جستجوی استاد راهنمای دانشگاهی

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.

• Numerical Analysis
• Partial Differential Equations
• Scientific Computing
• +۳ مورد دیگر

Prof. Dr. Willy Dörfler is a full professor at the Institute for Applied and Numerical Mathematics within the Faculty of Mathematics at Karlsruhe Institute of Technology (KIT). He leads the research group on Numerical Methods for Partial Differential Equations and teaches advanced courses including Adaptive Finite Element Methods and Modeling and Simulation of Li-Ion Batteries . His work focuses on numerical analysis, scientific computing, and multi-physics simulations. His research spans Partial differential equations with adaptive discretization Wave propagation and space-time methods Battery modeling with chemo-mechanical coupling Lattice Boltzmann techniques for fluid dynamics Applications in mechanics, optics, and electrochemistry as evidenced by his 15 most recent publications. These works emphasize finite element methods, discontinuous Galerkin approaches, and high-performance computing for complex systems. Contact: willy.doerfler@kit.edu | Office hours: Mondays 14:30–15:30 during lecture periods

Christian Wienersمشاهده پروفایل

استاد

• Scientific Computing
• Numerical Analysis
• Finite Element Methods
• +۶ مورد دیگر

Prof. Dr. Christian Wieners is a faculty member at the Institute for Applied and Numerical Mathematics , part of the Faculty of Mathematics at Karlsruhe Institute of Technology (KIT) . He has held leadership roles, including Head of the KIT Department of Mathematics (2012-2015) and Speaker of the GAMM activity group on numerical methods for PDEs (2010-2017). Academic Rank: Professor Research Focus: Scientific Computing, Discontinuous Galerkin Methods, Multigrid Algorithms, and Applications in Solid Mechanics and Cardiac Modeling His research spans Numerical Analysis , Computational Mechanics , and Biomedical Engineering , with a focus on parallel finite element methods for wave equations, phase-field fracture, and multi-physics cardiac simulations. Recent work includes adaptive space-time DG methods, visco-acoustic inversion, and digital twins for heart modeling. He has served as an Associated Editor for SIAM Journal of Scientific Computing (2008-2013) and a Section Editor for Numerical Analysis in ZAMM. His publications highlight collaborations in Parallel Computing , Visco-Elastic Models , and Nonlocal Plasticity . Prof. Wieners teaches courses like Numerische Mathematik and Grundlagen der Kontinuumsmechanik , with a history of lectures on Scientific Computing , Machine Learning in Mathematics , and Multigrid Methods . His work integrates Mathematical Rigor with Engineering Applications .

Matthias Maischakمشاهده پروفایل

استاد

• Elliptic Boundary Value Problems
• Transmission Problems
• Signorini Problems
• +۱۰ مورد دیگر

Dr Matthias Maischak is a Reader in the Department of Mathematics at Brunel University London within the College of Engineering, Design and Physical Sciences . His research focuses on elliptic boundary value problems , transmission problems , Signorini problems , and variational inequalities , with emphasis on boundary and finite element methods , fast solvers , and adaptive algorithms . He is also a key developer of the MaiProgs software package, which implements advanced numerical techniques for engineering applications. Research Areas : Boundary Element/FEM Methods, Contact Mechanics, Adaptive Algorithms, High-Performance Computing, Retarded Potential Analysis Supervision : Ph.D. and MSc students in computational mathematics, including projects on shape analysis, discontinuous Galerkin methods, and boundary integral equations. Publications span topics like dual-dual formulations , FE-BE coupling , hp-adaptive methods , and error estimation in linear elasticity and acoustic fluid-structure interaction . He has co-authored works on nonlinear interface conditions and time-domain boundary element methods , with applications to microstructure analysis , elastoplastic contact , and singular perturbations .

