جست‌وجوی استاد و پژوهشگر

• Structural Dynamics
• Composite Structure Design
• Experimental Modal Analysis
• +۵ مورد دیگر

Bekir Bediz is an Associate Professor at Sabanci University , Faculty of Engineering and Natural Sciences, with a focus on structural dynamics and multi-scale manufacturing processes. He holds a Ph.D. in Mechanical Engineering from Carnegie Mellon University (2014) and earlier degrees from Middle East Technical University (B.S. 2006, M.S. 2009). Education: Ph.D., Mechanical Engineering, Carnegie Mellon University (2014) M.Sc., Mechanical Engineering, Middle East Technical University (2009) B.S., Mechanical Engineering, Middle East Technical University (2006) Academic Positions: Associate Professor, Sabanci University (2023–present) Assistant Professor, Sabanci University (2016–2023) Instructor, Middle East Technical University (2015–2016) Post-doctoral Researcher, Carnegie Mellon University (2015) Research Interests include high-fidelity dynamic modeling of complex structures, variable stiffness composite design, experimental modal analysis, mechanical micromachining, and vibration energy harvesting systems. His work integrates spectral Chebyshev methods with lamination parameters to optimize composite panels and develop novel manufacturing techniques for micro-devices. Recent Publications highlight advancements in: Active magnetic bearing spindle design for micro-milling Manufacturable variable stiffness composite laminates Particle damper integration in additive manufacturing Microneedle array fabrication for localized drug delivery Nonlinear vibration analysis of rotating functionally graded beams Scientific Awards include multiple TUBITAK grants for projects on: Multi-objective optimization of stiffened composite panels (TUBITAK 1001, 2023–2026) Ultra-high-speed spindle design (TUBITAK 1002, 2023–2024) Variable stiffness composite manufacturing (TUBITAK 1005, 2020–2022) Research Group includes Ph.D. and M.Sc. students working on composite optimization, microneedle design, and spindle dynamics. His projects often involve collaborations with institutions like Koc University, Istanbul Technical University, and Hacettepe University.

Peter Eberhardمشاهده پروفایل

استاد

• Multibody Systems
• Mechatronics and Control
• Optimization
• +۳ مورد دیگر

Peter Eberhard is a Full Professor (C4/W3) and Director of the Institute of Engineering and Computational Mechanics at the University of Stuttgart, previously known as Institute B of Mechanics until 2005. He leads a research team of ~35 members and has been active in technical dynamics for over 30 years. Born : March 15, 1966, Stuttgart Education : Dipl.-Ing. in Mechanical Engineering (1991), Dr.-Ing. (1996), Dr.-Ing. habil. (2000), all from University of Stuttgart Leadership : Dean of Studies 'Mechatronics' (2002-2006), Coordinator of DFG Priority Programme SPP1897 (2016-present) Research Interests span multiple domains: Multibody Systems: vibrations analysis, model order reduction, damage recognition via machine learning, flexible gear drives, brake systems, delay-differential equations Mechatronics: control systems for maglev trains, predictive driving safety, 6DOF driving simulators Optimization: distributed algorithms, robotics applications, particle swarm methods Robotics: serial/parallel robots, swarm localization, force-controlled manipulators Biomechanics: hearing mechanics, implants/prostheses Meshless Methods: discrete element modeling, fluid-structure interaction Scientific Contributions : Authored/Co-authored 57+ doctoral theses Co-edited Springer book series 'Lecture Notes Applied and Computational Mechanics' Founded SimTech Excellence Cluster (2007) Organized major conferences: IUTAM Symposium (2006), IMSD Conference (2012)

