جست‌وجوی استاد و پژوهشگر

• Behavioral Economics
• Experimental Economics
• Applied Microeconometrics
• +۵ مورد دیگر

Prof. Dr. Thomas Dohmen is a Professor of Applied Microeconomics at the Department of Economics, Universität Bonn, and holds a professorship in Education and the Labour Market at Maastricht University. He also serves as a Research Professor at DIW Berlin and a Research Fellow at IZA. His research focuses on behavioral and experimental economics, applied microeconometrics, and the formation of cognitive/non-cognitive skills. Key affiliations include the Institute for Applied Microeconomics (IAME) and the Research Centre for Education and the Labour Market (ROA). Education: M.A. and Ph.D. from Maastricht University, MSc from the University of Warwick. His work spans topics like risk preferences, labor market dynamics, and organizational economics, with publications in top journals such as the American Economic Review and Science. Research highlights include studies on testosterone's impact on competitiveness, the role of patience in economic development, and cross-country analyses of non-cognitive skill formation. Awards include the Leading House Best Paper Award and the 2013 SOEP Prize. He advises on policy and serves on scientific boards, including the Human Capital and Economic Opportunity Global Working Group (HCEO). His work bridges microeconomic theory with empirical applications, emphasizing experimental and survey-based methodologies.

• Graph Theory
• Combinatorics
• Algorithmic Problem Solving
• +۲ مورد دیگر

Felix Joos leads the Theoretical Computer Science and Discrete Mathematics research group at Heidelberg University. His research examines graphs and hypergraphs through algorithmic, extremal, and structural lenses, incorporating probability theory methods. Currently serving as Vice Dean of the Faculty for Mathematics and Computer Science. Key research areas: Combinatorial optimization Random graph structures Discrete probability applications Structural graph theory Significant recognition includes: European Prize in Combinatorics (2023) Lauterschläger Prize for Young Researchers (2020) DFG Emmy Noether grant (2019) Prior academic positions include professorships at Hamburg University and postdoctoral research at University of Birmingham. Research contributions advance fundamental combinatorial methods with applications in computer science and discrete mathematics.

• Discrete Optimization
• Convex Geometry
• Mathematical Optimization
• +۳ مورد دیگر

René Brandenberg is a Senior Lecturer at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. His research focuses on Discrete Optimization, Convex Geometry, and Mathematical Optimization, with notable contributions to geometric inequalities, containment problems, and algorithm design. He has extensively supervised theses addressing topics like energy system optimization, linear programming applications, and geometric algorithms. His teaching responsibilities include courses such as Linear Algebra for Engineering students and advanced seminars on topics like Convex Optimization. He has co-advised numerous theses, collaborating with researchers like Peter Gritzmann and Michael Ritter. His work bridges theoretical advancements with practical applications in logistics, energy systems, and computational geometry. Brandenberg’s research group participates in initiatives like the TUM-ICL Mathematical Sciences Hub and contributes to interdisciplinary projects, including optimization models for power markets and algorithmic solutions for geometric containment. His publications reflect a deep engagement with foundational problems in computational geometry and optimization theory.

• Geometry
• Mathematical Visualization
• Linear Algebra
• +۳ مورد دیگر

Vanessa Landgraf is a Lecturer at the Technical University of Munich's Chair of Geometry and Visualization (Prof. Richter-Gebert). She specializes in Mathematics Education, Geometry, and interactive learning environments. Her roles include teaching Linear Algebra and Analysis courses, supervising tutor trainings, and bridging school and university mathematics through outreach programs like the 'Schulportal' and 'TUM-Entdeckerinnen'. She holds a PhD in Multimedia Mathematics Education and a Diplom in K-Homology. Research interests span symmetry, educational storytelling (e.g., her children's book 'Der kleine Mathe-Engel OHO'), and developing interactive tools for mathematical learning. She has contributed to academic works on matroid theory and pedagogical frameworks. Her teaching focuses on fostering mathematical understanding through innovative methods.

