جست‌وجوی استاد و پژوهشگر

Gregor Gassnerمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Numerical Analysis
• High-Performance Computing
• +۷ مورد دیگر

Gregor Gassner is a Professor at the University of Cologne's Mathematical Institute, specializing in numerical methods for fluid dynamics and high-performance computing. He leads research in entropy-stable discontinuous Galerkin (DG) methods, focusing on robust and efficient simulations of multi-scale problems governed by conservation laws. His work includes adaptive algorithms for compressible flows, magnetohydrodynamics (MHD), and oceanography, supported by an ERC Starting Grant targeting 'un-crashable' solvers. Key research areas: Non-linear multi-scale simulations High-order DG methods Entropy stability and robustness Exascale computing (e.g., SCALEXA project) Adaptive mesh refinement Subcell limiting techniques Publications emphasize advancements in DG schemes, split-form discretizations, and applications to aerodynamics, plasma physics, and geophysical flows. His ERC grant aims to unify efficacy and robustness in numerical methods. Grants/Awards: ERC Starting Grant for developing robust numerical solvers. Labs/Teams: Core scientist at the Center for Data and Simulation Science, leading the NumSim group.

Arne Koorsمشاهده پروفایل

پژوهشگر

• Discrete-Event Simulation
• Algorithm Optimization
• Financial Market Modeling
• +۳ مورد دیگر

Arne Koors serves as a scientific Assistant at the Department of Computer Science , University of Hamburg , under the Faculty of Mathematics, Informatics and Natural Sciences (MIN) . His research focuses on discrete-event simulation optimization , financial market modeling , and ERP system integration . He has contributed to 9 Bachelor's and 5 Diplom theses as primary supervisor. Education & Teaching: He teaches courses including Mathematics for Computer Science , Introduction to Computer Science , and Simulation Projects . His teaching spans topics like cryptography, network systems, and simulation seminars. Research Contributions: His work emphasizes performance optimization of simulators, priority queue algorithms, and simulation-ERP system interaction. Notable achievements include a Best Paper Award at ESM 2014 for Analysis by State: An Alternative View on Discrete Event Time Series . Practical Experience: He led project management for 75 manufacturing companies in ERP implementation and developed a globally used sales planning software deployed in 250 firms. His invited talks include presentations on ERP systems in education and sales planning strategies. Key Projects: Development of the DESMO-J simulation framework, integration of financial risk metrics into discrete-event systems, and asynchronous RNG methods for performance enhancement.

Thorsten Ohlمشاهده پروفایل

استاد

• Particle Physics
• High-Energy Physics
• Collider Physics
• +۳ مورد دیگر

Prof. Thorsten Ohl is a Professor at the University of Würzburg's Faculty of Physics and Astronomy, leading the Department of Theoretical Physics II. He is a Principal Investigator in the Research Training Group (RTG) 2994, focusing on particle physics at colliders in the LHC precision era. His work centers on theoretical physics, computational methods, and high-energy collider experiments, particularly involving the WHIZARD event generator framework. His research spans precision measurements, BSM physics, scattering amplitudes, and software development for particle physics simulations. His research interests include quantum field theory, noncommutative standard models, and advanced computational techniques for collider analysis. He contributes to international projects like the FCC-ee and LHC precision experiments. His publications highlight advancements in event generation tools, model implementation, and precision studies of Higgs sectors and vector boson scattering. Prof. Ohl collaborates on RTG 2994's doctoral training and oversees the development of software tools for high-energy physics, emphasizing parallel computing and Monte Carlo methods. His lab integrates theoretical insights with computational innovation to address forefront questions in particle physics.

• Computational Geometry
• Discrete Geometry
• Convex Optimization
• +۶ مورد دیگر

Francisco Criado is a researcher with significant contributions to computational geometry, discrete mathematics, and applied algorithm design. His work spans theoretical and applied domains, including convex optimization, Voronoi diagrams, and geometric modeling in gas dynamics and earthquake decision-making frameworks. Collaborators : Francisco Santos, Sebastian Pokutta, Michael Joswig Key Venues : Discrete & Computational Geometry , Foundations of Computational Mathematics , NeurIPS Research Interests focus on geometric algorithms, polyhedral complexes, and applications of fuzzy logic. His 2025 papers explore convex hulls, zonotopes, and tropical geometry, while earlier works address gas dynamics and decision-making models. Article Trends reveal expertise in high-dimensional geometry, combinatorial optimization, and numerical methods. He frequently employs randomized and linear convergence algorithms in 2022–2025. Advising and Grants : No explicit data provided, but his extensive co-authorship network suggests collaborative research leadership.

