جست‌وجوی استاد و پژوهشگر

• Fluid Dynamics
• Blood Flow Simulation
• Mesh Generation
• +۷ مورد دیگر

Dr. Igor Sazonov is a Senior Lecturer in Aerospace Engineering at Swansea University, affiliated with the School of Aerospace, Civil, Electrical and Mechanical Engineering. His expertise spans fluid dynamics, blood flow simulation, mesh generation, geophysics, and acoustics. He has contributed extensively to computational biomechanics, particularly in cardiovascular systems and viral infection dynamics. His research integrates mathematical modeling with clinical applications, including the development of predictive tools for cardiovascular diseases and infectious disease control. Dr. Sazonov teaches modules such as EG-335 Gas Dynamics, EGA215 Rocket and Space Technology, and EGA321 Satellite Systems. His work bridges engineering and medicine, focusing on digital twin technologies, AI-driven diagnostics, and numerical methods for biomedical systems. Notably, his recent studies address airborne transmission dynamics and SARS-CoV-2 intracellular kinetics, reflecting a commitment to addressing global health challenges through interdisciplinary innovation. His research has been published in high-impact journals like Biomechanics and Modeling in Mechanobiology and Viruses , emphasizing computational fluid dynamics, stochastic modeling, and machine learning applications. Collaborative projects with institutions like the Morgan Advanced Studies Institute (MASI) highlight his role in advancing Swansea University’s research impact in engineering and healthcare.

• Dynamical Systems Theory
• Fluid Turbulence
• Flow Instability
• +۲ مورد دیگر

Dr. Davide Lasagna is an Associate Professor in the Department of Aeronautics and Astronautics at the University of Southampton. His primary research focuses on applying dynamical systems theory to fluid turbulence, with specific interests in flow instability, optimization and control, and model order reduction. He has received funding from the UK's Engineering and Physical Research Council (EPSRC) and the USA's Air Force Office of Scientific Research (AFOSR). Current Research Projects: The shadow of turbulence: algorithms and applications; Sensitivity of Turbulence using Recurrent Flows Collaborations: Bharath Ganapathisubramani, Zheng-Tong Xie, Andrea Da Ronch His work spans theoretical and applied fluid mechanics, with recent publications on chaotic systems, wake flows, and urban aerodynamics. He also coordinates Year 1 and 2 of the Aero & Astro Engineering Programme and teaches courses in engineering design, flight mechanics, and data-driven fluid mechanics.

Francis Ogokeمشاهده پروفایل

استادیار

• Artificial Intelligence
• Deep Learning
• Physics-Informed Machine Learning
• +۷ مورد دیگر

Francis Ogoke is an incoming Assistant Professor in the Department of Mechanical Engineering at Carnegie Mellon University, set to begin in Fall 2025. He is currently a postdoctoral associate at the Massachusetts Institute of Technology. His academic journey includes a Ph.D. in Mechanical Engineering from Carnegie Mellon University (2024) and a B.S.E. in Chemical and Biological Engineering from Princeton University (2019). His research lies at the intersection of artificial intelligence and engineering systems, with a focus on developing foundational AI methods for complex engineering problems. Key areas include: Physics-informed deep learning Uncertainty quantification and probabilistic modeling Representation learning for generalization Applications in additive manufacturing, digital twins, and cyber-physical systems The recent articles reflect a strong trend in leveraging deep learning—especially vision transformers, generative models, and reinforcement learning—for accelerating simulations, enhancing in-situ monitoring, and improving control in additive manufacturing. His work consistently bridges AI innovation with real-world engineering challenges, particularly in metal 3D printing and multiphysics modeling. Notable scientific awards include: Presidential Fellowship in the College of Engineering, Carnegie Mellon University G.E.M. Fellowship Francis Ogoke advises emerging researchers and is expected to lead a research group focused on AI-driven engineering systems. His lab will likely focus on developing intelligent frameworks for digital twins and autonomous manufacturing. He has not yet advised any students as per current records. He is actively involved in pioneering research that integrates AI into core engineering workflows, supported by advanced computational and experimental infrastructure. He is affiliated with the College of Engineering at Carnegie Mellon University and conducts research relevant to advanced manufacturing, sensing technologies, and intelligent systems.

