جست‌وجوی استاد و پژوهشگر

Andre Borrmannمشاهده پروفایل

استاد

• Building Information Modeling
• Point Cloud Engineering
• Digital Twin
• +۴ مورد دیگر

Andre Borrmann is Professor and Chair of Computing in Civil and Building Engineering at the Technical University of Munich (TUM), where he leads cutting-edge research at the intersection of computer science and construction engineering. His work spans over two decades with consistent publication output since 2003, demonstrating sustained academic leadership in computational methods for the built environment. His research focuses on: Building Information Modeling (BIM) and its advanced applications Digital Twin development for infrastructure management Point cloud processing and semantic enrichment Artificial intelligence integration in construction workflows Construction automation and robotics systems Analysis of his 2023-2025 publications shows a clear trend toward sophisticated AI applications in construction engineering, with increasing emphasis on graph neural networks, transformer models, and large language models. His work bridges theoretical computer science with practical construction challenges, particularly in model automation, code compliance checking, and digital documentation of existing structures. Scientific recognition includes: Konrad Zuse Medal (2024) Professor Borrmann leads multiple significant research initiatives including AM2PM (Additive to Predictive Manufacturing for Multistorey Construction), AI4CADCAM (AI-based CAD processing), and BauPuls360 (a public service platform for the construction industry). His research group maintains extensive international collaborations across academia and industry, contributing to UN Sustainable Development Goals related to sustainable cities, industry innovation, and climate action through their technological advancements in construction engineering.

Colin Jahelمشاهده پروفایل

پژوهشگر ارشد

• Model Theory
• Dynamics
• Probability Theory

Colin Jahel is a Research Fellow at Technische Universität Dresden, specializing in mathematical research at the intersection of Model Theory, Dynamics, and Probability Theory. He completed his PhD in 2021 at the University of Lyon, France, under the supervision of Lionel Nguyen Van Thé and Todor Tsankov. Prior to his current position, he was a postdoctoral researcher at Carnegie Mellon University. His research explores connections between model-theoretic methods and dynamical systems, with emphasis on invariant measures, automorphism groups, and structural properties of mathematical objects. Key themes include ergodic theory applications to countable structures, topological dynamics of Polish groups, and probabilistic aspects of mathematical logic. Jahel's publications demonstrate consistent focus on interactions between model theory and dynamics, with recurrent themes of invariant measures, group actions, and classification of infinite structures. His collaborative work frequently addresses problems in geometric group theory, combinatorial limit theory, and measurable dynamics. He maintains active research collaborations with mathematicians across institutions, including co-authors from Carnegie Mellon University, Charles University, and other European universities.

Martin Michajlowمشاهده پروفایل

پژوهشگر

• Quantum Chemistry
• Machine Learning
• Geometric Deep Learning
• +۲ مورد دیگر

Martin Michajlow is a doctoral researcher in the Machine Learning Group at TU Berlin since June 2024. His research explores the intersection of machine learning and quantum chemistry, with a focus on molecular systems modeling. He holds a B.Sc. in Mathematics from Saarland University (2018) and an M.Sc. in Mathematics from TU Berlin (2024), both completed under academic supervision. Education: Bachelor of Science in Mathematics, Saarland University (2018) Master of Science in Mathematics, Technical University of Berlin (2024) Research interests include developing equivariant graph neural networks for atomic/molecular property prediction, geometric deep learning applications in chemistry, and message passing neural networks for molecular dynamics simulations. Current projects emphasize improving computational efficiency and predictive accuracy in quantum chemistry through advanced ML architectures. No scientific awards or grants have been documented in the available information. He has no listed advisees at this time. Labs/Teams: Core member of TU Berlin's Machine Learning Group, collaborating on interdisciplinary AI+chemistry projects.