Frank Luebeckمشاهده پروفایل

استاد

• Representation Theory of Groups
• Finite Groups of Lie Type
• Reductive Algebraic Groups
• +۳ مورد دیگر

Frank Lübeck is a Professor at RWTH Aachen University's Lehrstuhl D für Mathematik within the Faculty of Mathematics, Computer Science and Natural Sciences. His research focuses on representation theory of groups, particularly finite groups of Lie type and reductive algebraic groups, with an emphasis on computational methods and the development of computer algebra systems like CHEVIE. He has contributed extensively to understanding character tables, tensor product decompositions, and algorithmic approaches to group theory problems. His work includes foundational studies on Brauer trees, constructive recognition of groups, and the analysis of element proportions in finite Lie type groups. Collaborations with researchers like Geck, Hiss, and Malle have led to influential publications in journals such as Journal of Algebra and Archiv der Mathematik . Lübeck’s tools, such as the EDIM package, address computational challenges in linear algebra and group theory. His research bridges theoretical insights with practical algorithmic solutions, impacting both pure and computational mathematics.

Holger Götzمشاهده پروفایل

پژوهشگر

• Granular Matter
• Computational Mechanics
• Metamaterials Design
• +۳ مورد دیگر

Dr. Holger Götz is a Researcher affiliated with Friedrich-Alexander University Erlangen-Nuremberg (FAU), located at Cauerstraße 3, Room 03.140 in Erlangen. His research focuses on granular matter dynamics, computational mechanics, and metamaterials design. Utilizing advanced simulation techniques like the Discrete Element Method (DEM), he investigates phenomena such as granular jamming, elastic membrane interactions, and robotic gripper optimization. Recent work includes studies on structural features of jammed metamaterials and the dynamic response of granular meta-materials. Götz collaborates with institutions like FAU's physics and engineering departments, contributing to interdisciplinary projects in materials science and robotics. Publications Highlights: His 2024 paper in Physical Review Research explores metamaterial structural features, while 2023 contributions to Granular Matter and Mathematics in Computer Science address DEM simulations and software advancements. A 2022 study in Granular Matter demonstrates how soft particles enhance robotic gripper performance through granular jamming principles. Affiliations: Active in FAU's physics and engineering communities, his work intersects computational modeling, material design, and robotics applications. Contactable at holger.goetz@fau.de.

Jens Hartingمشاهده پروفایل

استاد

• Thin Film Dynamics
• Fluid Mechanics
• Materials Science
• +۳ مورد دیگر

Prof. Jens Harting leads the 'Modelling of Thin Films' research group at the Helmholtz-Institut Erlangen-Nürnberg für Erneuerbare Energien (HI ERN). His work focuses on fluid dynamics, thin film behavior, and computational modeling. Key research areas include reactive thin films, microfluidic systems, and nanoscale particle interactions. He has published extensively in top journals like Advanced Materials , Physical Review Letters , and Journal of Fluid Mechanics . Notable contributions include studies on inertial particle migration, bioinspired microswarm robotics, and lattice Boltzmann method optimizations. Current projects explore phase-field simulations for thin film evaporation and energy materials. No awards are explicitly listed, but his work is widely cited in nanotechnology and materials science.

• Decision Procedures
• Model Checking
• Formal Verification
• +۳ مورد دیگر

Marco Muñiz is a postdoctoral researcher at Aalborg University, specializing in formal verification, model checking, and automated theorem proving. His work focuses on the verification of software and real-time systems. Previously, he conducted research at the University of Freiburg, where he earned his Master's thesis in 2009. Muñiz's research interests include decision procedures, hybrid systems analysis, and formal methods for industrial standards compliance. He has contributed to the design of the Hybrid Model Checker SASET and collaborated with the Jahob Verification System for reasoning about tree and list data structures. Research Interests : Decision Procedures, Model Checking, Real-Time Systems, Automated Theorem Proving, Software Verification, Formal Verification of Industrial Systems. Teaching : Lectured on Model Checking at San Pablo University in Peru, and co-organized courses such as Model Checking SS11 and Algorithms Theory at the University of Freiburg. He has also conducted tutorials for software design and analysis in UML. Publications : His work spans formal verification of hybrid and timed automata, with notable contributions to quasi-dependent variables and clock reduction techniques. Recent publications emphasize applications in real-time systems and industrial compliance, showcasing his expertise in bridging theoretical formal methods with practical system validation. Awards : Microsoft Certified Solution Developer (Systems Engineer).

