جستجوی استاد راهنمای دانشگاهی

• Quantum Information Theory
• Quantum Many-Body Physics
• Mathematical Physics
• +۷ مورد دیگر

Professor Michael Marc Wolf is a faculty member at the Technical University of Munich , affiliated with the School of Computation, Information and Technology and the Department of Mathematics . His research focuses on the mathematical and conceptual foundations of quantum theory and quantum information. Current research group: Quantum Information Theory Ongoing collaborations: Munich Center for Quantum Science and Technology, Munich Quantum Center, CRC TRR 352 Research Interests: Wolf works at the intersection of quantum information theory , quantum many-body physics , and mathematical physics . His work explores undecidability in physics, quantum tomography, spectral gaps, and quantum channel theory. Recent trends in his publications include entropy-constrained sets, quantum complexity, and differential forms applied to quantum systems. Teaching: Currently teaching Mathematics for Physicists 2 (Analysis 1) and advanced quantum information experiments in Winter 2024/25 and Summer 2025.

• 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.

• Optimal Transport
• Calculus of Variations
• Wasserstein Barycenters
• +۴ مورد دیگر

Camilla Brizzi is a Researcher at the Technical University of Munich (TUM), affiliated with the Chair of Global Analysis under Prof. Friesecke. She completed her PhD through a co-tutorship program between the University of Florence and the University of Paris Dauphine. Her research focuses on optimal transport theory, calculus of variations, and related areas such as Wasserstein barycenters, multi-marginal problems, and entropic methods. She has contributed to advancements in non-convex cost optimization and supremal variational problems. Her academic journey includes studies at the University of Florence, followed by doctoral research combining European institutions. She collaborates with leading figures in the field, including Gero Friesecke and Luigi De Pascale, and her work bridges theoretical analysis with computational methods. Her publications span high-impact journals like Nonlinear Analysis and Applied Mathematics and Optimization , addressing both foundational and applied aspects of optimal transport. Brizzi’s research interests also extend to the application of optimal transport in solving complex mathematical problems, such as those arising in physics and data science. She actively contributes to the academic community through seminars, conferences, and interdisciplinary projects, reflecting her commitment to advancing mathematical foundations and their real-world implications.

• Numerical Analysis
• Mathematical Physics
• Differential Geometry
• +۳ مورد دیگر

Eddy de Leon Aguilar is a post-doctoral researcher at the Technical University of Munich's Department of Mathematics under the School of Computation, Information and Technology. His work focuses on numerical methods for high-dimensional time-dependent PDEs, gravitational lensing, and spacetime visualization using ray tracing techniques. He specializes in mathematical physics, particularly in applications of theta functions to problems like the Schottky problem and axially symmetric spacetimes. Research Interests: Numerical Analysis of Partial Differential Equations Mathematical Physics General Relativity and Spacetime Modeling Theta Functions and Riemann Surfaces Computational Geometry Notable Contributions: His recent publications highlight interdisciplinary work bridging algebraic geometry, computational physics, and relativistic visualization. He develops efficient algorithms for geodesic computation and explores connections between abstract mathematics and physical phenomena like black hole shadows.

Nicola Wolpertمشاهده پروفایل

استاد

• Geometric Algorithms
• Digital Prototyping
• Neural Networks
• +۴ مورد دیگر

Prof. Nicola Wolpert is a Professor at HFT Stuttgart, specializing in Geometry and industrial applications within mathematics and computer science. She teaches across programs including Applied Mathematics and AI, Computer Science, and Mathematics. Her work focuses on geometric algorithms, digital assembly planning, and neural networks for geometric problems. She is affiliated with the Competence Center for Industrial Applications of Computer Science and Mathematics. Her research projects include Digital Assembly Planning (automating vehicle component paths), GeoCADUp (3D CAD geometry analysis), and the M4_LAB (Innovation Laboratory for Metropolitan Region 4.0). She also contributes to urban digital twin initiatives (iCity 2) and leads the Rasand Laboratory, developing software solutions for geometric analysis. Publications are accessible via the Rasand Laboratory website. Prof. Wolpert is a member of the BW-CAR Doctoral Center, part of Baden-Württemberg’s Universities of Applied Sciences doctoral network. Her advising and grants are tied to these collaborative projects, emphasizing interdisciplinary innovation in manufacturing and urban ICT systems. Key facilities include the Rasand Laboratory, where she oversees software development for digital geometry analysis, and the HFT Innovation Laboratory for advanced technological prototyping.

