Find Academic Supervisors

• Wind Energy
• Aerospace Engineering
• Turbulence
• +3 more

Dominic A. von Terzi is a Professor in the Faculty of Aerospace Engineering at Delft University of Technology, specializing in Wind Energy through the TU Delft Wind Energy Institute (DUWIND). His work bridges fundamental fluid dynamics research with practical wind turbine engineering applications, focusing on enhancing operational reliability and performance in challenging environments. His research centers on Wind Energy and Aerospace Engineering, with deep expertise in Turbulence modeling, Large Eddy Simulation, and Wind Turbine Aerodynamics. He investigates critical phenomena including rain erosion on blade leading edges, transonic flow effects at turbine tips, and innovative concepts like floating offshore wind systems and airborne wind energy. His approach combines advanced computational modeling with real-world validation to address industry challenges in turbine durability and energy yield optimization. Recent publications reveal strong trends toward solving operational challenges in extreme conditions (erosion, transonic flow) and system-level innovations (wind-storage integration, airborne energy). These works emphasize computational rigor while exploring frontier concepts like hydrogen production from offshore wind and floating turbine platforms, reflecting a strategic shift toward holistic energy system design beyond standalone turbine optimization. Professor von Terzi chairs the European Research Community on Flow Turbulence and Combustion (ERCOFTAC) and leads research within the EU-funded MERIDIONAL project on multiscale wind farm modeling. He has supervised two students and maintains active industry engagement through media discussions on floating wind technology and grid integration. Embedded within DUWIND's collaborative ecosystem, his work leverages partnerships with institutions like ERCOFTAC and industry stakeholders to advance wind energy technology. Current efforts focus on erosion-safe operational modes, transonic flow management, and scaling airborne wind energy systems, positioning him at the forefront of next-generation wind energy solutions.

• Aerodynamic Unsteadiness
• Road and Racing Car Aerodynamics
• Advanced Wind Tunnel Instrumentation and Analyses

Professor David Sims-Williams is a faculty member at the Department of Engineering within the Faculty of Science at Durham University . His research focuses on Aerodynamic Unsteadiness , Road and Racing Car Aerodynamics , and the Development of Advanced Wind Tunnel Instrumentation and Analyses . He is actively involved in experimental and computational studies of fluid dynamics, vehicle aerodynamics, and aeroacoustic noise. Academic Rank: Professor Research Keywords: Aerodynamics, Fluid Mechanics, Automotive Engineering, Computational Fluid Dynamics, Noise Control His recent work includes studies on flow-induced vibration of polygonal cylinders , piezoelectric actuator integration in wind turbines , and beamforming techniques for noise source localisation . He frequently publishes in journals like SAE International Journal of Passenger Vehicle Systems , Journal of Fluids and Structures , and Physics of Fluids . His collaborations span fluid-structure interactions, transient flow analysis, and automotive noise reduction strategies. He has presented at major conferences including the International Vehicle Aerodynamics Conference , UK Fluids Conference , and SAE World Congress . His methodologies combine large eddy simulations , wind tunnel experiments , and machine learning for flow visualisation .

Shane KeatingView profile

Associate Professor

• Mathematical Oceanography
• Geophysical Fluid Dynamics
• Climate Dynamics
• +4 more

Shane Keating is an Associate Professor at the School of Mathematics & Statistics, University of New South Wales, with a research focus on mathematical oceanography and geophysical fluid dynamics. His work bridges theoretical modeling, numerical simulations, and observational data to study ocean turbulence, mixing, and climate-critical processes. Current role: Senior Lecturer (2017–Present) Previous roles: Lecturer at UNSW (2013–2017), Postdoctoral and Research Scientist positions at New York University's Courant Institute PhD in Physics from University of California San Diego His research interests include: Turbulent mixing and stirring in geophysical flows Ocean state estimation and data assimilation Satellite remote sensing of ocean dynamics Submesoscale ocean eddy interactions Fractal geometry of ocean fronts Geophysical wave energy transfer He leads projects on parameterizing submesoscale processes in climate models, with applications to the East Australian Current. His publications span topics from Southern Ocean eddy dynamics to breaking inception in surface gravity waves. His recent work emphasizes: Stochastic methods for unresolved submesoscale dynamics Quantifying cross-front transport patterns Advanced data assimilation techniques Energy pathways in western boundary currents Contact: s.keating@unsw.edu.au