Christoph Pflaumمشاهده پروفایل

استاد

• simulation of airships
• computational optics
• high performance computing
• +۲ مورد دیگر

Prof. Christoph Pflaum holds the position of Professor of Computational Engineering at the University of Erlangen-Nürnberg's Department of Computer Science. His academic journey includes a PhD (1996) and Habilitation (1999) from Technical University Munich and University of Würzburg, respectively. His research focuses on computational optics, high-performance computing, numerical analysis, and multigrid methods, with applications in laser simulation and energy-efficient systems. Education : 1992: Diploma in Mathematics, Technical University Munich 1996: Dr. rer. nat., Technical University Munich 1999: Habilitation, University of Würzburg Research Interests : PDE solvers on sparse grids, laser dynamics (thermal lensing, solid-state amplifiers), computational fluid dynamics for airships, and optical system optimization. His work bridges theoretical numerical methods with industrial applications in photonics and renewable energy. Key Contributions : Developed simulation tools for high-power lasers and solar cells, including LASCAD and FDFD methods. Advances in multigrid algorithms and finite element analysis for complex optical systems. Teaching : Courses in theoretical computer science, scientific computing, and computational optics, emphasizing practical implementation using advanced numerical libraries and HPC. Grants & Projects : Led research on laser systems optimization (Innonet SOL), solar cell simulations (Photonics Europe), and high-performance computing initiatives (Par-EXPDE project).

• Quantum Algorithms for Optimization Problems
• Quantum Software-Hardware Co-Design
• Quantum Error Correction
• +۲ مورد دیگر

Lilly Palackal is a Researcher and External PhD candidate at the Technical University of Munich (TUM) School of CIT, affiliated with the Department of Computer Science. She collaborates closely with Infineon Technologies AG on quantum computing research. Her work focuses on quantum algorithms for optimization problems, co-design of quantum software/hardware, and quantum error correction/mitigation. Education: BSc (2018) and MSc (2021) in Mathematics from TUM, with thesis topics in quantum error correction and interactive quantum communication. Current PhD research bridges academic and industrial quantum computing challenges. Research interests include developing quantum solutions for logistics (e.g., vehicle routing), optimization (e.g., knapsack problems), and hardware-aware algorithm design. She supervises multiple student projects across mathematics, physics, and engineering disciplines at TUM and partner institutions. Recent publications explore hybrid quantum-classical methods, QAOA applications, and efficient algorithm encodings for quantum systems. Her work emphasizes practical implementations of quantum technologies in real-world scenarios.

• Numerical Analysis
• Computational Fluid Dynamics
• Partial Differential Equations
• +۳ مورد دیگر

Aleksey Sikstel is a part-time faculty member at RWTH Aachen University , holding the title of Vertr.-Prof. (Part-Time Lecturer). His research focuses on advanced numerical methods for hyperbolic conservation laws, including Discontinuous Galerkin schemes, stochastic Galerkin formulations, and error estimation techniques. Key research areas: Numerical Analysis, Computational Fluid Dynamics, and Applied Mathematics Primary affiliation: Faculty 10 Institutions at RWTH Aachen University Contact: aleksey.sikstel@rwth-aachen.de His work emphasizes coupling hyperbolic systems, entropy-stable discretizations, and adaptive grid methods. Recent publications analyze Baer-Nunziato-type models, multiresolution strategies, and boundary control for hyperbolic equations.

• Aerothermodynamics
• Rarefied Gas Dynamics
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Dr. Georgii Oblapenko is a postdoctoral researcher at the Aerodynamics Center (ACOM), RWTH Aachen University, since November 2023. He has held postdoctoral positions at the German Aerospace Center (DLR) Institute of Aerodynamics and Flow Technology (2021–2023) and the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin (2018–2021). Earlier, he worked as a research engineer at Saint-Petersburg State University's Department of Hydroaeromechanics (2013–2017). His research focuses on mathematical modeling of continuum and rarefied gas flows with thermochemical non-equilibrium, particle-based simulation methods (DSMC, DVM), and uncertainty quantification in aerothermodynamics. He has contributed to the development of advanced kinetic theory approaches for vibrational relaxation, chemical reactions, and transport coefficients in high-temperature flows. Notable achievements include a personal fellowship from the Alexander von Humboldt Foundation (2021–2023) and collaborations with institutions like the University of Texas at Austin and DLR. His teaching activities include instructing Math I and Math II at RWTH Aachen. Scientific Awards: Alexander von Humboldt Foundation Fellowship. His work spans aerothermodynamics, plasma physics, and computational methods, with recent publications addressing entropy-stable simulations, vibrational non-equilibrium effects, and hybrid particle-continuum modeling.