• Numerical Analysis
• Scientific Computing
• High-Performance Computing
• +۱۳ مورد دیگر

Stefano Berrone is a Full Professor in the Department of Mathematical Sciences "G.L. Lagrange" (DISMA) at the Polytechnic University of Turin, where he also holds key administrative roles as Vice-Rector for Quality and President of the University Quality Assurance Committee. He is a member of the Interdepartmental Center SmartData@PoliTO and the University Committee for Research, Technology Transfer and Services to the Territory. Department of Mathematical Sciences "G.L. Lagrange" (DISMA), Polytechnic University of Turin Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory Scientific leadership in EU, national, and commercial research projects Teaching assignment at Turin Polytechnic University in Tashkent (2012–2014) His research lies at the intersection of numerical analysis, scientific computing, and machine learning, with a strong emphasis on the development and analysis of advanced numerical methods. He specializes in the Virtual Element Method (VEM), mesh adaptivity and generation, high-performance computing (HPC), physics-informed neural networks, and deep learning for engineering problems. His work contributes to computational engineering, data science, and sustainable development (aligned with SDGs 4, 9, and 13). He leads multiple research groups and projects focused on numerical optimization, PDE discretization on polygonal meshes, and simulation of complex physical systems. The recent publications (2023–2025) reveal a strong trend toward hybrid computational methodologies, combining classical numerical techniques like VEM with machine learning, particularly physics-informed and neural-approximated models. There is a clear focus on stabilization-free formulations, mesh optimization, and applications in energetic materials, fluid dynamics, and subsurface modeling. The work spans high-impact journals in scientific computing, computational mechanics, and algorithms. Scientific Participations and Memberships: Full Member, SIAM (Society for Industrial and Applied Mathematics) (2020–present) Full Member, Italian Society of Applied and Industrial Mathematics (2020–present) Full Member, Italian Mathematical Union (2020–present) Full Member, National Institute of Higher Mathematics - National Group for Scientific Computing (1999–present) Research Leadership and Grants: Scientific Responsible, In-Deep (EU Horizon Europe, 2024–2028) Scientific Responsible, PYGEOM (PRIN, 2023–2026) Scientific Director of Structure, SHIMMER (Clean Hydrogen JTI, 2023–2026) Scientific Director of Structure, HPC-Spoke 6 (PNRR, 2022–2025) Scientific Responsible, AdPolyMP (PRIN, 2022–2025) Scientific Responsible, Virtual Element Methods: Analysis and Applications (PRIN, 2019–2022) Scientific Responsible, IDEA (PRIN, 2013–2015) Scientific Responsible, AIRTOLYMI (Regional, 2007–2011) Scientific Responsible, Engine Health Monitoring (Commercial, 2024–2025) Advising and Doctoral Supervision: Supervising multiple PhD students in Pure and Applied Mathematics and Mathematical Sciences Member of Doctoral Colleges in Pure and Applied Mathematics at Politecnico di Torino and University of Turin (2013–2023) Key advisor in research areas including energetic materials, computational fluid dynamics, and numerical PDEs Laboratories and Research Groups: Numerical Analysis and Scientific Computing (DISMA) Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory Lead in developing computational tools like HEMSim for energetic materials simulation

• Computational Fluid Dynamics
• Fluid-Structure Interaction
• Computational Structural Dynamics
• +۱۲ مورد دیگر

Dr.-Ing. Norbert Hosters is a Research Associate and Chief Engineer at the Chair for Computational Analysis of Technical Systems (CATS), Faculty of Mechanical Engineering, RWTH Aachen University. He has been active since 2020 and serves as General Secretary of the German Association for Computational Mechanics (GACM). His work bridges advanced computational methods with engineering applications. His research focuses on numerical methods for fluid-structure interaction , computational fluid and structural dynamics , isogeometric analysis , and aerothermoelasticity . He also explores applied quantum methods and physics-informed neural networks for solving complex PDEs and optimizing industrial processes. His interdisciplinary work spans mechanical, biomedical, and computational engineering. The recent publications (2023–2025) demonstrate a strong trend toward integrating machine learning with traditional simulation techniques, particularly in partitioned FSI , multiphase flow , shape optimization , and biomedical simulations such as LVAD modeling. His work appears in high-impact journals like Scientific Reports , Computers & Fluids , and International Journal for Numerical Methods in Engineering , as well as major conferences including GACM and CMBE. He is actively involved in teaching courses on Numerical Methods for Fluid-Structure Interaction , Isogeometric Analysis , and Simulation Methods in Mechanical Engineering . He offers student projects and supervises research, though no named advisees are listed. He has no listed scientific awards or fellowships. His research is conducted within the CATS chair, a leading group in computational mechanics, contributing to both fundamental methods and industrial applications. He plays a key role in academic service through GACM leadership.

