جستجوی استاد راهنمای دانشگاهی

Dominik Schillingerمشاهده پروفایل

استاد

• Numerical Mechanics
• Isogeometric Analysis
• Finite Element Methods
• +۷ مورد دیگر

Prof. Dominik Schillinger (Technische Universität Darmstadt) is a leading expert in numerical mechanics, with 15+ years of academic leadership in computational methods, multiscale modeling, and biomedical applications. His career spans prestigious institutions including Leibniz Universität Hannover and University of Minnesota. W3-Professur für Numerische Mechanik (2021–present) W2-Professur für Numerische Mechanik (2019–2021) Assistant/Associate Professor (2013–2019) Postdoc & PhD (2008–2012) His research focuses on isogeometric analysis , discontinuous Galerkin methods , and multiscale biomedical modeling , with applications in vascular networks, bone mechanics, and additive manufacturing. He pioneered phase-field methods for fracture analysis and physics-informed neural networks for material modeling. Recent publications highlight matrix-free algorithms for compressible flows, physics-augmented lattice optimization , and thermodynamically consistent phase-field models . Awards include the PECASE , ERC Starting Grant , and NSF CAREER award. Presidential Early Career Award (2019) ERC Starting Grant (2017) NSF CAREER Award (2017) ICE Zienkiewicz Medal (2015) He teaches core courses in numerical methods , finite element analysis , and computational mechanics at TU Darmstadt and Leibniz Universität Hannover, with international collaborations in Bethlehem and Austin.

• Condensed Matter Physics
• Nanoscience
• Theoretical Physics
• +۳ مورد دیگر

Prof. Gustavo Miguel Pastor is a Professor of Theoretical Physics (W3) at the University of Kassel, Germany, leading the Theory of Low-Dimensional and Nanostructured Materials group since 2007. His research focuses on condensed matter theory and nanoscale phenomena. His academic credentials include: Master in Physics, Instituto Balseiro, Universidad de Cuyo, Argentina (1984) PhD in Physics, Free University of Berlin, Germany (1989) Habilitation, Université Louis Pasteur, Strasbourg, France (1994) Prof. Pastor's work centers on Condensed Matter Physics and Nanoscience, specializing in magnetism, electronic structure, and low-dimensional systems. He develops advanced theoretical frameworks for strongly correlated electrons and nanostructures, with emphasis on quantum many-body phenomena and magnetic behavior at atomic scales. Analysis of his 2012-2018 publications reveals consistent focus on density functional theory applications, Hubbard model extensions, and magnetic properties of nanomaterials. Key contributions include theories for ultrafast demagnetization mechanisms, spin-density wave configurations, and electric-field manipulation of magnetic anisotropy in transition metal clusters. He actively serves as reviewer and advisor for major international funding bodies including DFG, ANR, EU, ESF, NSF, FWO, DAAD, and AvH. His research group investigates fundamental electronic and magnetic properties of low-dimensional systems through advanced computational modeling.

David Bommesمشاهده پروفایل

استاد

• Computer Graphics
• Geometry Processing
• Mesh Generation
• +۴ مورد دیگر

Prof. Dr. David Bommes is a leading researcher in computer graphics and geometry processing, currently a Professor at the University of Bern . His expertise lies in mesh generation, particularly quadrilateral and hexahedral meshing, numerical optimization, and automatic differentiation techniques. His research focuses on developing robust algorithms for generating high-quality meshes from complex geometries, with applications in CAD, architecture, and simulation. He has made significant contributions to the fields of surface and volume parametrization, directional field synthesis, and geometry processing optimization. Prof. Bommes has received notable recognition, including the Best Paper Award (1st place) at SGP 2022 and the Graphics Replicability Stamp for his work on TinyAD, a lightweight automatic differentiation library for geometry processing. His publications span top-tier venues such as SIGGRAPH, Eurographics, and ACM Transactions on Graphics, covering topics from automatic differentiation and geodesic computation to advanced meshing techniques. He actively collaborates with leading institutions and researchers worldwide.