• Combinatorics
• Algebraic Geometry
• Tropical Geometry
• +۳ مورد دیگر

Alessio Borzì is a Researcher in the Nonlinear Algebra group at the Max Planck Institute for Mathematics in the Sciences (MPI MiS) in Leipzig, Germany, under the leadership of Bernd Sturmfels. He holds a PhD from the University of Warwick (2023), supervised by Diane Maclagan, following a Master’s and Bachelor’s from the University of Catania, where he was also part of the Scuola Superiore di Catania. His research focuses on Combinatorics, Algebraic Geometry, and Tropical Geometry, with particular emphasis on matroids, toric geometry, and their interactions with Commutative Algebra. Research interests include tropical geometry’s connections to toric varieties, matroid realizability, and algebraic structures like cyclotomic numerical semigroups. His work bridges abstract algebra and combinatorial geometry, with applications in computational algebraic tools such as Macaulay2. Notable contributions include studies on matroid quotients, tropical flag varieties, and graded algebras with cyclotomic Hilbert series. Recent talks and publications highlight trends in realizability problems (e.g., matroid quotients and Bergman fans), tropical moduli spaces, and algebraic combinatorics. Borzì has organized reading groups and seminars on topics like K-stability and tropical geometry, reflecting his commitment to advancing interdisciplinary research. He is a member of the London Mathematical Society and Italy’s GNSAGA. Collaborative networks include co-authors such as Diane Maclagan, Bernd Sturmfels, and others in the Nonlinear Algebra community. His work often involves international collaborations, as evidenced by presentations at institutions like the University of Tübingen, York, and Warwick.

André Schulzمشاهده پروفایل

استاد

• Graph Theory
• Computational Geometry
• Algorithm Design
• +۳ مورد دیگر

Prof. André Schulz is a Professor at the Faculty MI, Department of Theoretical Computer Science, Distance University. His research focuses on graph theory, computational geometry, and algorithm design, with a strong emphasis on geometric graphs, graph drawing algorithms, and topological representations. He has published extensively in top-tier journals and conferences such as Discrete & Computational Geometry , Journal of Graph Algorithms and Applications , and Graph Drawing and Network Visualization . His work spans topics like adjacency graphs of polyhedral surfaces, Lombardi drawings of knots, and experimental analysis of graph visualization techniques. He collaborates internationally, co-authoring over 30 peer-reviewed articles since 2015. His research addresses challenges in geometric algorithms, graph embeddings, and combinatorial optimization, with applications in social network analysis and geometric topology. Key contributions include minimizing geometric primitives in planar graph drawings and developing efficient algorithms for 1-planar and cubic graphs. His recent work (2023–2024) explores orthogonal circle arrangements and schematic hypergraph layouts. Despite no explicit mention of awards or grants, his prolific publication record underscores his academic influence.

Hannes Freyمشاهده پروفایل

استاد

• Wireless Networked Systems
• Mobile Robotics
• Sensor Networks
• +۲ مورد دیگر

Hannes Frey is Professor and Head of the Computer Networks Research Group at the University of Koblenz and Landau. His research focuses on the controllability of complex dynamically networked systems including sensor networks, mobile autonomous robot teams, and connected vehicles. The group investigates fundamental theoretical questions and system-level practical issues, with emphasis on transferring theoretical results into practice through prototype implementations. Research interests include: Connectivity and percolation in wireless networked systems Local topology control under graph structure assumptions Cooperative distributed control for wirelessly networked mobile robots Reliable ultra-low latency communication for autonomous platforms Software Defined Networking for IoT systems The group maintains the UniKoRN laboratory for practical research in wireless communication and mobile distributed robotics, supporting research internships and student projects.

Wolfgang Mulzerمشاهده پروفایل

استاد

• Theoretical Computer Science
• Computational Geometry
• Algorithms
• +۳ مورد دیگر

Wolfgang Mulzer is a Professor in the Department of Computer Science at Freie Universität Berlin, within the Faculty of Mathematics and Computer Science. He leads the Theoretical Computer Science research group (AG Theoretische Informatik) and holds a PhD from Princeton University (2010), advised by Bernard Chazelle. His research focuses on computational geometry, algorithms, and discrete mathematics, with notable contributions to geometric algorithms, data structures, and combinatorial optimization. Education: PhD in Computer Science, Princeton University (2010) Advisor: Bernard Chazelle Research Interests: Mulzer's work spans theoretical computer science with an emphasis on computational geometry. Key areas include geometric algorithms (e.g., Voronoi diagrams, Fréchet distance), dynamic graph algorithms (e.g., disk graphs, connectivity problems), and algorithmic complexity. His research also addresses discrete geometry challenges like Tverberg theorems and geometric intersection graphs. Grants & Labs: Leading the Theoretical Computer Science group at FU Berlin Active in collaborative projects on geometric algorithms and algorithmic foundations Professional Activities: Mulzer has authored or co-authored over 100 peer-reviewed papers, with work appearing in top venues like Discrete & Computational Geometry , SIAM Journal on Computing , and Algorithmica . His research bridges theoretical foundations with practical algorithm design.