Stefan Guerickeمشاهده پروفایل

استاد

• Data Science
• Business Intelligence
• Operations Research
• +۳ مورد دیگر

Stefan Guericke is a Professor of Business Informatics at the University of Applied Sciences Osnabrück since 2022, specializing in Data Science and Business Intelligence. He holds a PhD in Decision Support & Operations Research from the University of Paderborn (2014) and a degree in Business Informatics from the University of Paderborn and Beijing Institute of Technology. His professional experience includes roles at A.P. Møller-Mærsk, where he served as Senior Engineering Manager and Senior Data Scientist, focusing on logistics optimization and data-driven solutions. Research interests span logistics network design, mathematical optimization, containerization problems, and the application of advanced analytics in microservices architectures. He has contributed to solving complex problems in liner shipping, cargo allocation, and fleet deployment through both heuristic and exact methods. His work bridges academic research and industrial applications, emphasizing practical solutions for supply chain challenges. Teaching responsibilities include courses on Data Science fundamentals, Deep Learning, Operations Research, and Statistics. He is affiliated with the Faculty of Management, Culture, and Technology at HSO, contributing to interdisciplinary projects and student mentoring.

Paul W. Thurnerمشاهده پروفایل

استاد

• Political Science
• Conflict Studies
• Electoral Systems
• +۳ مورد دیگر

Prof. Dr. Paul W. Thurner is a Professor of Political Science at Ludwig-Maximilians-University (LMU) Munich, holding the Chair for Empirical Political Research and Policy Analysis. He is affiliated with the Department of Political Science within the Faculty of Social Sciences. His research focuses on intrastate conflicts, electoral processes, discrete choice modeling, and global armament policies. Notably, he received the LMU Teaching Innovation Award (2013) for collaborative projects integrating statistical and political science methodologies, including a large-scale exit polling initiative during the 2013 Bavarian elections involving over 70 students and 13,000 interviews. Teaching: Offers courses on empirical conflict analysis, advanced statistical modeling, electoral research, and international policy. Recent courses include 'Causes and Consequences of Intrastate Conflicts' and 'Advanced Discrete Choice Modelling.' Research Projects: Leads seminars on applied survey and electoral research, with a focus on hybrid models combining individual and aggregate data for forecasting. Collaborates with institutions like the Statistical Office of Munich and Infratest dimap. Awards: His 2013 Teaching Innovation Award recognized interdisciplinary pedagogical innovation, blending academic rigor with practical fieldwork. Current research emphasizes methodological advancements in political analysis and policy evaluation.

Florian Meinfelderمشاهده پروفایل

مدرس

• Data Analysis with Missing Values
• Data Fusion
• Statistical Methodology
• +۵ مورد دیگر

Dr. Florian Meinfelder is a Lecturer for Special Tasks and Coordinator of the Master's Program in Survey Statistics at the University of Bamberg's Department of Statistics and Econometrics. He holds a PhD in Statistics from the Otto-Friedrich University of Bamberg (2009) and previously worked in middle management at GfK SE, leading their Data Integration Competence Center. His research focuses on data analysis with missing values, data fusion, empirical Bayes procedures, and nearest-neighbor algorithms. He has contributed to the development of the BaBooN software package for imputation methods and serves as an Associate Editor for the Journal of Official Statistics . His work bridges academic research with practical applications in official statistics and survey methodology. Education: Studied Social Sciences at FAU Erlangen-Nuremberg, conducted research at Harvard University and the University of Michigan. Professional Experience: 8 years in industry roles at GfK SE, followed by academic roles since 2010. Key Contributions: Over 20 peer-reviewed publications on statistical methodology, data integration, and survey design. Engaged in collaborative projects and methodological advancements in handling incomplete data and multinational survey systems. Research Interests: Methodological innovations in missing data imputation, data fusion techniques, Bayesian methods, and the application of statistical theory to real-world problems. His work emphasizes bridging gaps between theoretical frameworks and practical implementation in official statistics and econometrics.