• Numerical Linear Algebra
• Model Order Reduction
• Matrix Equations
• +۵ مورد دیگر

Dr. Jens Saak is a leading researcher and team leader at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. He heads the Computational Methods in Systems and Control Theory research group and has held several leadership positions at the institute since 2010, including Head of the Scientific Computing Team (2010-2020), Head of the Matrix Equations Team (2013-2020), and currently serves as Head of the Data, Infrastructure, Software & Computing Team since 2021. Dr. Saak earned his undergraduate degree in Technomathematik from the University of Bremen (1996-2003), completed his PhD at TU Chemnitz (2003-2009), and held a postdoctoral position there (2009-2010) before joining the Max Planck Institute. His research spans computational mathematics with a focus on large-scale sparse matrix equations , model order reduction , and optimal control of complex systems. He specializes in developing efficient numerical algorithms for Lyapunov and Riccati equations, with applications in mechanical engineering (particularly machine tools), fluid dynamics, and thermal systems. His work bridges theoretical numerical analysis with practical high-performance computing implementations. Analysis of his recent publications reveals a clear trajectory toward energy-efficient computing solutions, sustainable research software practices, and increasingly sophisticated model reduction techniques for complex coupled systems. His work demonstrates a strong emphasis on practical implementations with industrial applications, particularly in mechanical engineering contexts. Dr. Saak has been instrumental in developing and maintaining research software infrastructure, with a growing focus on sustainability and reproducibility in computational science. His leadership extends to collaborative projects across the German mathematical community, particularly in research data management initiatives. His team actively contributes to open-source scientific computing tools, with significant work on the M-M.E.S.S. (Matrix Equations, Sparse Solvers) toolbox, which provides implementations of modern algorithms for matrix equations and model order reduction.

Thomas Zeiserمشاهده پروفایل

پژوهشگر

• High-Performance Computing
• Lattice Boltzmann Methods
• Computational Fluid Dynamics
• +۳ مورد دیگر

Dr. Thomas Zeiser serves as Head of Systems & Services and Chief Operating Officer HPC at NHR@FAU (Center for National High Performance Computing Erlangen) at Friedrich Alexander University Erlangen-Nuremberg. He leads the Systems & Services group of NHR@FAU and HPC4FAU since the end of 2020 and serves as deputy for NHR@FAU in the NHR Betreiberausschuss. His work focuses on transitioning from serving FAU only to national center operations, managing HPC systems, procuring new infrastructure, financial controlling of NHR@FAU's budgets, and supporting planning for a new data center building. Dr. Zeiser's research interests center around High-Performance Computing with specific expertise in Lattice Boltzmann Methods , large-scale simulations, evaluation of HPC hardware and software, and efficient operation of HPC systems. His work bridges the gap between theoretical computational methods and practical implementation in high-performance environments. He has implemented the first job-based job and performance monitoring for RRZE's HPC systems and has extensive experience in procurement of HPC infrastructure. Analysis of Dr. Zeiser's publication record reveals a consistent focus on practical applications of computational methods in HPC environments. His research demonstrates a progression from fundamental lattice Boltzmann method development toward increasingly complex system-level concerns including fault tolerance, performance monitoring, energy efficiency, and scalable implementations. The publications show strong collaboration patterns with researchers at FAU and other German institutions, particularly in the areas of computational fluid dynamics and parallel computing. Dr. Zeiser regularly serves as a reviewer for various journals and compute time commissions of different HPC centers. He is also one of the local organizers for the Ferienakademie of TUM, FAU, and Universität Stuttgart held in Sarntal. His work with NHR@FAU positions him at the forefront of national high-performance computing infrastructure in Germany. At NHR@FAU and RRZE (Regional Computing Center Erlangen), Dr. Zeiser leads teams responsible for operating some of Germany's most powerful academic supercomputing resources. His group plays a critical role in supporting computational research across multiple disciplines at FAU and increasingly at the national level through the NHR initiative.

• Robotics
• Automation Technology
• Mechatronic System Design
• +۳ مورد دیگر

Prof. Dr.-Ing. Tobias Bruckmann holds the Chair of Mechatronics at the University of Duisburg-Essen . His research focuses on robotics , particularly cable-driven parallel robots with applications in logistics , construction , and space systems . He is also involved in automation technology and human-machine interfaces . Key Scientific Activities : Organized multiple international conferences (e.g., CableCon 2019, IFToMM DA-CH 2020) and served as Associate Editor for IEEE robotics conferences. Research Projects : Led EU-funded CableBOT (logistics), DFG projects SEGESTA and ARTIST , and contributed to FAROMIR (home robotics). Recent Publications (2025-2023): Explored cable force calculations, automation in construction, human-robot collaboration, and space robot suspension systems. Collaborations : Worked with institutions in Germany (Fraunhofer IPA, TU Delft), France (INRIA), China (The Chinese University of Hong Kong), and Poland. Email: tobias.bruckmann@uni-due.de