• Renewable Energy
• Hydrogen Fuel Cells
• Unmanned Aerial Vehicles
• +3 more

Frank Buysschaert is an Assistant Professor at the Department of Mechanical Engineering within the Faculty of Engineering Technology at KU Leuven, based at the Bruges Campus. He heads the Subdivision M-Group Aeronautics, Applied Mechanics and Energy Conversion and serves as contact person for the Applied Mechanics and Energy conversion (TME) unit. He also holds senior academic positions on the Faculty of Engineering Technology Council and Mechanical Engineering Department Council. His research spans renewable energy systems with emphasis on ocean energy conversion, hydrogen fuel cell technology, and unmanned aerial vehicles. Current projects integrate aerodynamics, fluid dynamics, and energy conversion to develop sustainable solutions for defense, offshore wind, and aerospace applications. Key focus areas include hybrid drone systems, PEM fuel cell optimization, and rim-driven thruster hydrodynamics. Recent publications reveal strong interdisciplinary trends connecting hydrogen-powered UAVs, marine propulsion systems, and military water treatment. His work bridges fundamental material science (e.g., proton exchange membrane degradation) with applied engineering (e.g., adjoint-based duct optimization), demonstrating consistent growth in energy conversion and drone technology research. Dr. Buysschaert actively secures major research funding as promotor or co-promotor, with current projects including: Development of a Hybrid Fixed-Wing and Hover Drone System for Long-Range Offshore Wind Inspection (2025-2029) Hydrogen technology for defense energy supply (2022-2026) Performance prediction of fuel cells in UAVs under variable weather (2024-2028) He operates within KU Leuven's M-Group specializing in aeronautics and energy conversion, utilizing advanced facilities like the tomographic Particle Image Velocimetry system. His team collaborates on drone inspection systems, hydrogen propulsion, and marine energy conversion with strong industry and defense sector partnerships.

Pierre BeckView profile

Researcher

• Nonlinear Dynamics
• Machine Learning in Physics
• Computational Modeling
• +3 more

Pierre Beck is a Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering’s Institute of Mechanical Engineering (IGM) and the Emergent Complexity in Physical Systems (ECPS) group. He is also a PhD student in Mechanics at EPFL, currently pursuing his doctoral degree since 2022. BA (Hons) Mathematics, University of Cambridge (2016–2019) MMath, University of Cambridge (2019–2020) PhD Mechanics, EPFL (2022–present) Beck’s research focuses on leveraging data-driven methods to analyze and predict nonlinear dynamical systems, particularly chaotic attractors and periodic orbits. His work bridges machine learning with theoretical physics, aiming to uncover hidden structures in complex physical phenomena through computational modeling. The articles demonstrate expertise in applying deep learning to chaotic systems, topological analysis of attractors, and DSGE economic models. Key interdisciplinary themes include algorithmic innovation, pattern recognition, and mathematical physics, with a strong emphasis on numerical methods and non-existing solutions in dynamical systems. Beck is based in the ECPS group at EPFL, where he contributes to advancing understanding of emergent complexity in physical systems. His office is located in MED 2 2924, and he can be contacted at pierre.beck@epfl.ch.

Gert LubeView profile

Professor

• Numerical Methods for Partial Differential Equations
• Computational Fluid Dynamics
• Turbulence Modeling
• +2 more

Prof. Dr. Gert Lube is a faculty member at the Institute for Numerical and Applied Mathematics (NAM) within the Faculty of Mathematics and Computer Science at Georg-August-University Göttingen. His research focuses on numerical methods for partial differential equations , with emphasis on stabilized finite element methods , turbulence modeling , and magnetohydrodynamics (MHD) . Workshops Organized : Calibration of Viscosity Models for Turbulent Flows (2010), Variational Multiscale Methods (2008), Local Projection Stabilization (2008), BAIL Conferences. His academic contributions include 15+ publications since 2010 on topics like Navier-Stokes simulations , LES/VMS methods , stabilized FEM , and FEM-BEM coupling . Collaborations span institutions like TU Graz, Saarbruecken University, and DLR Göttingen. Key Research Areas : Finite Element Methods, Turbulence Modeling, MHD, Incompressible Flows, Singularly Perturbed Problems, Parallel Computing. Advisees include PhD candidates working on topics such as non-isothermal flows , mass conservation , hybrid RANS/LES , and domain decomposition .