• Smoothed Particle Hydrodynamics (SPH)
• Fluid-Structure Interaction (FSI)
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Xiangyu Hu, Dr.-Ing. habil., is a researcher at the Chair of Aerodynamics and Fluid Mechanics at Technische Universität München (TUM). Based at the TUMWAER facility in Garching bei München, their work focuses on advanced computational methods in fluid dynamics and solid mechanics using smoothed particle hydrodynamics (SPH). Research Focus: SPH methodology development, fluid-structure interaction (FSI), multi-phase flows, numerical stability, and GPU-accelerated simulations Recent publications demonstrate a strong emphasis on solving complex fluid dynamics problems through SPH method enhancements, including: Multi-resolution and multi-physics SPH frameworks Deep reinforcement learning integration for dynamic optimization Novel approaches to hourglass instability and consistency correction Applications to wave energy conversion and elastic tank sloshing suppression Their work combines theoretical advancements with practical implementations in the SPHinXsys library, addressing challenges in both incompressible and compressible flow simulations.

René Kahawitaمشاهده پروفایل

استاد

• Hydraulic Engineering
• Fluid Mechanics
• Numerical Simulation
• +۴ مورد دیگر

René Kahawita is a Full Professor at the Department of Civil, Geological and Mining Engineering at Polytechnique Montréal . Holding a Ph.D. from Colorado State University, his research focuses on hydraulic engineering , fluid mechanics , and numerical simulation of water flow systems. His academic journey includes a B.Sc. from Imperial College , an M.Sc.A. from Waterloo , and a Ph.D. from Colorado State . As a member of the Experimental and Digital Water Flow Engineering Group (GENIE EAU) , he has supervised 16 graduate theses (6 Ph.D. and 10 Master's) on topics ranging from dam breach modeling to pollutant transport in porous media . Research Themes : Hydraulic modeling of rivers and estuaries Numerical simulation of fluid dynamics Air/water pollution dispersion analysis Heat transfer in environmental systems Computational methods for floodplain simulation Dam failure and breach formation The 15 most recent publications (1977-2019) demonstrate sustained expertise across fluid mechanics , environmental pollution , and computational hydraulics . Key methodologies include Godunov schemes , SPH techniques , and finite-volume methods .

• Computational Fluid Dynamics
• Hydrodynamics
• Fluid Structure Interaction
• +۴ مورد دیگر

David LE TOUZÉ is a Professor of Fluid Mechanics and Director of the Research Laboratory in Hydrodynamics, Energetics & Atmospheric Environment (LHEEA) at Centrale Nantes. His research focuses on advanced computational methods in fluid dynamics, particularly Smoothed Particle Hydrodynamics (SPH) and its applications to ocean engineering, wave-structure interactions, and multiphase flows. Research Interests: Prof. LE TOUZÉ's work spans: Development of high-fidelity SPH algorithms for complex fluid-structure interactions Hydrodynamic modeling of offshore structures and wave energy converters Numerical wave tanks and experimental validation techniques Multi-scale coupling methodologies (SPH-FEM, SPH-FV) Free-surface flows and multiphase systems Publication Focus: His recent publications demonstrate strong emphasis on: 1) SPH methodology enhancements for industrial applications, 2) Experimental-computational synergy in marine hydrodynamics, and 3) Novel approaches to modeling fluid-elastic systems. Dominant themes include wave-structure interactions, particle method optimizations, and marine renewable energy applications. Laboratory Leadership: Directs the LHEEA laboratory, coordinating research in hydrodynamic systems, atmospheric environment studies, and marine renewable energy technologies through the MÉLUHSINE IIHNÉ research group.

