 2016): Technical specialist in aeroengine noise and CFD Research Interests: Alec’s work centers on advancing eigen analysis techniques for acoustic propagation in complex duct geometries and mean flows. His research addresses challenges in next-generation aircraft noise modeling, including boundary layer effects, transonic fan optimization, and multi-disciplinary design approaches. Key contributions include developing fast, computationally efficient methods for noise prediction and sensitivity analysis in propulsion systems. Recent Research Trends: His 2024 publications focus on tone noise propagation and buzz-saw noise under flow distortion, while earlier works (2019–2022) explore non-uniform duct modeling, adjoint optimization for blade design, and error quantification in eigen analysis. Scientific Awards: Rolls-Royce Engineering Fellowship (Associate Fellow in Aerodynamics, Hydrodynamics, and Computational Fluid Dynamics) Teaching & Supervision: Alec supervises PhD students and teaches in acoustics, aerodynamics, and mechanical engineering. He currently advises Joseph Stephen Paul Binns, focusing on aeroacoustic modeling and optimization. External Roles: Vice-chair of CEAS/ASC (Council of European Aerospace Societies, Aeroacoustics Subcommittee).

• Aerospace Engineering
• Sustainable Aviation
• Hydrogen Propulsion Systems
• +۵ مورد دیگر

Phillip J Ansell is an Associate Professor in the Department of Aerospace Engineering at the University of Illinois. He serves as the Director of the Center for High-Efficiency Electrical Technologies for Aircraft (CHEETA), focusing on advancing sustainable aviation through innovative propulsion and energy systems. His research interests include aerodynamics optimization, hydrogen propulsion, electric aircraft integration, and cryogenic technologies. Ansell has received prestigious awards such as the AFOSR Young Investigator Award (2015), ARO Young Investigator Award (2017), and the Lawrence Sperry Award (2023), recognizing his contributions to sustainable aviation and flow control technologies. His work spans interdisciplinary areas like hydrogen fuel cell systems, airfoil design, and electrified aircraft architectures. Recent research emphasizes sustainable aviation frameworks, cryogenic hydrogen storage, and propulsion-airframe integration. Ansell has collaborated on projects involving distributed propulsion systems, wind energy optimization, and advanced plasma actuators for flow control. His leadership in CHEETA drives innovations in superconductivity and high-temperature superconducting components for next-generation aircraft. Notable contributions include studies on laminar flow control, transonic aerodynamics, and the technical challenges of integrating MW-scale hydrogen propulsion systems. His publications reflect a blend of theoretical modeling, experimental validation, and systems engineering approaches to address aviation's sustainability challenges.

Juan Alonsoمشاهده پروفایل

استاد

• Aerospace System Design
• Computational Fluid Dynamics
• Multi-Disciplinary Optimization
• +۷ مورد دیگر

Prof. Juan Alonso is the Vance D. and Arlene C. Coffman Professor and James & Anna Marie Spilker Chair in the Department of Aeronautics & Astronautics at Stanford University. He directs the Aerospace Design Laboratory (ADL), focusing on high-fidelity computational methods for aerospace system design. His expertise spans transonic/supersonic/hypersonic aircraft, rotorcraft, and launch vehicles. Alumni include record-holding teams for human-powered watercraft and lightweight unmanned aerial vehicles. Education: PhD (1997) from Princeton University in Mechanical & Aerospace Engineering; M.A. (1993) Princeton; B.S. (1991) MIT Aeronautics/Astronautics. Research emphasizes multi-disciplinary optimization, numerical methods, and parallel computing applied to advanced aircraft design, sustainable aviation, and UAS systems. Notable contributions include computational design frameworks like SU2 and SUAVE, and initiatives in curriculum development for engineering education. Recent work focuses on: GPU-accelerated CFD solvers, multi-fidelity surrogate models (e.g., VortexNet), contrail simulation frameworks, and battery degradation modeling for electric aircraft. Active in urban air mobility and high-fidelity trajectory optimization for hypersonic systems. Labs/Teams: Aerospace Design Laboratory (ADL) leading open-source computational tools development. Involved in NASA-funded projects and industry partnerships for advanced propulsion systems.

H. Jane Baeمشاهده پروفایل

استادیار

• Turbulence Modeling
• Computational Fluid Dynamics
• Fluid Mechanics
• +۳ مورد دیگر

H. Jane Bae is an Assistant Professor of Aerospace at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science. Her research focuses on turbulence modeling, particularly developing high-fidelity computational methods to simulate high-Reynolds-number flows for applications in aircraft design, wind farms, and atmospheric predictions. She integrates machine learning, information theory, and numerical techniques to enhance turbulence modeling efficiency. Education: B.S. in Aerospace Engineering from Caltech (2011), Ph.D. in Mechanical Engineering from Stanford University (2018). She joined Caltech in 2021. Research interests include near-wall turbulence dynamics, resolvent analysis, sparse identification of nonlinear dynamics, and reinforcement learning for wall models in LES. Her work addresses computational cost reduction and model accuracy in complex flow simulations. Awards: 2023 Outstanding Referee Award from Physical Review. Teaching includes courses on fluid mechanics (Ae/APh/CE/ME 101 abc) and turbulence (Ae 239 ab). Her lab combines turbulence theory, high-performance computing, and data-driven methods to study unsteady flows over complex surfaces. Notable contributions include machine learning-based wall models and resolvent analysis frameworks for non-stationary flows.