Frédéric GibouView profile

Professor

• Computational Science and Engineering
• Solid Mechanics, Materials & Structures
• Fluid Dynamics, Thermal Sciences & Fluid Mechanics
• +10 more

Frédéric Gibou is a Professor in the Department of Mechanical Engineering, Department of Computer Science, and Department of Mathematics at the University of California, Santa Barbara. He is also a core faculty member in the Computational Science and Engineering program. His academic journey began with a PhD in Applied Mathematics from UCLA, followed by post-doctoral research in the Departments of Mathematics and Computer Science at Stanford University. PhD in Applied Mathematics, UCLA Post-doctoral research, Stanford University (Mathematics and Computer Science) Professor Gibou's research sits at the interface between Applied Mathematics, Computer Science and Engineering Sciences, focusing on the design of high resolution computational methods for large scale computations. His work spans Computational Materials Science, Computational Fluid Dynamics, and Computational Image Analysis. The common thread across these applications is that they involve complex/free boundaries and similar classes of nonlinear partial differential equations. His group develops computational strategies on spatially adaptive grids for massively parallel environments, increasingly incorporating Machine Learning algorithms to solve forward and inverse problems. His research output shows a clear trend toward integrating traditional numerical methods with machine learning approaches, particularly for solving partial differential equations with complex interfaces. The publications reveal a strong focus on developing sharp interface methods, adaptive grid techniques, and novel computational paradigms that can handle multiscale phenomena across various scientific domains. Alfred P. Sloan Fellowship in Mathematics Regent's Junior Faculty Fellowship NSF Mathematical Sciences Postdoctoral Fellowship Robert Sorgenfrey Distinguished Teaching award Professor Gibou leads a multidisciplinary research group called Computational Applied Science Laboratory (CASL), which has strong collaborations with experimentalists at UCSB and worldwide. His group has received substantial funding from various agencies, enabling them to tackle challenging problems in computational science. CASL focuses on designing computational methods on Quad-/Oc-trees grids in the level-set formalism for solving previously intractable problems in science and engineering. The group's work spans Computational Materials Science (including nanostructured polymeric materials and high temperature multicomponent alloys), Computational Fluid Dynamics (including flow over superhydrophobic surfaces, flow in reactive porous media, and multiphase flows), and Computational Image Analysis (including image guided surgery and image segmentation).

Anima AnandkumarView profile

Professor

• Machine Learning
• Artificial Intelligence
• Neural Operators
• +6 more

Anima Anandkumar is the Bren Professor of Computing and Mathematical Sciences at the California Institute of Technology (Caltech). She holds a B.Tech from the Indian Institute of Technology Madras (2004) and a Ph.D. from Cornell University (2009). Her research focuses on AI algorithms , Neural Operators , and Tensor Methods for scientific simulations, particularly in climate modeling, flight control, and biomedical applications. Her recent work includes accelerating scientific simulations with Fourier Neural Operators Quantum Chemistry Modeling Climate Forecasting She has received prestigious honors including the IEEE Fellowship Alfred P. Sloan Fellowship NSF Career Award Industry Fellowships from Microsoft, Google, Facebook, and Adobe and is part of the World Economic Forum's Expert Network. Her lab develops AI methods for 45,000x faster weather forecasting Drone landing in extreme winds Drug discovery and protein modeling Quantum chemistry simulations Surgeon performance assessment Robust control systems