Felipe Gonzalez Cornejoمشاهده پروفایل

پژوهشگر

• Computational Fluid Dynamics
• Numerical Methods
• Additive Manufacturing
• +۴ مورد دیگر

Felipe Gonzalez Cornejo is a Researcher at the Chair for Computational Analysis of Technical Systems (CATS) at RWTH Aachen University, affiliated since 2019 (PhD student until 2023, postdoc thereafter) and a member of NHR4CES's Simulation and Data Lab Fluids since 2023. Education: Bachelor's and Master's in Mechanical Engineering, University of Santiago of Chile (Usach) His research develops numerical methods for extrusion-based additive manufacturing, focusing on Computational Fluid Dynamics (CFD) for free-surface flows and non-Newtonian fluids, stabilized finite-element formulations, adaptive mesh techniques, and moving-domain simulations. He integrates High-Performance Computing (HPC) to model thermofluid flow, phase change, and thermoplastic behavior in Fused Deposition Modeling (FDM). No scientific awards were mentioned. He offers thesis supervision on FDM simulation topics: Multi-filament deposition and porosity estimation Nozzle geometry optimization via model order reduction Mesh-update techniques for moving multi-domain simulations HPC tools including load rebalancing and adaptive mesh refinement He collaborates across CATS work groups: production engineering, fluid-structure interaction, and INTERESST.

Flavio SARTORETTOمشاهده پروفایل

دانشیار

• Numerical Analysis
• Computational Science
• Medical Signal Processing
• +۴ مورد دیگر

Flavio SARTORETTO is an Associate Professor in Scientific Computing at Ca' Foscari University of Venice. He holds a Mathematics degree from the University of Padua and has held academic positions at University of Padua (1982-1992) and Sapienza University of Rome (1992-1993) before joining Ca' Foscari in 1993. His research focuses on numerical analysis, computational methods, and interdisciplinary applications including environmental modeling, cognitive processes, and assistive technologies. Key research areas include numerical solutions of PDEs, meshless methods, EEG signal analysis, and e-learning tools for impaired individuals. He has participated in major research projects such as EC Network (1992-1995), PRIN initiatives (1997-2010), and contributed to software development for geomechanical models and air quality systems. His work spans computational fluid dynamics, robotics applications, and cognitive studies. Recent publications highlight advancements in mesh refinement strategies, robotic assistive devices, and spatial cognition research. He has reviewed for prestigious journals and served in academic committees for state examinations and international conferences. He maintains active involvement in academic service, including roles in evaluation committees and contributions to professional societies like SIAM and CICAP.

• Geographic Information Systems
• 3D Visualization
• Terrain Rendering
• +۵ مورد دیگر

Дејан Д. Ранчић је редовни професор на Електронском факултету у Нишу (Универзитет у Нишу), где је изабран 2015. године након дугогодишњег рада као доцент од 2005. године. Дипломирао, магистрирао и докторирао је на истом факултету у области Електротехника и рачунарство. Његово образовање укључује: Дипломирани инжењер електротехнике и рачунарства (1993) Магистар електротехнике и рачунарства (1997) Доктор електротехнике и рачунарства (2004) Ранчићев истраживачки фокус је на ГИС технологијама , 3D визуелизацији терена и обраги радарских сигнала . Кључни доприноси укључују развој алгоритама за мобилне ГИС апликације, паралелно рендеровање великих терена и радарску обраду података за сузбијање града. Његов рад комбинује теоријску рачунарску геометрију са практичним инжењерским решењима. Анализа његових радова показује еволуцију од радарских система (1997-1999) ка иновативним ГИС решењима (2000-2006), са посебним нагласком на визуелизацију терена и мобилне платформе. Најзначајнији радови објављени су у часописима као што су Computer and Geosciences и WSEAS Transactions on Computers . Тренутно учествује у 3 национална и 1 интернационални истраживачки пројекат, а као рецензент ради за WSEAS серију часописа. Иако детаљи о менторству нису наведени, његова публикацијска активност и пројекти указују на значајну улогу у развоју геопросторних технологија у Србији.