• Asymptotic Geometric Analysis
• Geometric Probability
• Information-based Complexity
• +۳ مورد دیگر

Mathias Sonnleitner is an Erwin Schrödinger Research Fellow at the Institute of Financial Mathematics and Applied Number Theory, Johannes Kepler University Linz, hosted by Friedrich Pillichshammer. Previously, he held postdoctoral positions at the University of Alberta (hosted by Alexander Litvak) and the University of Münster (hosted by Zakhar Kabluchko). He earned his Dr. rer. nat. (PhD) in Mathematics from the University of Passau in 2022 under the supervision of Joscha Prochno and Aicke Hinrichs. His research focuses on asymptotic geometric analysis, geometric probability, and information-based complexity, with applications to convex geometry, stochastic processes, and high-dimensional approximation. Education includes a Dipl.-Ing. (MSc) in Mathematics from Johannes Kepler University Linz (2019) and a BSc in Technical Mathematics from the same institution (2018). His work bridges functional analysis, probability, and numerical methods, with notable contributions to entropy numbers, convex body approximation, and optimal recovery problems. Recent publications address minimal dispersion on spheres, shadows of ℓ p -balls, and random approximation in Hausdorff distance. He has received prestigious awards including the Joseph F. Traub Young Researcher Award (2022) and the Sparda-Bank Dissertation Prize (2023). His teaching includes courses on information-based complexity and convex geometry at the University of Passau and Johannes Kepler University Linz.

Ulrich Bauerمشاهده پروفایل

استاد

• Applied Topology
• Computational Topology
• Topological Data Analysis
• +۳ مورد دیگر

Prof. Dr. Ulrich Bauer is a Professor at the Technische Universität München (TUM) , leading the Applied and Computational Topology research group within the TUM School of Computation, Information and Technology . His academic career includes positions at Freie Universität Berlin, Georg-August-Universität Göttingen (where he earned a doctoral degree in Mathematics), and the Institute of Science and Technology Austria. Bauer specializes in applied and computational topology, focusing on multi-scale data connectivity and developing computational methods for large datasets. He is a key member of the Collaborative Research Center Discretization in Geometry and Dynamics and the Centre for Topological Data Analysis . Research Interests: Bauer’s work bridges theoretical foundations and practical applications in topology. He explores methods like persistent homology and discrete Morse theory to uncover global data structures. His contributions include advancing algorithms for topological data analysis, with applications in medical imaging, computational biology, and geometric modeling. Bauer’s software tool Ripser is widely recognized for efficient computation of persistence barcodes. Awards: ATMCS Best New Software Award (2016) Best Paper Award TopoInVis (2013) Apple Design Award (2003) O’Reilly Mac OS X Innovators Award (2003) Grants & Leadership: Bauer’s leadership roles include the executive board of the CRC Discretization in Geometry and Dynamics. His research has been supported by grants focusing on topological methods in data science and geometry. He actively contributes to advancing interdisciplinary collaborations between mathematics, computer science, and applied fields. Labs & Teams: As founder of the Applied and Computational Topology group at TUM, Bauer fosters innovation in computational topology, mentoring researchers and students in developing cutting-edge methodologies. His work intersects with the TUM School’s broader mission in computational and data-driven science.