Yoann Le Hénaffمشاهده پروفایل

پژوهشگر

• Numerical analysis
• Mathematical physics
• Partial differential equations
• +۲ مورد دیگر

Yoann Le Hénaff is a postdoctoral researcher at the Numerical Analysis Department of the University of Tübingen, Germany. He works within the CRC TRR 352's B4 project and collaborates with C. Lubich's group. His research focuses on computational mathematics and physical modeling through numerical analysis. Education: PhD in Mathematics (2024), University of Rennes, France Master's degree in Mathematics, University of Rennes, France Engineering degree in applied mathematics, INSA Rennes, France Research Interests: Specializing in partial differential equations and numerical simulations, Le Hénaff develops grid-free particle methods for the Vlasov-Poisson system and studies modulated soliton solutions for nonlinear Schrödinger equations. Key subfields include spectral concentration problems, Dirac-Frenkel variational principles, and computational complexity optimization. Publication Trends: Recent work demonstrates expertise in hybrid numerical methods combining classical PDE approaches with modern computational techniques. 2023-2025 publications show progression from particle method convergence proofs to advanced soliton-based algorithms and spectral concentration generalizations across multiple dimensions. Collaborations: Actively involved in the CRC TRR 352 consortium, participating in annual retreats and contributing to the B4 project's objectives. Regularly presents at international seminars including the NAG seminar in Tübingen and IRMAR doctoral meetings in Rennes.

• Dynamical Low-Rank Approximation
• Numerical Analysis
• Scientific Computing
• +۳ مورد دیگر

Gianluca Ceruti is a researcher at the Mathematical Institute of Eberhard Karls University of Tübingen. His work focuses on numerical analysis and scientific computing, particularly in dynamical low-rank approximation and tensor networks. He is involved in projects related to wave phenomena and quantum system dynamics. Research Interests: Dynamical low-rank approximation, tensor networks, uncertainty quantification, and numerical methods for differential equations. Key Collaborations: Jonas Kusch, Christian Lubich, Lukas Einkemmer, Martin Frank. His recent publications address stability analysis, rank-adaptive integrators, and time integration of tree tensor networks. Contact: ceruti@na.uni-tuebingen.de .

Dong Anمشاهده پروفایل

استادیار

• Quantum Computing
• Applied Mathematics
• Quantum Algorithms
• +۳ مورد دیگر

Dong An is an Assistant Professor at the Beijing International Center for Mathematical Research (BICMR) , Peking University, since September 2024. He previously held a QuICS Hartree Postdoctoral Fellowship at the University of Maryland (2021-2024). He earned his Ph.D. in Applied Mathematics (2021) from UC Berkeley under Professor Lin Lin and a B.S. in Computational Mathematics (2016) from Peking University. Research Focus: Quantum algorithms for classical scientific computing problems and classical algorithms for quantum many-body problems. Key Areas: Quantum simulation, Hamiltonian dynamics, quantum linear systems, differential equations, and adiabatic quantum computing. Publications highlight advancements in quantum differential equation solvers, linear combinations of Hamiltonian simulations, and multi-product methods with explicit commutator scaling. His work bridges theoretical quantum computing and practical scientific computation, emphasizing optimal parameter dependence and error bounds. Scientific Awards: Co-Principal Investigator of NSF Robust Quantum Simulation Seed Grant QuICS Hartree Fellowship Bernard Friedman Memorial Prize in Applied Mathematics Multiple honors from Peking University Teaching: Currently instructs graduate-level quantum algorithms courses at Peking University. Previously served as a teaching assistant for differential equations and calculus at UC Berkeley. Service: Organizer for workshops on quantum differential equations and SIAM special sessions. Active reviewer for journals like PRX Quantum and conferences including QIP and TQC.