• Computational Fluid Dynamics (CFD)
• Fluid Mechanics
• Biomedical Engineering
• +۴ مورد دیگر

Prof. Cuneyt Sert is a faculty member in the Department of Mechanical Engineering at Middle East Technical University (METU), where he teaches courses such as Fluid Mechanics, Numerical Methods, and Computational Fluid Dynamics (CFD). His academic rank is Professor, reflecting his extensive contributions to research and education. He actively supervises graduate students, including PhD candidate Burcu Ramazanlı, whose work on abdominal aortic aneurysm hemodynamics led to a 2024 publication in the Journal of Thermal Science and Technology. Prof. Sert's research focuses on CFD, fluid dynamics, and biomedical applications. His studies on hemodynamics, turbulence, and material response in aerospace systems have produced influential papers since 2000. He is known for developing innovative numerical methods, such as adaptive discontinuous Galerkin techniques and CUDA-based parallel CFD solvers. His work bridges engineering education and industry, with projects on cryocooler optimization, metro aerodynamics, and grid fin aerodynamics. In teaching, Prof. Sert is praised for his student-centered approach, detailed lecture notes, and rigorous assignments. He emphasizes practical skills like MATLAB and C programming, though some students note concerns about workload and attendance policies. His courses, such as ME 310 (Numerical Methods) and ME 485 (CFD), are recognized for their rigor and real-world relevance. Prof. Sert’s contributions extend to interdisciplinary collaborations, including biomedical acoustics and material science. He has pioneered GPU-accelerated CFD tools and contributed to the design of microchannel heat exchangers. Despite no explicit awards listed, his peer reviews highlight his dedication to fostering critical thinking and problem-solving in students, earning him recognition as one of METU’s most respected educators.

Jan Liedmannمشاهده پروفایل

استاد

• Structural Mechanics
• Finite Element Analysis
• Environmental Mechanics
• +۷ مورد دیگر

Jan Liedmann is a Professor at the Institute for Statics and Dynamics of Aerospace Structures (ISD) within the Faculty 6: Aerospace Engineering and Geodesy at the University of Stuttgart. His research focuses on structural mechanics, dynamics, environmental mechanics, and biomechanics with methodological emphasis on finite element analysis, machine learning integration, and high-performance computing (HPC). He leads projects involving uncertainty quantification, porous media simulation, and methane oxidation studies. Affiliations: DFG Cluster of Excellence SimTech, SPP 1886, SPP 2311, and FOR 5151 HPC Resources: Vulcan cluster, Hawk supercomputer, bwUniCluster 2.0 Key research areas include experimental mechanics, carbon fiber composite durability, and sea ice modeling. Recent work emphasizes physics-informed machine learning and adaptive finite element methods. The ISD operates advanced labs for static/dynamic fatigue testing and biomaterial analysis, supported by institutional GPU servers. His team collaborates with the Alfred Wegener Institute (AWI) on Antarctic projects and participates in EU initiatives like DigiTain for sustainable aerospace design. Recent publications highlight innovations in separable DeepONet architectures and multiphysics modeling frameworks.

Stefan Schimankoمشاهده پروفایل

پژوهشگر

• Numerical Analysis
• Computational Mathematics
• Adaptive Finite Element Methods
• +۴ مورد دیگر

Stefan Schimanko is a Researcher affiliated with the Numerical Research Department at the Faculty of Mathematics and Geoinformation , Vienna University of Technology (TU Wien). His primary focus is on numerical analysis and computational methods for engineering applications, particularly in the areas of adaptive finite element methods (FEM), boundary element methods (BEM), and isogeometric analysis (IGA). He holds a Dipl.-Ing. (engineering diploma), Dr.techn. (doctorate in technical sciences), and BSc degree. His research emphasizes improving computational efficiency and accuracy in adaptive algorithms, with a focus on nonlinear operators, iterative solvers, and optimal complexity analysis. Recent contributions include studies on IGABEM stability in MATLAB, quasi-optimal adaptive algorithms, and preconditioned conjugate gradient (PCG) solvers for BEM. Collaborations with renowned researchers like Dirk Praetorius and Gregor Gantner highlight his active role in advancing adaptive numerical methods. Key achievements include demonstrating the quasi-optimal computational costs of adaptive FEM/BEM and developing localized smoothness control for isogeometric BEM. His work bridges theoretical numerical analysis with practical engineering applications, ensuring methods are both mathematically rigorous and computationally feasible. Education: BSc, Dipl.-Ing., Dr.techn. (Technical Sciences) Labs/Teams: Part of TU Wien's Numerical Research Department and Network Lab projects