• Machine Learning
• Model Order Reduction
• Quantum Computing
• +۷ مورد دیگر

Prof. Wenxiao Pan is a Professor of Mechanical Engineering at the University of Wisconsin-Madison. Her interdisciplinary research bridges mechanical engineering, applied mathematics, and scientific computing, focusing on numerical methods for complex fluids, soft matter, and solid materials. She holds a BS and MS in Mechanical Engineering from Peking University, and a PhD in Applied Mathematics from Brown University. Education: PhD 2010, Brown University MS 2007, Brown University MS 2003, Peking University, China BS 2000, Peking University, China Research Interests: Machine Learning-enhanced Modeling Data-driven Model Order Reduction Quantum Computing Applications Complex Fluid Dynamics Energy Storage Systems Manufacturing Optimization Recent Research Trends: Prof. Pan’s work emphasizes scalable numerical methods and AI-driven simulations for materials design. Her recent publications highlight advancements in graph neural networks for particulate systems, quantum topology optimization, and phonon dynamics in nanomaterials. Awards: 2024 Vilas Associate Award 2017 R&D 100 Award (Carbon Capture Initiative) 2014 Pacific Northwest Lab Exceptional Contribution Award Advising & Grants: Active in mentoring graduate students and leading projects in energy storage and materials modeling. Her research group operates from https://pan.labs.wisc.edu/ .

Benjamin Zwickمشاهده پروفایل

پژوهشگر ارشد

• Computational Biophysics
• Biomedical Engineering
• Medical Image Analysis
• +۵ مورد دیگر

Benjamin Zwick is a Research Fellow in the School of Engineering at The University of Western Australia (UWA), specializing in computational biomechanics and biomedical engineering. His research focuses on applying computational methods to address challenges in neurosurgery, epilepsy, brain cancer, and cardiovascular disease. He holds a BEng(Hons) and PhD from UWA, with industry experience in engineering design. His work emphasizes open science, developing tools like SlicerCBM (for brain biomechanical analysis) and MVox (medical image voxelization). Key projects include brain shift correction using physics-informed neural networks and computational models for tumor resection planning. He has secured grants such as the WA Near-miss Awards for epilepsy surgery planning and neurosurgical applications of machine learning. Zwick teaches courses in biomechanics, cardiovascular biomechanics, and numerical methods at UWA. His expertise spans computational fluid dynamics, finite element analysis, and high-performance computing. Collaborations include teams at Harvard, MIT, and Stanford, with software contributions to platforms like 3D Slicer and GitLab repositories.

• Applied Mathematics
• Computational Science
• Plasma Physics
• +۷ مورد دیگر

Giovanni Samaey is a Professor of Applied Mathematics and Mathematical Engineering at KU Leuven's Faculty of Engineering Science. He leads research in computational and multiscale methods, focusing on plasma edge modeling for nuclear fusion reactors, Bayesian inversion, and Monte Carlo algorithms. Appointed in 2011, he currently supervises ten PhD students and has held a five-year membership in the Young Academy. His work bridges academic research with societal impact, co-founding Platform Wiskunde Vlaanderen to strengthen mathematics in Flanders. Education: Graduated in Computer Science (specializing in applied mathematics) from KU Leuven (1996), completed a PhD in 2001 under Prof. Dirk Roose, supported by an NFWO fellowship. He transitioned from engineering studies due to a passion for mathematics' societal impact, initially avoiding academia but ultimately embracing teaching and research. Research Interests: Development of numerical methods for multiscale phenomena, including micro-macro acceleration algorithms, multilevel Monte Carlo techniques, and hybrid fluid-kinetic models. His work addresses challenges in plasma physics, fusion energy systems, and inverse problems. Key contributions include the X-Factor book (with Joos Vandewalle) promoting mathematics outreach and advancing computational tools for plasma edge simulations. Awards/Honors: Member of the Young Academy (2016-2021), NFWO Aspirant Fellowship (2001-2002). His efforts in STEM advocacy and mathematics promotion through Platform Wiskunde Vlaanderen highlight his dedication to education and public engagement. Advising & Leadership: Supervises a team of PhD students in applied mathematics and computational science. Active in curriculum development and interdisciplinary collaborations, particularly in fusion energy modeling. His research group contributes to codes like EMC3-EIRENE for plasma edge simulations. Labs/Teams: Leads projects in multiscale numerical methods and plasma simulation within KU Leuven's engineering faculty. Collaborates internationally on fusion reactor modeling and Monte Carlo algorithm design, emphasizing computational efficiency and scalability.