• Computational Mechanics
• Continuum Mechanics
• Material Modeling
• +۳ مورد دیگر

Prof. Dr. Philipp Junker serves as the Executive Director of the Institute of Continuum Mechanics at Leibniz University Hannover within the Faculty of Mechanical Engineering. He also participates in several collaborative research initiatives including Task Group S1: Macro Optical Systems, International RTG 2657: Computational Mechanics Techniques in High Dimensions, and PhoenixD: Photonics, Optics, and Engineering - Innovation Across Disciplines. His work bridges continuum mechanics with computational methods and optical engineering applications. Professor Junker's primary research interests lie in computational mechanics, continuum mechanics, and their applications to material modeling and structural analysis. His work focuses on developing advanced numerical methods including virtual element methods, phase field fracture modeling, and variational formulations for material behavior. He explores applications in diverse areas such as biomedical engineering (dental implants, stents), thermal barrier coatings, and optical systems engineering. His recent publications demonstrate a strong focus on computational efficiency and accuracy in mechanical simulations, with particular emphasis on damage modeling, fatigue analysis, and multi-physics coupling. His research group develops novel numerical frameworks that integrate thermodynamics principles with computational methods to address complex engineering challenges. Professor Junker is actively involved in the academic governance of Leibniz University Hannover as a member of the Senate and as a representative for professors. His leadership role as Executive Director positions him to shape research directions and academic programs within mechanical engineering.

• Nonlinear Optimization
• Numerical Optimization
• Optimization and Control with PDEs
• +۱۲ مورد دیگر

Prof. Dr. Nicolas R. Gauger is Full Professor and Chairholder for Scientific Computing at the University of Kaiserslautern-Landau (RPTU), holding dual appointments in the Department of Mathematics and Department of Computer Science. He directs the university's Computing Center (RHRZ) and leads the SciComp research team, with prior roles at DLR Braunschweig, Humboldt University Berlin, RWTH Aachen University, and MIT. His academic background includes a Master in Mathematics (Dipl.-Math.) from Leibniz University Hannover (1998) and a Ph.D. in Applied Mathematics (Dr.rer.nat.) from Braunschweig University of Technology (2003). 1998-2010: Research Scientist, Numerical Methods for Aerodynamics at DLR Braunschweig 2005-2010: Assistant Professor (W1), Department of Mathematics, Humboldt University Berlin 2010-2014: Associate Professor (W2), RWTH Aachen University 2014: Visiting Professor, Massachusetts Institute of Technology Prof. Gauger's research centers on optimization under uncertainty for complex physical systems. His work integrates Algorithmic Differentiation with Machine Learning to advance Computational Fluid Dynamics, Aeroacoustics, and Structural Mechanics. Recent projects focus on medical applications like proton computed tomography (pCT) for cancer treatment through SIVERT and AI Care initiatives, alongside aerodynamic design for noise reduction and flow control. His 2025 publications reveal a dominant trend in end-to-end differentiable programming for physics-based optimization, particularly in fundamental particle physics experiments and medical imaging. Key subfields include diffusion models for detector design, reinforcement learning for particle tracking, and robust optimization frameworks applied to turbulence modeling and proton therapy. Scientific recognition includes: Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA), 2018 Teaching Award from RPTU, June 2025 He has advised doctoral students including award-winning researcher Max Aehle (2025 Freundeskreis RPTU Outstanding Dissertation Award). Major grants include leadership of the Excellence Initiative-funded AICES Graduate School (2010-2019), the Center for Mathematical and Computational Modelling (CM) 2 (2014-2019), and the MathApp (2019-2024) and MSO (2024-present) research initiatives. Current projects like SIVERT and AI Care apply AI to cancer therapy. Prof. Gauger co-leads the Fraunhofer Performance Center's R&D Lab for Data Analysis and AI, serves on the Managing Board of ERCOFTAC (European Research Community on Flow, Turbulence and Combustion), and chairs the Steering Committee of ERCOFTAC's Special Interest Group on Design Optimization. His team develops critical AD tools including CoDiPack and OpDiLib within the NHR South-West high-performance computing consortium.