Sébastien Rivatمشاهده پروفایل

پژوهشگر

• Philosophy of Physics
• Quantum Mechanics
• Effective Field Theories
• +۳ مورد دیگر

Sébastien Rivat is a Research Associate at Ludwig-Maximilians-Universität München's Chair for Philosophy of Science. His academic background includes a PhD in Philosophy from Columbia University (2020), MPhil in History and Philosophy of Science from Cambridge University, Master's in Theoretical Physics (Cambridge Mathematical Tripos), and undergraduate studies at École Centrale Paris. He previously served as a postdoctoral fellow at the Max Planck Institute for the History of Science (2020-2022). Rivat's research examines the philosophical implications of modern physics, particularly quantum phenomena and effective field theories. His work bridges history of science, metaphysics, and epistemology, investigating why scientific methodologies succeed. Current projects analyze gauge symmetries, open systems, and discretization methods. His publications demonstrate consistent focus on renormalization group theory and effective field theories, with historical analyses of their development and philosophical examinations of their implications for scientific realism. Starting in 2025, he will lead an ERC project on the history and philosophy of contemporary physics (RESCALE). Rivat has taught in Columbia University's Core Curriculum and continues to mentor students in philosophy of science at LMU Munich.

Rolf Socherمشاهده پروفایل

استاد

• Mathematics for Computer Science
• Theoretical Computer Science
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Rolf Socher is a Professor at the Department of Computer Science and Media, Brandenburg University of Technology. His expertise lies in Mathematics for Computer Scientists, with a focus on theoretical foundations, algebraic structures, and artificial intelligence. He is a member of the German Mathematical Society (DMV) and the German Informatics Society (GI). Teaching responsibilities include foundational mathematics courses for the Online Media Informatics program. His textbook publications span core areas of computer science education, with notable works on algebraic methods, theoretical computer science, and AI fundamentals. Recent works include an updated 2021 edition of Mathematik für Informatiker . Research interests bridge mathematics and computer science, emphasizing practical applications in algorithm design, formal methods, and computational theory. No specific grants or lab affiliations are mentioned in the provided materials.

Rolf H. Möhringمشاهده پروفایل

استاد

• Combinatorial Optimization
• Graph and Network Algorithms
• Operations Research
• +۶ مورد دیگر

Prof. Rolf H. Möhring is a Professor at the Department of Mathematics, Faculty II – Mathematics and Natural Sciences, Technical University of Berlin. He specializes in Combinatorial Optimization, Graph and Network Algorithms, and Operations Research with applications in industrial and transportation systems. His research bridges theoretical foundations and practical implementations, addressing challenges in scheduling, distributed computing, and algorithmic game theory. Key research interests include graph algorithms, project scheduling optimization, and robust optimization methodologies. Notable contributions span network flow analysis, traffic equilibrium design, and logistics optimization in container terminals and shipping routes. Awards: 2025 Research.com Mathematics in Germany Leader Award, 2010 EURO Gold Medal. Publications: Over 127 papers with 16,279 citations in Computer Science and 113 papers with 15,733 citations in Mathematics. His work frequently explores combinatorial structures, invariant theory, and practical applications in distributed systems. His advising focuses on PhD students in combinatorial optimization and algorithmic theory, with contributions to the Mathematics Genealogy Project. Collaborations include industrial projects like Kiel Canal ship traffic optimization and AGV routing in container terminals, emphasizing real-world problem-solving through mathematical frameworks.

Stephan Schmidtمشاهده پروفایل

مدرس ارشد

• Shape optimization
• Inverse problems
• Data-driven optimization
• +۷ مورد دیگر

Stephan Schmidt is a Senior Lecturer in the Department of Mathematics at the University of Trier. His academic career includes teaching and research roles at Humboldt University of Berlin, University of Paderborn, University of Würzburg, TU Darmstadt, and Imperial College London, with a focus on courses like Shape Optimization and Computational Geometry , Numerical Mathematics , and Ordinary Differential Equations . His research spans Shape Optimization , Non-smooth Optimization , and Medical Imaging . He develops advanced mathematical techniques for PDE-based inverse problems , 3D regularization , and High-Performance Computing , often applied to fluid dynamics, electromagnetic scattering, and tomography. Recent publications highlight work on Total Generalized Variation for mesh denoising, Medical Image Registration using hyperbolic PDEs, and Non-smooth Shape Calculus . These papers integrate Finite Element Methods , Discontinuous Galerkin Discretization , and Shape Newton Schemes , reflecting his interest in geometric control and computational efficiency. He has collaborated with institutions like the University of Würzburg (Habilitation, 2018) and Trier University (PhD, 2010), and worked with researchers including Roland Herzog , Andrea Walther , and Viktor Schulz . His projects often address Geometric Inverse Problems , Sparse Neural Networks , and Aerodynamic Design .