Renato Vacondioمشاهده پروفایل

استادیار

• Computational Fluid Dynamics
• Flood Risk Management
• Numerical Modeling
• +۷ مورد دیگر

Renato Vacondio is an Assistant Professor (RTD-b) in the Department of Engineering and Architecture at the University of Parma, where he also obtained his PhD in Civil Engineering. His work focuses on advanced numerical modeling for flood risk management, particularly using meshless Lagrangian methods such as Smoothed Particle Hydrodynamics (SPH). His research interests lie at the intersection of computational fluid dynamics , flood risk modeling , and hydraulic infrastructure protection . He develops and applies SPH-based solvers (SPHysics, DualSPHysics) to simulate rapidly varying free-surface flows, contributing significantly to both academic and industrial applications. He is deeply involved in the international SPH community through the SPHERIC Steering Committee and as editor of the SPHERIC newsletter. The recent publications reflect a strong trend toward high-fidelity simulation of flood events , integration of data-driven forecasting models , and development of advanced numerical schemes for non-hydrostatic and shallow water flows. His work increasingly emphasizes real-time applications and infrastructure resilience. Scientific Awards: SIR (Scientific Independence of young Researchers) Research Fellow (2014) Research Leadership and Supervision: Dr. Vacondio has served as Principal Investigator on multiple competitive research projects, including PARFLOOD (MIUR-SIR, €383k), PGRA (€1.1M), and Andritz-SPH (€102k), with total funding exceeding €1.4 million. He has supervised PhD students and postdoctoral researchers across projects such as PARFLOOD and RESILIENCE. He is also a member of the academic board of the PhD school in Civil Engineering and Architecture at the University of Parma. Professional Affiliations and Editorial Roles: He is a member of the SPHERIC Steering Committee and has served as Guest Editor for a special issue on SPH methods in Computers & Fluids . He has delivered invited keynotes at international institutions including Imperial College London and the University of Stuttgart.

Duncan Bormanمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Multiphase Flow
• Mathematical Modelling
• +۷ مورد دیگر

Dr Duncan Borman is an Associate Professor at the School of Civil Engineering, University of Leeds . His expertise spans Computational Fluid Dynamics (CFD) , mathematical modeling , and multiphase flow with applications in environmental, energy, and industrial systems. Active in multidisciplinary research across the University, UK, and internationally Programme Leader for Civil and Structural Engineering undergraduate programme Faculty of Engineering Digital and Blended Learning Champion Research Interests : Dr Borman focuses on modeling complex multiphase flows involving chemical/biological processes (e.g., bioreactors, fuel cells, combustion) and moving boundaries (e.g., air-water interfaces, crystallization). His work combines in-house numerical code development with commercial solvers. Key projects: Algal growth/wastewater modeling for energy efficiency Crystallization of actinide salts using impinging droplets Alternative fuel combustion modeling for aviation emissions Development of SPH/meshless methods for inverse problems Collaborations : Works with the cross-faculty Centre for Computational Fluid Dynamics and the Institute for Public Health and Environmental Engineering (IPHEE). Engaged in PEM/SOFC fuel cell research with experimental facilities. Education Initiatives : Leads the ESTEEM1 project for interactive engineering mathematics education and chairs the Faculty of Engineering's Blended Learning committee. Scientific Awards : EPSRC Research Internship EPSRC and National Nuclear Laboratory funding University of Leeds Education Fellowship