Ergin KOSAView profile

Assistant Professor

• Mechanical Engineering
• Materials Science
• Wear Analysis
• +4 more

Ergin KOSA is an Assistant Professor in the Department of Mechanical Engineering at Beykent University , Faculty of Engineering and Architecture. He has been actively involved in teaching and research since 2017, with a focus on wear analysis, additive manufacturing, and computational fluid dynamics. His academic career includes administrative roles such as Department Head from 2018 to 2020. Doctorate in Mechanical Engineering (Istanbul Technical University, 2016) Master's in Mechanical Engineering (Istanbul Technical University, 2008) Bachelor's in Mechanical Engineering (Istanbul Technical University, 2003) Bachelor's in Civil Engineering (Istanbul Technical University, 2008) Research interests include erosive-abrasive wear modeling , 3D-printed composite optimization , CFD simulations for automotive and energy systems, and MEMS design . Key publications address wear prediction in industrial components, hydrogen production from gasoline reforming, and thermoelectric refrigerator performance. His work frequently appears in journals like Journal of Thermoplastic Composite Materials and European Mechanical Science . Teaching responsibilities encompass courses such as Applied Project Management , Machine Elements , and Manufacturing Technologies for both undergraduate and graduate students. Collaborations include co-authorships with researchers like Meltem Eryildiz, Bekir Yavuzer, and Senol Durmusoglu.

• Aerodynamics
• Wind Turbine Airfoils
• Computational Fluid Dynamics
• +5 more

Shreyas Bidadi is a Researcher III in Computational Science at the National Wind Technology Center , affiliated with the National Renewable Energy Laboratory (NREL) . His work focuses on advanced computational modeling of wind turbine aerodynamics and fluid dynamics. Research Focus: Aerodynamics, Computational Fluid Dynamics (CFD), and vortex-shedding analysis for wind turbines. Key Contributions: Studies on 360-degree angle-of-attack airfoil behavior, mesh requirements for deep-stall simulations, and the ExaWind high-performance computing framework. Collaborations: Active partnerships with institutions and researchers in turbulence modeling, low-Mach-number flows, and renewable energy systems. Dr. Bidadi's research integrates fluid dynamics , turbulence modeling , and high-performance computing to optimize wind energy technologies. His recent publications emphasize accurate simulation of deep-stall aerodynamics and vortex shedding in low-Mach-number regimes.

Martín Hoecker-MartinezView profile

Associate Professor

• Geophysical Fluid Dynamics
• Ocean-Atmosphere Interaction
• Boundary Layer Flows
• +4 more

Martín Hoecker-Martinez is an Associate Professor and Department Chair at the University of Redlands. His research focuses on geophysical fluid dynamics, particularly boundary layer flows and air-sea exchange processes. Education: Ph.D. in Oceanography, Oregon State University M.S. in Applied Physics, California Institute of Technology B.S. in Physics, Harvey Mudd College His work combines field observations , rotating fluid dynamics experiments , and computer modeling to study ocean-atmosphere interactions. Recent publications examine geophysical flows , carbon cycle dynamics , and microbial transport mechanisms . Scientific Awards: Woods Hole Oceanographic Institution Geophysical Fluid Dynamics Fellow (2011) AGU Fall Meeting Outstanding Student Paper (2010) Wayne V. Burt Outstanding Graduate Student (2010) Adjunct Faculty Excellence, Mt San Antonio College (2006-2007) He maintains affiliations with multiple professional societies including the American Geophysical Union and American Physical Society. His group has developed a rotating fluid dynamics laboratory at Redlands for studying geophysical flows.

Vatsal SanjayView profile

Assistant Professor

• Soft Matter Singularities
• Viscous Free-Surface Flows
• Non-Newtonian Fluids
• +3 more