• Database Systems
• Data Mining
• Query Optimization
• +۳ مورد دیگر

Jeffrey F. Naughton is a Professor at the University of Wisconsin and works at Google Inc in Madison, WI, USA. His academic career spans decades with significant contributions to database systems, data mining, and privacy-preserving analytics. Research Interests : Distributed query processing and optimization Machine learning integration with relational databases Differential privacy in data analysis Scalable data warehousing systems Energy-efficient database architectures Temporal data management Article Trends : Over the past decade, Naughton's publications demonstrate a trajectory from foundational database optimization to modern challenges in scalable analytics and privacy-preserving techniques. Key themes include query execution prediction, workload summarization, and system design for big data environments. Scientific Awards : ACM Software System Award (2008) - Recognizing his contributions to database software systems Collaborative Network : He has collaborated with leading researchers including AnHai Doan (entity matching), Somesh Jha (privacy), and Stratis Viglas (query optimization), producing impactful work in SIGMOD, VLDB, and ICDE venues.

• Applied Mathematics
• Optimization
• Computational Mathematics
• +۳ مورد دیگر

Yair Censor is a distinguished Professor in the Department of Mathematics at the University of Haifa. His work focuses on applied mathematics, particularly in optimization, projection methods, and computational algorithms with applications in medical physics and engineering. He has developed foundational techniques like the superiorization method, which balances feasibility-seeking and objective function reduction in iterative algorithms. Research Interests: Optimization theory, convex feasibility problems, superiorization, medical imaging algorithms, and parallel computing. Collaborations: Extensive work with Gabor T. Herman, Aviv Gibali, Reinhard Schulte, and others in computational methods for radiation therapy and tomography. His recent publications (2023–2025) emphasize feasibility-seeking algorithms, superiorization in floorplanning, and perturbation resilience. While no explicit awards or students are listed in the provided text, his contributions to iterative methods and medical physics remain influential.

• Hardware Design
• FPGA Programming
• Parallel Computing
• +۵ مورد دیگر

Satnam Singh is a Professor at Newcastle University's School of Electrical and Electronic Engineering, UK. With a research career spanning over three decades from 1989 to present, Singh has established himself as a leading expert in hardware design, FPGA programming, and parallel computing systems. His research interests focus on hardware-software co-design , reconfigurable computing , and functional programming applications for hardware design. Singh has pioneered work in using functional languages like Haskell for hardware description and verification, particularly through his contributions to the Lava hardware description language. His work bridges theoretical computer science with practical hardware implementation challenges. Analysis of his publication history reveals a clear evolution from early work on formal verification and FPGA design in the 1990s, through substantial contributions to parallel programming models in the 2000s, to more recent applications of machine learning techniques in diverse domains including cheminformatics and sensory systems. His 2022-2025 publications demonstrate continued innovation in specialized processor programming, AI applications for olfactory systems, and health hazard classification using deep learning. Singh has maintained extensive collaborations throughout his career, notably with Krishna R. Pattipati (15 joint publications), Anuradha Kodali (8 publications), and David J. Greaves (5 publications), reflecting his ability to bridge theoretical computer science with practical engineering applications. His work spans multiple prestigious venues including FPGA, FCCM, ICFP, and IEEE Transactions on Systems, Man, and Cybernetics, demonstrating both theoretical depth and practical impact across computer architecture, programming languages, and applied machine learning domains.

Hans-Joachim Bungartzمشاهده پروفایل

استاد

• Scientific Computing
• Fluid Mechanics
• Plasma Physics
• +۴ مورد دیگر

Prof. Hans-Joachim Bungartz is a Full Professor of Scientific Computing at the Technical University of Munich (TUM), leading the Department of Computer Science. He holds the TUM School of Computation, Information and Technology affiliation. His career includes roles at the University of Augsburg and Stuttgart, and he has been at TUM since 2004. He specializes in scientific computing, focusing on numerical algorithms, HPC software, and applications in fluid mechanics, plasma physics, and quantum simulations. Education: Bachelor/Master in Mathematics, Informatics, and Economics (TUM, 1982–1989) PhD (1992) and Habilitation (1998) in Sparse Grids and Numerical Methods (TUM) Research Interests: His work spans adaptive grids, parallel computing frameworks (e.g., Peano), and interdisciplinary applications in computational engineering. He emphasizes bridging modeling, algorithms, and HPC infrastructure. Awards: ISC PRACE Award (2013) Bavarian Habilitation Award (1994) His contributions include over 150 publications and leadership roles in institutions like the Leibniz Supercomputing Center and the TUM Graduate School. Leadership: As Dean of the Informatics Department (since 2013) and Director of the TUM Graduate School, he shapes academic policies. He chairs key national/international bodies like the German Research Network (DFN) Executive Board (2011–2020).