• Computer Communications
• Fluid Modeling
• Parallel Computing
• +۵ مورد دیگر

Miloš Ivanović serves as an Assistant Professor at the Institute of Mathematics and Informatics within the Faculty of Natural Sciences and Mathematics at the University of Kragujevac. His academic career is deeply rooted in computer science and computational mathematics, with research spanning multiple interdisciplinary domains that bridge theoretical computer science with practical applications in engineering, physics, and biology. Dr. Ivanović earned his Doctorate in Computer Science from the Faculty of Natural Sciences and Mathematics (PMF) at the University of Kragujevac, establishing a foundation for his subsequent research career focused on computational methods and high-performance computing. His research interests represent a sophisticated convergence of computational theory and practical applications. Ivanović specializes in advanced computing paradigms including grid computing, GPGPU computing, and cloud-based high-performance computing systems. His work in fluid modeling employs meshless methods and particle dynamics approaches, particularly SPH and DPD techniques applied to microfluidic systems. The breadth of his research extends from theoretical mathematics (graph theory and chemical indices) to practical applications in hydrology, biomedical engineering, and nuclear physics. His interdisciplinary approach enables innovative solutions across diverse scientific domains that require intensive computational resources. The collection of his publications reveals a consistent trajectory of research focused on computational methods with applications spanning multiple scientific disciplines. His work demonstrates strong expertise in parallel computing architectures and their application to complex scientific problems. The publications show a progression from fundamental computational mathematics toward increasingly complex multi-domain applications, particularly in biomedical and environmental systems. His research consistently addresses the challenge of implementing computationally intensive methods on distributed and parallel architectures to solve real-world scientific problems. Throughout his career, Ivanović has participated in numerous national and European research and infrastructure projects, including FP6, FP7, and Tempus initiatives. His collaborative approach is evident in the diverse range of co-authors spanning multiple institutions and disciplines, reflecting his ability to bridge computational science with domain-specific applications. Dr. Ivanović is affiliated with the Group for Mathematical Modeling and Computer Simulations, which develops computational solutions across various domains including fluid dynamics, biomedical applications, and environmental modeling. The group's work encompasses software development for simulation purposes, as evidenced by projects like the SPH07 software package and various specialized simulation tools for engineering and biomedical applications.

Kürsat Yurtمشاهده پروفایل

پژوهشگر ارشد

• High Performance Computing
• Performance Portable Programming
• Rotor and Wake Aerodynamics
• +۳ مورد دیگر

Kürsat Yurt, M.Sc., serves as a Research Associate at the Institute for Rotorcraft and Vertical Flight, Technical University of Munich (TUM), based at Boltzmannstr. 15, 85748 Garching, Germany. His role encompasses advanced computational research in vertical flight systems, thesis supervision, and participation in multiple national and international projects targeting next-generation rotorcraft technologies and urban air mobility solutions. Yurt's research spans High Performance Computing, Performance Portable Programming, Rotor and Wake Aerodynamics, and Aeroelasticity. He develops GPU-accelerated meshless methods for large eddy simulations, creates real-time guidance algorithms for urban obstacle avoidance, and investigates morphing airfoil dynamics through fluid-structure interaction frameworks. His work bridges computational mechanics with practical rotorcraft design challenges, emphasizing energy efficiency and flight safety in complex environments. His 2022-2025 publications reveal a cohesive trajectory in computational rotorcraft aerodynamics, featuring innovations in meshless GPU simulations, partitioned coupling techniques, and urban air mobility guidance systems. These works integrate computational fluid dynamics, high-performance computing, and aerospace engineering to address vertical flight challenges including wake modeling, morphing rotor blades, and rotor-airframe interactions. Yurt actively supervises Master's and Bachelor's theses on vortex particle methods, rotorcraft simulation frameworks, and morphing rotor technologies. His research is funded through key projects: ENGEL - Energy Efficient Flight Guidance VARI-SPEED II ARCTIS LaBouR complemented by completed initiatives like InteReSt II and TEMA-UAV. The Institute provides critical infrastructure for his work through specialized facilities: Whirl Tower for rotor dynamics testing Flight Simulator Facilities for pilot-in-loop studies Unmanned Rotorcraft Testbed (AREA) High-performance GPU/CPU clusters for computational workloads These resources enable experimental validation of his computational models and support the institute's mission in vertical flight innovation.