Radu Cimpeanuمشاهده پروفایل

دانشیار

• Fluid Mechanics
• Microfluidics
• Computational Fluid Dynamics
• +۷ مورد دیگر

Radu Cimpeanu is an Associate Professor (Reader) at the Warwick Mathematics Institute, University of Warwick, and holds honorary/visiting roles at Imperial College London and the University of Oxford. His research focuses on fluid mechanics, microfluidics, computational acoustics, and industrial mathematics. He leads the Warwick Fluid Dynamics Research Centre and participates in national initiatives like the UK Fluids Network and the KE Hub. His work bridges theoretical, numerical, and experimental approaches, with applications in aerospace, biomedical engineering, and industrial optimization. He actively collaborates with international groups and industry partners, contributing to innovations in fluid control, interfacial dynamics, and high-performance computing. Education: PhD in Mathematics from Imperial College London (pre-2017). Prior roles include Hooke Research Fellow at Oxford (2017-2019). His research has advanced methodologies for drop impact dynamics, electrohydrodynamic control, and laminar flow modeling. He maintains strong ties with Imperial College through honorary affiliations and co-supervision of students. Key areas of current research include high-speed fluid-structure interactions, feedback control for liquid films, and computational acoustics. He frequently participates in international conferences and has organized workshops on multiphase flows and optimal control. His work emphasizes practical industrial applications, such as optimizing port terminal operations and developing medical devices.

Charbel Farhatمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Fluid-Structure Interaction
• Structural Mechanics
• +۷ مورد دیگر

Charbel Farhat is the Vivian Church Hoff Professor of Aircraft Structures and Professor of Aeronautics and Astronautics at Stanford University's School of Engineering. He chairs the Department of Aeronautics and Astronautics and has led significant initiatives such as the Stanford-King Abdulaziz City for Science and Technology Center. His research focuses on computational methods for multiphysics problems in aerospace engineering, including fluid-structure interaction, digital twinning, and uncertainty quantification. Farhat has authored over 650 publications and holds prestigious awards like the Vannevar Bush Faculty Fellowship and multiple honorary doctorates. Education: Ph.D. in Civil Engineering, University of California, Berkeley (1987) MS in Electrical Engineering and Computer Sciences, UC Berkeley (1986) MS in Structural Engineering, UC Berkeley (1984) MS in Applied Mechanics, Université de Paris VI (1983) Engineering Diploma, Ecole Centrale des Arts et Manufactures (1983) Research Interests: Farhat's work emphasizes advanced computational algorithms for aerospace systems, including autonomous carrier landing dynamics, hypersonic trajectory analysis, and physics-based machine learning. His group develops high-performance software for digital twinning and model reduction techniques to address complex engineering challenges. Recent efforts include supersonic parachute dynamics modeling and probabilistic learning frameworks for uncertainty quantification. Awards & Recognition: Member of National Academy of Engineering (U.S.), Royal Academy of Engineering (UK), and Lebanese Academy of Sciences Fellowships from AIAA, ASME, SIAM, and multiple computational mechanics societies Recipient of the Gordon Bell Prize, John von Neumann Medal, and Gauss-Newton Medal Advising & Grants: Farhat supervises doctoral and master's students in advanced computational methods. His research is funded by NSF, AFOSR, ONR, NASA, and industry partners like Boeing and Lockheed-Martin. He advises on national boards and editorial roles for journals like the International Journal for Numerical Methods in Engineering. Labs & Teams: Leads the Farhat Research Group (FRG) at Stanford, focusing on Simulation-Based Engineering Science. Collaborates internationally on projects like the Army High Performance Computing Research Center and the Stanford-King Abdulaziz Center.