• Fluid Mechanics
• Aeroacoustics
• Computational Fluid Dynamics
• +۳ مورد دیگر

Antonio Alguacil Cabrerizo is an Assistant Professor (starting 2025) at Université de Sherbrooke, where he currently serves as a Postdoctoral Fellow (2023-2025). His academic trajectory includes dual doctoral degrees in Mechanical Engineering from Université de Sherbrooke and École Nationale Supérieure d'Aéronautique et de l'Espace, complemented by aerospace engineering degrees from ENSEEIHT and Universidad Politécnica de Madrid. His research integrates computational fluid dynamics with machine learning, focusing on: Aeroacoustic prediction and noise source identification Deep learning surrogates for fluid and acoustic systems Turbomachinery and airfoil aerodynamics Data-driven modeling of spatiotemporal physical systems This work advances computational efficiency in simulating complex wave propagation, turbulence effects, and fluid-structure interactions. Publication analysis reveals consistent focus on developing neural network-based computational methods for aeroacoustics and fluid dynamics. His 15 most recent works demonstrate progressive refinement in applying convolutional architectures to predict acoustic scattering, refraction phenomena, and turbomachinery noise with increasing physical accuracy and computational efficiency. Awards and recognition include: Top 5 in AIAA Best Student Paper in Aeroacoustics (2024) Graduate Scholarship Award from CFD Society of Canada (2022) Eureka Scholarship from Université de Sherbrooke (2021) Best Poster Prize at CRASH Day (2021) He secured a $70,000 CAD startup grant (2025-2028) from Université de Sherbrooke for establishing his research program. No student advising relationships or laboratory affiliations are currently documented.

• Plasma Physics
• Fluid Dynamics
• Turbulence
• +۴ مورد دیگر

Dr Mahdi Davoodianidalik is a researcher in the Department of Nuclear Physics & Accelerator Applications at the Australian National University (ANU). He is affiliated with the Space plasma power and propulsion group and the Physics of fluids group, focusing on interdisciplinary research at the intersection of plasma physics, fluid dynamics, and space propulsion technologies. His research interests include Turbulence and wave-driven flows Plasma thrusters and electrothermal propulsion Fluctuation-induced forces and interactions Fluid-structure dynamics Thermal engineering of micro-thrusters Nonlinear phenomena in fluids Recent publications highlight his work on analogs of the Casimir effect in turbulent flows, passive propulsion mechanisms, and advanced propulsion systems using solid hydrocarbon propellants. He has contributed to understanding turbulence in both fundamental and applied contexts, with a focus on energy transfer and chaotic flow phenomena. His collaborations span ANU colleagues including Nicolas Francois and Michael Shats, with a strong emphasis on experimental and computational fluid dynamics.

Alexandros Kontogiannisمشاهده پروفایل

پژوهشگر ارشد

• Fluid Dynamics
• Applied Mathematics
• Bayesian Inference
• +۱۰ مورد دیگر

Alexandros Kontogiannis is a research fellow at the University of Cambridge, Department of Engineering, specializing in fluid dynamics and applied mathematics. His work combines Bayesian inference, machine learning, and physics-informed algorithms to solve inverse problems in magnetic resonance velocimetry (MRV) and fluid-structure interaction. EPSRC National Fellow in Fluid Dynamics Member of Energy, Fluids and Turbomachinery Division Research Focus: Development of digital twin frameworks that integrate MRV data with Navier-Stokes equations to reconstruct flowfields, infer rheological parameters in non-Newtonian fluids, and estimate hidden quantities like pressure and wall shear stress. Key innovations include: Physics-informed compressed sensing for sparse MRV data Simultaneous boundary shape and flowfield estimation Bayesian turbulence model parameter learning Scientific Awards: ASME Fluids Engineering Division Graduate Student Scholar (2021) Technical Chamber of Greece (TEE) Award (2018) Limmat Foundation Academic Excellence (2017) Mentzelopoulos Scholarship for international studies (2017) Greek State Scholarships Foundation Award (2012) Key Contributions: Algorithms for 3D flow reconstruction with adaptive discretization, viscous signed distance field regularization, and multi-objective aerodynamic shape optimization. His methodologies enable 27x reductions in MRI scanning time while maintaining diagnostic accuracy.

Seher Ekenمشاهده پروفایل

استادیار

• Thin-Walled Composite Beams
• Aeroelastic Analysis
• Hypervelocity Impact
• +۵ مورد دیگر

Seher Eken is an Assistant Professor in the Department of Aerospace Engineering at Istanbul Technical University. Her research focuses on structural dynamics and aeroelasticity of aerospace systems, specializing in thin-walled composite beams, spacecraft shielding, and hypervelocity impact mechanics. She has led multiple projects on topics like transonic flutter suppression, ballistic armor optimization, and orbital debris mitigation. Key research areas include: Composite material failure under extreme loads Aeroelastic stability of rotating structures Numerical simulation of hypervelocity impacts Dynamic analysis of aircraft wings and turbine blades Active vibration control techniques Her recent work emphasizes spacecraft protection systems, with studies on orbital debris impact dynamics and advanced composite armor design. She has also contributed to launch vehicle instability analysis and swept wing flutter characteristics. Current projects involve 3D-printed turbine blade repair, transonic flutter prediction for unmanned aircraft, and ballistic impact optimization for high-performance fabrics. Notable projects (2022–2025): AB Yeni Nesil İnsansız Savaş Uçakları Aeroelastik Uyarlama (Transonic Flutter Prediction) 3D-Printed Turbine Blade Repair with Sustainability Focus Ballistic Impact Analysis of Fabric Armors Orbital Debris Impact Simulation for Spacecraft Shields Her research integrates computational modeling (CFD, FEA) with experimental validation, focusing on aerospace structural systems under extreme conditions. Collaborations span international partners in composite material development and space debris mitigation strategies.