Michael Martinمشاهده پروفایل

پژوهشگر

• Computational Fluid Dynamics
• Heat Transfer
• Advanced Manufacturing
• +۳ مورد دیگر

Michael Martin is a nationally recognized expert in National Renewable Energy Laboratory (NREL) , specializing in Computational Fluid Dynamics , Heat Transfer , and Advanced Manufacturing . His work addresses sustainability challenges in areas like green steelmaking and quantum computing energy efficiency. He joined NREL in 2017 and serves as practicum coordinator for the DOE Computational Science Graduate Fellowship and representative in the HPC4EI program . Research interests include: Computational Fluid Dynamics Heat Transfer Optimization Sustainable Computing Advanced Manufacturing Recent publications analyze: Climate change impacts on renewable energy resources Supercritical CO2 flow dynamics Quantum data center thermal parameters Geothermal reservoir machine learning models Scientific awards include: ASME Fellow (2023) Milton Van Dyke Award (2022) New Voices Cohort (2021) Active in professional networks like: American Physical Society AIAA DOE HPC4EI

Hariswaran Sitaramanمشاهده پروفایل

پژوهشگر

• Computational Fluid Dynamics
• Reacting Flows
• Adaptive Mesh Refinement
• +۲ مورد دیگر

Hariswaran Sitaraman is a Researcher IV in the Computational Science Center at the National Renewable Energy Laboratory (NREL), specializing in computational modeling of reacting flows and numerical method development for high-performance computing architectures. His academic background includes: Bachelor of Aerospace Engineering from the Indian Institute of Technology Madras Master of Aerospace Engineering from The University of Texas at Austin PhD in Aerospace Engineering from The University of Texas at Austin Dr. Sitaraman's research centers on multiphase reacting flow simulations for biochemical conversion processes, adaptive mesh refinement algorithms, and continuum-Lagrangian solvers for granular flows. His work bridges computational fluid dynamics, reacting flow physics, and advanced numerical techniques with direct applications in energy decarbonization and sustainable manufacturing. Analysis of his 2025 publications reveals strong emphasis on plasma-assisted combustion for ammonia-air systems, high-fidelity simulation of industrial processes like steelmaking, and adaptive computing frameworks for scale-up challenges. These works demonstrate integration of computational science with energy transition technologies across power generation, transportation, and industrial sectors. Scientific awards: None documented in source material. Advising and grant activities are not specified in the provided information, though his collaborative network indicates active engagement with energy research initiatives. As a core member of NREL's Computational Science Center, Dr. Sitaraman contributes to national efforts in advancing computational methods for next-generation energy systems through high-performance computing infrastructure.

Malte Wincklerمشاهده پروفایل

پژوهشگر ارشد

• Numerical Analysis
• Partial Differential Equations
• Maxwell's Equations
• +۶ مورد دیگر

Dr. Malte Winckler is a research-active academic in the Faculty of Mathematics at the University of Duisburg-Essen, Germany. His work centers on the numerical analysis of partial differential equations with applications in superconductivity and electromagnetic field modeling. His research focuses on numerical analysis of PDEs , particularly Maxwell's equations , variational inequalities , and shape optimization . He applies advanced mathematical techniques to model physical phenomena in type-II superconductors , including Bean's critical-state model and H(curl)-elliptic systems. His methodological expertise lies in finite element methods, adaptive approximation schemes, and optimal control. The recent publications show a consistent focus on developing and analyzing numerical schemes for non-smooth and nonlinear PDEs arising in superconductivity. Key themes include adaptive edge elements , fully discrete approximations , and shape optimization under physical constraints . These works appear in top-tier applied mathematics journals such as SIAM Journal on Numerical Analysis and Computational Optimization and Applications . Dr. Winckler is involved in the DFG SPP 1962 Priority Programme as a contributor to project 22 on non-smooth distributed parameter systems. He teaches courses such as Introduction to Numerical Methods and collaborates closely with Prof. Dr. Irwin Yousept. He has no listed scientific awards in the provided text. He maintains active research profiles on Google Scholar , ResearchGate , ORCID , and GitLab , indicating engagement with the broader scientific community. He advises no students listed in the material and is not indicated as part-time, retired, or former staff.