Alexander Wrayمشاهده پروفایل

مدرس

• Fluid Dynamics
• Hydrodynamics
• Low-Order Modelling
• +۱۲ مورد دیگر

Dr. Alexander Wray is a Lecturer in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. His research focuses on the low-order modeling of multiphysics continuum systems, particularly in hydrodynamics, droplet dynamics, and free-surface flows. He actively leads and collaborates on multiple research projects involving droplet evaporation, thick film instabilities, and electrostatic control of interfacial phenomena. His research interests include: Low-order modeling of thick liquid layers with inertia Dynamics of evaporating droplets (including non-circular and splitting drops) Suppression of the coffee-ring effect using electric fields Electrohydrodynamic instabilities in coating and falling films Asymptotic and analytical methods for fluid flow modeling The recent publications highlight a strong trend in applying high-order asymptotic and reduced-order models to complex interfacial flows, particularly involving droplets and thick films under external fields. His work bridges applied mathematics, fluid mechanics, and industrial applications such as OLED manufacturing. He frequently publishes in high-impact journals like Physical Review E , Journal of Fluid Mechanics , and SIAM Journal on Applied Mathematics . Scientific contributions and recognition: Principal Investigator on multiple funded projects including 'Multidrop Manufacturing Methods' and 'Making droplet analysis real-world ready' Co-investigator on several Doctoral Training Partnerships (Maths DTP) at Strathclyde He supervises a number of PhD students and has mentored several postdoctoral researchers. His work involves close collaboration with leading researchers such as Stephen K. Wilson, D.T. Papageorgiou, and O.K. Matar. He is involved in both theoretical modeling and practical applications, particularly in industrial contexts involving droplet-based manufacturing. His research group focuses on developing predictive, computationally efficient models for complex fluid systems.

Casey Harwoodمشاهده پروفایل

دانشیار

• Experimental fluid dynamics
• Fluid-structure interactions
• Lifting surfaces and propellers
• +۵ مورد دیگر

Casey Harwood is an Associate Professor in the Department of Mechanical Engineering at the University of Iowa's College of Engineering, and an Associate Faculty Research Engineer at IIHR—Hydroscience and Engineering. He specializes in experimental fluid dynamics, fluid-structure interactions, and multi-phase flow phenomena. His research focuses on hydroelastic responses of lifting surfaces, ventilation in flows, and advanced modeling techniques. Harwood holds a PhD in Naval Architecture and Marine Engineering from the University of Michigan (2016), an MSe from the same university (2014), and a BS from The Webb Institute (2011). He leads the Marine Science and Technology (MaST) Lab, which explores naval engineering challenges and fluid dynamics applications. His research trends emphasize multi-phase flow dynamics, including cavitation, ventilation, and hydrofoil performance in complex environments. Recent work addresses amphibious vehicle dynamics in surf zones and data-driven modeling for underwater vehicles. He also contributes to engineering education, designing curricula and digital tools for naval science and foundry science education. Notable collaborations include IIHR—Hydroscience and Engineering. His lab focuses on experimental setups and numerical methods for real-time fluid dynamics analysis.

Frank Lagorمشاهده پروفایل

دانشیار

• Estimation and Control for Autonomous Systems
• Fluid Dynamics
• Aerospace Engineering
• +۳ مورد دیگر

Frank Lagor is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia. He joined UVA in 2023 after serving as faculty at the State University of New York at Buffalo. His research focuses on estimation and control for autonomous systems interacting with fluid environments, including gust mitigation in aerospace systems and bio-inspired flow sensing for robotics. Dr. Lagor holds a Ph.D. in Aerospace Engineering from the University of Maryland (2017), with prior degrees from the University of Pennsylvania (M.S., 2009) and Villanova University (B.S., 2006). Before academia, he worked at Lockheed Martin as a Certified Principal Engineer for satellite solar array systems. His research interests emphasize unsteady flow estimation, optimal maneuver design in gust encounters, and reduced-order modeling techniques. Key contributions include sensor placement strategies for data-driven flow estimation and closed-loop control methodologies for autonomous underwater vehicles. He has received prestigious awards including the AFOSR Young Investigator Award (2021) and UB SEAS Early Career Teacher of the Year (2020). Courses taught include advanced control systems theory, dynamics, and stochastic estimation methods.

Alex Ferrer Ferreمشاهده پروفایل

دانشیار

• Materials Design
• Aeronautical Engineering
• Computational Mechanics
• +۴ مورد دیگر

Àlex Ferrer Ferre is a Serra-Hunter Associate Professor at the Department of Physics, Universitat Politècnica de Catalunya (UPC) in Barcelona, and an associate researcher at the International Center for Numerical Methods in Engineering (CIMNE). His research focuses on topology optimization, computational mechanics, and advanced material design. He holds a PhD in Computational Mechanics from UPC (2017) and has conducted postdoctoral research at the University of Oxford and École Polytechnique. Key roles include teaching courses like Flight Mechanics and leading the Swan project for topology optimization software. His work integrates academic and industrial collaborations with entities like ESA and INEGI. Research interests span multiscale design, topology optimization for additive manufacturing, and fracture mechanics. Major projects include the TopSat CubeSat chassis project (ESA-funded) and the Flexion project on flexible material design. Awards include the Marie Curie Fellowship (2019) and an Excellent Cum Laude PhD. His labs and teams collaborate globally, emphasizing open-source tools and collaborative research.