Marc Zimmermannمشاهده پروفایل

مدرس

• Mathematics Education
• Chemistry Education
• Didactics
• +۳ مورد دیگر

Marc Zimmermann is a Lecturer and Campus Manager at Ludwigsburg University of Education. He holds a Master's degree in subject didactics (mathematics, physics) and has extensive experience in education and academic administration. His roles include serving as a Senate Elected Member and coordinating the introduction of HISinOne university management software. Zimmermann has held positions as a Research Associate and Lecturer at the Institute of Mathematics and Computer Science, with additional academic staff roles at the University of Economics and the Environment Nürtingen-Geislingen. Educational background includes a first state examination for teaching secondary schools (history, mathematics, physics) and advanced studies in mathematics and physics didactics. His research focuses on mathematics education innovation, including intelligent assessment tools, active learning strategies, and didactic frameworks for STEM subjects. Notable projects include the SAiL-M project addressing teaching methodologies and the development of the 'open math room' concept for active learning environments. Zimmermann’s work emphasizes bridging theory and practice in education through technology integration, such as e-learning tools and lecture recordings. His recent publications explore chemical reaction mechanisms, self-efficacy in mathematics learners, and conceptual understanding in STEM fields. He has contributed to curriculum development across multiple institutions and remains active in improving teaching quality through collaborative academic initiatives.

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.

Paul von Bünauمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Healthcare Technology
• Machine Learning
• +۴ مورد دیگر

Dr. Paul von Bünau serves as Managing Director (CEO) of IDALab, a strategic advisory firm focused on artificial intelligence in healthcare and biotechnology. He concurrently holds an adjunct academic role at Europa-Universität Viadrina Frankfurt (Oder), where he teaches courses on AI strategy and regulatory compliance in healthcare. His educational background includes a PhD in Machine Learning (TU Berlin), M.Sc. in Pure Mathematics (University of St Andrews), and B.Sc. in Computer Science (University of Potsdam). **Professional Background**: Paul provides strategic AI guidance to multinational healthcare companies, biotech startups, and medical device manufacturers. Key engagements include building AI innovation units for a medtech company, accelerating drug discovery through AI-driven R&D, and developing AI tools for healthcare market access under EU regulations. His approach emphasizes aligning technical solutions with organizational needs and regulatory landscapes. **Research & Teaching**: At Viadrina, he delivers seminars on AI strategy (2024) and regulatory compliance in healthcare AI (2025). His research focuses on non-stationary data analysis, clinical data harmonization, and AI applications in neuroscience. Recent work includes a validated clinical data pipeline for scalable AI deployment (JMIR Medical Informatics, 2023) and algorithms for stationary subspace analysis (Physical Review Letters, 2009). **Key Takeaways from Projects**: Companies with strong engineering cultures often underestimate the cultural and structural changes required for AI integration. Rapid prototyping, talent alignment, and cross-disciplinary teams (e.g., AI + healthcare experts) are critical for success. His work highlights the transformative potential of AI in healthcare while emphasizing ethical and regulatory considerations.

Torsten Mützeمشاهده پروفایل

استاد

• Discrete Mathematics
• Theoretical Computer Science
• Graph Theory
• +۵ مورد دیگر

Torsten Mütze is a Professor at the Institute of Mathematics at the University of Kassel. Previously, he held positions as an Assistant Professor at the University of Warwick (2019–2024) and was affiliated with Charles University Prague's Department of Theoretical Computer Science and Mathematical Logic. His academic journey includes a postdoc under Martin Skutella at TU Berlin, research stays at Georgia Tech and ETH Zurich, and a software engineering role at Supercomputing Systems Zurich. Education: PhD in 2011 from ETH Zurich under Angelika Steger's supervision Master's and Bachelor's degrees in related fields Research Interests: Focuses on discrete mathematics and theoretical computer science, including combinatorial algorithms, graph theory, computational geometry, order theory, Ramsey theory, and combinatorial games. His work bridges foundational theory and real-world applications, particularly in algorithm design and combinatorial generation. Advising & Grants: Supervised students: Francesco Verciani, Nastaran Behrooznia, Namrata, Arturo Merino, Frieder Smolny, Karl Däubel, Jerri Nummenpalo, and Ondřej Mička Funded projects: DFG Heisenberg grant 522790373, Chancellor's International Scholarships, and EU funding Labs & Collaborations: Organizes workshops like 'Combinatorics, Algorithms and Geometry' and contributes to research networks such as the 'Combinatorial Optimization and Graph Algorithms' group. His work involves collaborations with institutions globally, including ETH Zurich, Georgia Tech, and TU Berlin.

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 .

Raymond O. Wellsمشاهده پروفایل

استاد

• Complex Analysis
• Wavelet Analysis
• Differential Geometry
• +۳ مورد دیگر

Raymond O. Wells is a Distinguished Professor of Mathematics at the School of Computer Science & Engineering, Constructor University. Previously, he held roles as Professor of Mathematics and Vice President for External Affairs at Jacobs University Bremen, and served as Professor Emeritus at Rice University. His academic journey includes a BA in Mathematics from Rice University (1962) and a PhD from New York University (1965). His research focuses on complex analysis, wavelet theory, differential geometry, and the history of mathematics. Notable contributions include foundational work on complex manifolds, cohomology in theoretical physics, and applications of wavelet analysis in signal processing. He has authored influential books such as *Differential Analysis on Complex Manifolds* and *Wavelet Analysis: The Scalable Structure of Information*. Wells has received prestigious awards including the Guggenheim Fellowship (1974–1975) and Humboldt Senior Scientist Award. Beyond academia, he has served as President of the Boulder Philharmonic Orchestra and the Boulder Ensemble Theatre Company. His career reflects a blend of mathematical rigor and interdisciplinary engagement, spanning academic leadership, research innovation, and cultural contributions.