Dr. Vatsal Sanjay is an Assistant Professor at the Department of Physics , Durham University. He leads the Computational Multiphase Physics (CoMPhy) Lab, focusing on fundamental fluid dynamics research with applications in energy, manufacturing, and natural systems. Education: PhD in Physics (University of Twente, 2022) Research Areas: Soft Matter Singularities, Non-Newtonian Flows, Viscous Free-Surface Flows His work explores topological transitions in fluid systems through continuum simulations , collaborative experiments , and theoretical analysis , addressing phenomena like droplet impact , bubble bursting , and sheet fragmentation . Recent studies span microgravity fluid mechanics , viscoelastic jet formation , and mycofluidic transport in fungal networks. Articles reveal interdisciplinary trends combining fluid dynamics , materials science , and applied physics , with subfields spanning from Worthington jet dynamics to yield-stress fluid rupture . His Ammodo Science Fellowship enables research into fungal internal transport systems , bridging physics and biology. Supervision: Mentors PGR student Sam Walker Labs: Founder of CoMPhy Lab (moving to Durham in 2025) Open Science: Advocates code sharing and transparent research practices

Weimin HanView profile

Professor

• Numerical Analysis
• Computational Mechanics
• Variational Inequalities
• +5 more

Weimin Han is a Professor and Collegiate Fellow in the Department of Mathematics at the University of Iowa. He holds additional appointments in the Applied Mathematical & Computational Sciences (AMCS) program and the Iowa Technology Institute. His research focuses on numerical analysis, computational mechanics, and variational/hemivariational inequalities, with applications in fluid and solid mechanics. Han earned his Ph.D. in Mathematics from the University of Maryland (1991), following M.S. (1986) and B.S. (1983) degrees from the Chinese Academy of Sciences and Fudan University, respectively. He has served as Chair of the Department of Mathematics (2020–2022) and Director of AMCS (2007–2019). His honors include Fellow of the American Mathematical Society (2023), Simons Fellow (2012), and recognition as a top scholar in Numerical Analysis by Research.com and ScholarGPS. He has organized conferences like the Midwest Numerical Analysis Day 2024 and serves on editorial boards of journals such as Communications in Nonlinear Science and Numerical Simulation . Han’s research has led to groundbreaking work on nonsmooth problems, including contact mechanics and fluid dynamics governed by variational inequalities. His numerical methods address challenges in engineering and biomedical imaging.

Sheng XuView profile

Associate Professor

• Computational fluid dynamics
• Biological flows
• Supersonic turbulence
• +2 more

Sheng Xu is Associate Professor at Southern Methodist University, specializing in computational fluid mechanics and aerodynamics. He holds a Ph.D. from Cornell University (2002) and previously worked at GE Energy on steam turbine aerodynamics, with postdoctoral research at Cornell and Princeton. Research develops computational methods for biological flows, supersonic turbulence, flow control, and insect/swimmer hydrodynamics. The immersed interface method—a core focus—models solids using singular forces and solves fluid flows with jump conditions. Current applications include dragonfly wing kinematics and particle collision dynamics. Publications in Journal of Computational Physics, SIAM Journal on Scientific Computing, and Journal of Fluid Mechanics address turbulent boundary layers, particle collisions, and biological flight mechanics. Recent work advances interface methods for non-smooth boundaries and manufactured solutions for code validation.

• Fluid dynamics
• Rheology
• Transport phenomena
• +5 more

Michael D. Graham is a Professor of Chemical & Biological Engineering at the University of Wisconsin-Madison, with affiliations in the College of Engineering and Mechanical Engineering. He holds distinguished professorships including the Steenbock Professor of Engineering and Vilas Distinguished Achievement Professorship. Graham earned a PhD from Cornell University (1992) and a BS from the University of Dayton (1986). His research focuses on fluid dynamics, rheology, and transport phenomena across microscale and turbulent flows. Key areas include microorganism locomotion, blood flow dynamics, polymer/surfactant rheology, and turbulence control using machine learning. His work bridges theoretical, computational, and experimental methods to address both fundamental and applied challenges. Recent publications emphasize data-driven modeling of turbulent flows, elastic instabilities, and biological fluid mechanics. Over 30 awards highlight his contributions, including the 2024 Eugene C. Bingham Medal for rheology and the Vannevar Bush Faculty Fellowship (2018). He teaches graduate courses like CBE 620 (Intermediate Transport Phenomena) and supervises thesis research. Graham’s lab develops reduced-order models for turbulence control, leveraging nonlinear dynamics and neural ODEs. His work on sickle cell disease biomechanics and viscoelastic flow instabilities has advanced both engineering and medical applications.