George Vossenمشاهده پروفایل

استاد

• Optimal Control
• Partial Differential Equations
• Numerical Methods
• +۴ مورد دیگر

George Vossen serves as Professor of Applied Mathematics and Computer-Aided Simulation at the Department of Engineering and Computer Science, Niederrhein University of Applied Sciences. He holds the administrative position of Chairman of the University Examination Board and teaches core mathematics courses including Mathematik 1 and 2 for bachelor programs, Numerische Methoden for master programs, and Angewandte Mathematik - Optimierung as an elective. His office is located in room B 410 with consultation hours by email appointment. Professor Vossen's research focuses on optimal control theory for partial differential equations with industrial applications. His work develops mathematical models for laser cutting processes to minimize surface roughness and stabilize melt flow boundaries, optimizes charging protocols for lithium-ion batteries using electro-chemical models, and advances model reduction techniques for complex systems. He has made significant contributions to switching time optimization in bang-bang control and proper orthogonal decomposition methods for parabolic control problems. His publication record from 2010-2018 demonstrates consistent interdisciplinary work bridging mathematics with engineering challenges. The research shows strong thematic continuity in developing numerical methods for real-world optimal control problems, with applications spanning laser technology, energy systems, and biomedical engineering. His collaborative approach is evident through numerous co-authored publications addressing practical industrial constraints.

Narakorn Srinilمشاهده پروفایل

دانشیار

• Fluid-Structure Interaction
• Flow-Induced Vibrations
• Offshore Engineering
• +۳ مورد دیگر

Dr. Narakorn Srinil is an Associate Professor in Subsea Engineering at the School of Engineering, Newcastle University. He leads the FlexNARA research team focusing on Fluid-Flexible Structure Interactions for offshore infrastructure. His work bridges offshore oil & gas and renewable energy sectors, emphasizing predictive modeling of ocean current, wave, and ice loads. Reader/Associate Professor in Subsea Engineering, Newcastle University (since 2022) PhD Supervision in projects like 'Renewable Energy from Natural Flow Phenomena' (2021-2025) EPSRC Grant Holder for CableDyn (2022-2025) and MUFFINS (2018-2022) Royal Society & NSFC Awardee for High-Fidelity Modeling of Flow-Induced Vibrations (2019-2022) Research spans flow-induced vibrations (VIV, MFIV, IIV, WCIV) in offshore/maritime engineering, energy transition systems, and carbon capture pipelines. Key methodologies include phenomenological models, CFD simulations, and experimental validations in circulating water flumes. Recent publications analyze vortex-induced vibrations in S-shaped risers, turbulence characteristics in pulsatile flows, and AI-driven multiphase flow predictions. Awards include British Council Eco-NICE (2024-2026), EPSRC CableDyn (2022-2025), and Royal Society collaborations. Teaching involves advanced modules: MAR8052 - Dynamics of Subsea Installations , MAR8069 - Renewable Marine Structures , and MAR8011 - Offshore Installation Dynamics . Supervised over 50 MSc theses on topics like slug flow FIV, pipeline fatigue analysis, and hybrid riser systems.

Riccardo Rivaمشاهده پروفایل

پژوهشگر

• Wind Turbine Engineering
• Aeroelastic Stability
• Structural Analysis
• +۳ مورد دیگر

Riccardo Riva is a Special Consultant at the Department of Wind and Energy Systems at the Technical University of Denmark , specializing in wind turbine engineering and aeroelastic stability analysis. His work focuses on combining high-fidelity numerical modeling with machine learning for wind farm optimization, structural response prediction, and control system development. Key research areas: Wind turbine structural dynamics, surrogate modeling, and data-driven control systems Active supervisor in 4 PhD projects (2024-2027) related to wind farm co-design and structural modeling Recent publications address uncertainty propagation, vortex-induced vibrations, and multi-fidelity modeling approaches His research contributes to UN Sustainable Development Goals 7 (Affordable Energy) and 9 (Infrastructure Innovation). Current projects emphasize digital twin technology and floating offshore wind farm optimization.