Carlos Amendolaمشاهده پروفایل

استادیار

• Algebraic Statistics
• Applied Algebraic Geometry
• Nonlinear Algebra
• +۵ مورد دیگر

Carlos Amendola is an Assistant Professor (tenure-track) of Algebraic and Geometric Methods in Data Analysis at the Institute of Mathematics of the Technical University of Berlin. Previously, he was a postdoc at TU Munich in Mathematical Statistics and Optimization and Data Analysis groups, and served as a substitute professor at Ulm University. His academic journey includes a PhD from TU Berlin under Bernd Sturmfels and Christian Haase, an M.Sc. from NYU's Courant Institute, and dual B.Sc. degrees from Mexican institutions. B.Sc. in Applied Mathematics, Instituto Tecnológico Autónomo de México B.Sc. in Mathematics, Universidad Nacional Autónoma de México M.Sc. in Mathematics, Courant Institute at New York University Ph.D. in Mathematics, Technical University of Berlin (2017) Amendola's research centers on Algebraic Statistics, with significant contributions to Applied Algebraic Geometry and Nonlinear Algebra. His work explores the intersection of algebraic methods with statistical modeling, particularly focusing on Gaussian mixtures, likelihood geometry, moment varieties, graphical models, and path signatures. He has developed novel approaches connecting tropical geometry with max-linear graphical models for extreme value theory, and has made important contributions to understanding maximum likelihood estimation through algebraic and geometric perspectives. His recent publications demonstrate a strong focus on applying algebraic techniques to statistical problems, with particular emphasis on path signatures, tropical geometry, and graphical models. The research shows a clear trajectory toward developing computational methods for complex statistical models using algebraic geometry, with applications spanning machine learning, causal inference, and extreme value analysis. Amendola serves as an editor for the Algebraic Statistics (AStat) journal since 2022 and has organized major conferences including Algebraic Statistics 2025. He has successfully secured significant research funding through Berlin Mathematics Research Center MATH+ Project AA3-16, DFG Collaborative Research Center CRC/TRR 388, and DFG Priority Program SPP 2458. As an advisor, Amendola currently supervises four PhD students (Janike Oldekop, Kamillo Ferry, Francesco Nowell, and Gabriel Riffo) and two postdocs (Rosa Preiß and Leonard Schmitz). His teaching portfolio includes courses on Algebraic Statistics, Discrete Geometry, and various mathematics subjects at both undergraduate and graduate levels.

Maximilian Wiesmannمشاهده پروفایل

پژوهشگر ارشد

• Algebraic Geometry
• Computational Geometry
• Combinatorics
• +۴ مورد دیگر

Maximilian Wiesmann is a mathematician working as an ELBE Postdoctoral Fellow at the Center for Systems Biology Dresden, Germany. Previously, he completed his PhD at the Max-Planck-Institute for Mathematics in the Sciences in Leipzig under the supervision of Eliana Duarte and Bernd Sturmfels. Mentored by Aida Maraj and Ivo Sbalzarini at CSBD, his work bridges pure mathematics with applications in computational biology and quantum information. His educational background includes: PhD in Mathematics, Max-Planck-Institute for Mathematics in the Sciences, Leipzig (2025) MASt in Pure Mathematics, University of Cambridge (2022) B.Sc. in Mathematics, University of Bonn (2021) Wiesmann's research focuses on the intersection of algebraic geometry and computational mathematics, particularly in nonlinear algebra applications. His work spans theoretical investigations in toric geometry and combinatorics to practical implementations in quantum information and machine learning. He has developed significant software tools including the EulerStratifications.jl Julia package, which accompanies his research on hypersurface families. His publications demonstrate a consistent trajectory from foundational mathematical structures to their applications in statistical modeling and computational science. Analysis of his 11 most recent publications reveals a strong focus on algebraic statistics and geometric approaches to statistical problems, with increasing attention to machine learning applications. His work connects pure mathematical structures with practical computational frameworks, particularly through the lens of nonlinear algebra. The development of specialized software like EulerStratifications.jl demonstrates his commitment to making theoretical advances accessible for practical computation. Wiesmann has served as a tutor in linear algebra and foundational mathematics at the University of Bonn during winter terms 2019/20 and 2020/21. He also completed a Quantum Science Summer Internship at Riverlane in Cambridge, UK in 2021, and was a visiting student at the Institute for Mathematical and Statistical Innovation at the University of Chicago in September and October 2023. At CSBD, Wiesmann is part of a vibrant research environment focused on systems biology, where he applies his expertise in algebraic geometry to biological modeling problems. His work with the Nonlinear Algebra Community on Zenodo demonstrates his commitment to open science and community building in his field.