• Computer Science
• Computational Geometry
• CAD
• +۲ مورد دیگر

Prof. Dr. Margitta Pries serves as a Professor at Beuth University of Applied Sciences Berlin within Fachbereich II, maintaining an office in Haus Beuth, Room 128b at Luxemburger Str. 10, 13353 Berlin. Her contact includes telephone +49 30 4504 2990 with appointment-based office hours. Her academic focus centers on Computer Science , Computational Geometry , and Mathematical Methods , evidenced by extensive teaching in Data Structures and Algorithms, CAD systems, Theoretical Computer Science, and Geometric Modeling. Course history spans from Winter Semester 2003/2004 through current Moodle-hosted offerings. Current instructional materials are accessible via the university's Moodle platform, reflecting ongoing engagement in curriculum delivery for foundational and advanced computing topics without indication of reduced academic activity.

Johannes Neidhartمشاهده پروفایل

استاد

• Mathematical modeling
• Monte Carlo simulations
• Extreme value statistics
• +۳ مورد دیگر

Prof. Johannes Neidhart is a theoretical physicist and professor of mathematics at the Department of Electrical Engineering. His research focuses on mathematical modeling, Monte Carlo simulations, extreme value statistics, network dynamics, reliability theory, and functional safety. He explores complex systems through interdisciplinary approaches, combining statistical mechanics and evolutionary biology. His recent work examines phase transitions in adaptive walks on fitness landscapes and the role of epistasis in longevity interventions. Research Interests: Dr. Neidhart’s work bridges theoretical physics and biological systems, with a focus on survival curve analysis, fitness landscape dynamics, and evolutionary optimization. His studies often employ advanced statistical methods to model adaptive processes and system reliability. Notable research topics include phase transitions in evolutionary systems and the application of extreme value theory to biological aging mechanisms. Publications highlight trends in understanding longevity interventions through survival curves, adaptive dynamics in rugged fitness landscapes, and the interplay between epistasis and sexual reproduction advantages. While no awards are explicitly listed, his contributions reflect deep engagement with interdisciplinary theoretical frameworks. Advising & Grants: No advising records or grant details are provided in the current data. His academic profile emphasizes research output over listed collaborations or funding sources. Labs/Teams: No specific laboratories or research groups are mentioned in the provided information.

• Algebraic Geometry
• Number Theory
• Arithmetic Geometry
• +۱ مورد دیگر

Sigrid Yanara Palacios Castillo is a Researcher at the University of Cologne's Mathematical Institute, affiliated with the Department of Mathematics and Computer Science. She holds a Dr. phil. (PhD) in Mathematics from the University of Bonn (2018) and conducted postdoctoral research at Princeton University (2019–2021). Her research focuses on Algebraic Geometry, Number Theory, and Arithmetic Geometry, with applications to cryptography and geometric representation theory. Education: PhD in Mathematics, University of Bonn, 2018 Postdoc, Princeton University, 2019–2021 Her work explores moduli spaces of abelian varieties, p-adic cohomology, and geometric approaches to the Langlands program. She has been recognized with the Award for Outstanding Research in Arithmetic Geometry (2021) . Awards: Award for Outstanding Research in Arithmetic Geometry (2021) Advising & Grants: Supervised PhD students: Lisa Müller (2022), Johannes Weber (2023) Recipient of an ERC Starting Grant (2022–2027) Labs/Teams: Part of the Arithmetic Geometry Research Group at Cologne, collaborating on interdisciplinary projects.

• Combinatorics
• Algebra
• Geometry
• +۳ مورد دیگر

John Machacek is an Assistant Professor of Mathematics and Computer Science at Hampden-Sydney College. His academic journey includes a PhD in Mathematics from Michigan State University (advised by Michael Shapiro), postdoctoral positions at the University of Oregon and York University, and prior visiting roles at Hampden-Sydney. He specializes in combinatorics with applications to algebra, geometry, topology, and theoretical computer science. His research explores topics such as cluster algebras, matroid theory, graph theory, and scheduling problems. Key educational milestones include a B.S. from the University of Minnesota-Twin Cities (Honors Thesis advised by Victor Reiner) and postdoctoral collaborations with Patricia Hersh and Nantel Bergeron. His Erdős number is 3, reflecting collaborative work in combinatorial mathematics. Research trends in his articles focus on algebraic and geometric combinatorics, including studies on Grassmannians, matroid structures, scheduling algorithms, and discrete dynamical systems. His work bridges pure combinatorics with interdisciplinary applications in physics and computer science. No scientific awards are explicitly listed, though his extensive contributions to MathOverflow and collaborative projects highlight his scholarly engagement. He advises no listed students but actively participates in academic communities across platforms like MathOverflow and Google Scholar. His research outputs span diverse subfields, emphasizing both foundational theory and applied problem-solving.