Søren Juhl Andersenمشاهده پروفایل

دانشیار

• Wind Turbine Engineering
• Computational Fluid Dynamics
• Large Eddy Simulation
• +۳ مورد دیگر

Søren Juhl Andersen is an Associate Professor at the Department of Wind and Energy Systems Flows Wind Turbine Design Division, Technical University of Denmark (DTU). His research focuses on wind turbine wake dynamics, computational fluid dynamics (CFD), and energy systems optimization. Education : Not explicitly mentioned in provided texts Research Interests : Dr. Andersen specializes in wind turbine aerodynamics, turbulence dynamics, and data-driven flow control. His work explores Large Eddy Simulation (LES) for wind farm modeling, Proper Orthogonal Decomposition (POD) for wake characterization, and machine learning applications in wind energy optimization. Article Trends : Recent publications emphasize wake steering uncertainty, turbulence integral scales, and reduced-order modeling. Key themes include wind farm control strategies, lidar-assisted flow estimation, and cross-code validation of simulation tools. Projects : He leads initiatives like Train2Wind (2020–2024) and supervises PhD projects on machine learning surrogates, non-equilibrium turbulence dynamics, and wake entrainment studies. Conferences : Presented at Wake Conference (2025), TORQUE (2024), and FarmConners (2020)

David Chelidzeمشاهده پروفایل

استاد

• Nonlinear Vibrations
• Structural Health Monitoring
• Dynamical Systems
• +۳ مورد دیگر

Professor David Chelidze is a faculty member in the Mechanical, Industrial and Systems Engineering department at the University of Rhode Island . His research spans nonlinear vibrations, structural health monitoring, and fatigue evolution in engineered systems. He is the director of the Nonlinear Dynamics Laboratory , where he explores topics like modal testing, dynamical systems theory, and damage prognosis. Education: Ph.D., Engineering Science and Mechanics, Pennsylvania State University, 2000 M.S., Mechanical Engineering, Southern Illinois University, 1995 Diploma in Mechanical Engineering, Georgian Technical University, 1992 Research Interests focus on nonlinear dynamics, particularly vibration-based structural health monitoring, smooth mode decomposition for modal analysis, and phase space warping for fatigue damage detection. His work bridges theoretical advancements with practical applications in materials science, offshore engineering, and biomedical diagnostics. Publication Trends emphasize fatigue life estimation under variable loading, nonlinear model reduction techniques, and vortex-induced vibration analysis. Key subfields include 3D printing structural integrity , biomechanical fatigue monitoring , and hydrodynamic stability of flexible cylinders . Scientific Awards: NSF Career Award, 2009 U.S. Patent: General Method for Tracking Hidden Damage in Machinery Components (with Cusumano J, Chatterjee A), 2003 Grants include projects funded by the RI Commerce Corporation (2022) and collaborative efforts with the University of Connecticut/Office of Naval Research (2021). His lab also engages in digital twinning and physics-informed reduced-order modeling . Laboratory : The Nonlinear Dynamics Laboratory at URI develops tools for damage diagnosis in engineered, geophysical, and biological systems. The lab contributes to software like Smooth Mode Decomposition and Geometry-informed Phase Space Warping , with applications in fatigue monitoring and nonlinear system identification.

• Mechanics
• Rotordynamics
• Biomedical Engineering
• +۴ مورد دیگر

Katrin Ellermann is a University Professor (Professor) at the Institute of Mechanics , Graz University of Technology (TU Graz), Austria. Her research spans rotordynamics , nonlinear vibrations , biomedical engineering (particularly aortic dissection modeling), and offshore systems . She has developed advanced numerical methods like the Numerical Assembly Technique and applied fractional derivative damping models to rotor systems. Her work integrates computational mechanics with applications in industrial machinery and cardiovascular diagnostics via impedance cardiography. Her research interests include: Stability and vibration analysis of mechanical systems Computational modeling of aortic dissection and thrombosis Application of polynomial chaos expansion and sensitivity analysis Control systems using Kalman filters and mechatronic simulations Nonlinear dynamics in offshore structures Advanced damping models via fractional calculus Recent publications focus on rotordynamics (balancing techniques, damping models) and biomedical simulations (SynthAorta dataset, false lumen thrombosis). She has also contributed to fault detection in railway and offshore systems.