Anne Reinarzمشاهده پروفایل

استاد

• Scientific Computing
• High Performance Computing
• Numerical Simulation
• +۵ مورد دیگر

Anne Reinarz is a faculty member at the Chair of Scientific Computing in Computer Science (SCCS) within the Department of Informatics at Technical University of Munich. She is based at the Leibniz Supercomputing Centre in Garching bei München, where she maintains her office at Boltzmannstr. 1 E.2.036. Her research interests center around scientific computing, with specific focus on wave propagation methods, discontinuous Galerkin techniques, and numerical solutions to partial differential equations. Her work aligns with the SCCS mission of advancing algorithmics for scientific and high-performance computing applications. Dr. Reinarz has taught multiple advanced courses including Scientific Computing II, Master-Praktikum on Modern Wave Propagation using Discontinuous Galerkin methods and Julia programming, and seminars on Fundamentals of Wave Simulation. Her teaching reflects the department's emphasis on efficient numerical algorithms and their applications to complex simulation problems. While specific awards and publications aren't detailed in the available information, her involvement in student projects and research activities at one of Europe's leading supercomputing centers indicates significant contributions to the field of computational science.

Ernst-Walter Knappمشاهده پروفایل

استاد

• Computational Chemistry
• Biochemistry
• Molecular Dynamics
• +۴ مورد دیگر

Prof. Dr. Ernst-Walter Knapp is a Chemistry professor at the Free University of Berlin, specializing in Physical & Theoretical Chemistry. His research focuses on computational chemistry, biochemistry, and molecular dynamics, with an emphasis on protein structure, redox potential, and electrostatic modeling. Education: PhD in Computational Chemistry Knapp's lab developed tools like mFES for finite element electrostatics and DOOP for protein structure prediction. His work spans Protein Electrostatics , Redox Potential Analysis , and Cholesterol Transfer Pathways in lysosomal disorders. Key publication trends include 2018 studies on NPC1 protein , 2016 solvation models , and 2015 docking algorithms . His articles frequently address protonation states , electron transfer , and binding energy calculations . Knapp's lab collaborates on interdisciplinary projects in Structural Biology and Theoretical Biophysics , integrating quantum chemistry with experimental data for photosynthesis and metalloprotein research.

Holger Rudolphمشاهده پروفایل

پژوهشگر

• Mechanical Engineering
• Machine Tools
• Structural Analysis
• +۳ مورد دیگر

Holger Rudolph is a research associate at the Fraunhofer Institute for Mechanics of Materials (IWM), specializing in experimental and numerical machine analysis. His work focuses on structural dynamics, thermal modeling, and damping mechanisms in mechanical systems. Research Interests: Rudolph's research spans mechanical engineering and structural analysis, with a focus on numerical modeling, thermal management, and damping behavior in industrial machinery. His expertise includes finite element analysis, elastodynamics, and computer simulation for precision manufacturing applications. Publications Highlights: His recent work (2022-2023) explores adaptive thermal models and structural correction methods for machine tools. Earlier studies (2012-2017) established foundational approaches for damping analysis in mechanical joints and industrial structures.

• Transportation Engineering
• Traffic Flow Modeling
• Numerical Analysis
• +۲ مورد دیگر

Dr. Franziska Theurich serves as a faculty member within the Chair of Traffic Flow Science at Dresden University of Technology (TU Dresden), holding a doctoral degree in natural sciences (Dr. rer. nat.). Based in the Potthoff-Bau building at Hettnerstraße 1, Dresden, she contributes to the university's transportation research infrastructure through teaching and academic leadership. Her institutional role encompasses course instruction and research oversight within this specialized domain. Her research centers on Transportation Engineering and Traffic Flow Modeling, applying advanced mathematical techniques including integral transforms, multivariable calculus, and statistical analysis to traffic dynamics. She develops computational models for urban mobility systems, emphasizing numerical methods to address congestion and infrastructure challenges. This work bridges theoretical mathematics with practical transportation solutions, focusing on data-driven approaches to traffic optimization. The Chair of Traffic Flow Science operates as a dedicated research unit under Dr. Theurich's direction, collaborating with transportation authorities and industry partners. Located in Dresden's academic hub, the chair advances methodologies for traffic simulation and management while training students in quantitative transportation analysis through specialized coursework.

Edoardo Di Napoliمشاهده پروفایل

پژوهشگر

• Numerical Linear Algebra
• Tensor Computations
• Algorithm Optimization
• +۵ مورد دیگر

Edoardo Di Napoli serves as Head of the Simulation and Data Laboratory Quantum Materials at Forschungszentrum Jülich's Jülich Supercomputing Centre (JSC), where he is also a Principal Investigator in Helmholtz Information Program 1 and Joint Lab VMD. His work bridges advanced computational methods with quantum materials research. His research focuses on enabling high-performance large-scale quantum mechanical simulations through interdisciplinary approaches combining numerical linear algebra, tensor computations, and algorithm optimization. Key areas include parallel programming, code development/modernization, and data mining techniques for predicting macroscopic properties of quantum materials. His work specifically targets materials for energy applications. Dr. Di Napoli's scientific contributions center on the intersection of mathematical modeling and computational physics, with emphasis on developing novel simulation methods for quantum systems. His leadership in the SDL Quantum Materials drives methodological innovations for large-scale scientific computing. Awards and Recognition: Fulbright fellowship (1999) enabling graduate studies at University of Texas at Austin VolkswagenStiftung fellowship 'Computational Science' (2011-2013) His career trajectory includes postdoctoral positions at University of North Carolina and Perimeter Institute for Theoretical Physics, renewable energy consulting, and executive management at NetIQ before joining Forschungszentrum Jülich. He previously led the JARA SimLab 'ab initio methods in Quantum Chemistry and Physics' (2013-2016) and was a postdoctoral researcher at AICES graduate school. The Simulation and Data Laboratory Quantum Materials under his direction develops cutting-edge computational approaches for quantum materials research, with strong emphasis on high-performance computing infrastructure and interdisciplinary collaboration across physics, computer science, and materials engineering.

• Mechatronics
• Sensor Technology
• Electrical Engineering
• +۷ مورد دیگر

Kai Haake is a Professor at Saarland University of Applied Sciences, Faculty of Engineering, specializing in Mechatronics and Sensor Technology. He is actively involved in teaching and laboratory development, offering courses in electrical engineering, electronics, sensor technology, and numerical simulation. Research interests include robotics, artificial intelligence, IoT, 3D imaging systems, and electromagnetic field mapping. His work often bridges mechanical and electronic systems. His publications focus on electromagnetic compatibility, sensor integration, and field distribution analysis, with a strong emphasis on industrial applications. He holds multiple patents related to sensor technology and industrial truck systems, though no specific scientific awards are documented.

Estefanía Loayza-Romeroمشاهده پروفایل

پژوهشگر

• PDE-constrained optimization
• Shape Optimization
• Optimization on Manifolds
• +۱ مورد دیگر

Dr. Estefanía Loayza-Romero is a researcher at the Institute for Computational and Applied Mathematics within the Department of Mathematics and Computer Science at the University of Münster. She works in the research group led by Prof. Dr. Benedikt Wirth, contributing to advanced mathematical research in optimization and numerical methods. Her educational background includes: PhD at University of Heidelberg, Germany (2017-2022) M.Sc. at Escuela Politecnica Nacional, Quito, Ecuador (2015-2017) Diploma at Escuela Politecnica Nacional, Quito, Ecuador (2008-2014) Dr. Loayza-Romero's research spans several interconnected areas of applied mathematics with significant theoretical and practical implications: PDE-constrained optimization : Developing sophisticated methods for optimizing systems governed by partial differential equations Shape Optimization : Researching mathematical techniques to optimize geometries for engineering applications Optimization on Manifolds : Exploring optimization algorithms in non-Euclidean spaces with complex geometries Numerical Modeling : Creating computational frameworks to simulate complex physical phenomena Her work contributes to the advancement of mathematical optimization techniques with applications across various scientific and engineering disciplines, particularly in developing more efficient algorithms for solving complex optimization problems involving partial differential equations and geometric constraints.