Pierluigi D'Acuntoمشاهده پروفایل

استادیار

• Structural Engineering
• Architectural Design
• Computational Design
• +۴ مورد دیگر

Prof. Pierluigi D'Acunto holds the Rudolf Mössbauer Tenure-Track Assistant Professorship in Structural Design at the Technical University of Munich (TUM), within the TUM School of Engineering and Design. His research focuses on computational methods at the intersection of architecture and civil engineering, with an emphasis on innovative material systems, additive manufacturing, and robotic fabrication. Education: He completed a combined degree in Architecture and Civil Engineering at the University of Pisa (2007), earned a Master of Architecture from the Architectural Association in London (2012), and received his doctorate from ETH Zurich (2018). He previously served as a postdoctoral fellow at ETH's Chair of Structural Design before joining TUM in 2021. Research Interests: D'Acunto explores form-force relationships in structures, equilibrium-based design frameworks (e.g., Vector-based 3D Graphic Statics), and the integration of AI/machine learning with structural design tools. His work addresses sustainability through material-efficient construction and circular economy principles. Awards: ETH Medal (2019), IASS Design Excellence Award (2016), Rotary Foundation Scholarship (2011) Key Projects: Digital Bamboo Pavilion, CantiBox robotic timber assembly, Injection 3D Concrete Printing methodologies His publications emphasize data-driven design, fabrication-aware strategies, and the application of advanced robotics in construction. He collaborates closely with industry partners to translate theoretical frameworks into real-world prototypes and built projects.

• Computer Science
• Algorithms
• Computational Geometry
• +۴ مورد دیگر

Sujoy Bhore is affiliated with the Indian Institute of Technology Bombay (Department of Computer Science & Engineering), Université libre de Bruxelles, and Technische Universität Wien. His research focuses on algorithms , computational geometry , and graph theory , with a strong emphasis on geometric optimization , dynamic data structures , and parameterized algorithms . Recent publications highlight advancements in Euclidean spanners for sparse network design online algorithms for dynamic geometric problems Steiner trees and tree covers in planar domains k-median/means approximation using coresets His collaborative work spans institutions, with frequent joint research on geometric intersection graphs , map labeling , and planar graph embeddings . Co-authors include prominent researchers like Csaba D. Tóth, Martin Nöllenburg, and Timothy M. Chan. While no formal awards are documented here, his contributions to algorithmic complexity and geometric networks remain significant.

• Mathematical Analysis
• Stochastic Analysis
• Metric Geometry
• +۴ مورد دیگر

Dr. Michael Hinz is a researcher at Bielefeld University's Faculty of Mathematics with significant involvement in multiple research initiatives. He is affiliated with the International Research Training Group 2235 as a participating scientist and contributes to the Collaborative Research Center 1283 (SFB 1283) project titled 'Taming uncertainty and profiting from randomness and low regularity in analysis, stochastics and their applications,' specifically working on subproject A3: 'Analysis of manifolds, metric spaces and graphs.' Additionally, he is a member of the Bielefeld Graduate School in Theoretical Sciences academic staff. His research focuses on the intersection of mathematical analysis and stochastic processes, with particular emphasis on geometric structures. Dr. Hinz maintains offices at locations UHG V4-239 and UHG V3-237 on campus and can be reached through the Faculty of Mathematics secretariat at +49 521 106-4773. Research interests include: Analysis on manifolds and metric measure spaces Stochastic processes in geometric settings Spectral theory on graphs and fractals Dirichlet forms and potential theory Geometric analysis with applications to mathematical physics Dr. Hinz contributes to the 'Mathematical World' strategic research area at Bielefeld University, which develops fundamental mathematical concepts and theories with applications to solve long-standing open problems in economics and the natural sciences. His work aligns with the university's interdisciplinary research culture, particularly connecting mathematical theory with applications in complex systems.

• Birational Geometry
• Hodge Theory
• Hyperbolicity
• +۱ مورد دیگر

Sung Gi Park is a Veblen Research Instructor jointly affiliated with Princeton University and the Institute for Advanced Study. Previously, he completed his graduate studies at Harvard University under the supervision of Mihnea Popa. His academic appointments bridge two prestigious institutions with a focus on advanced mathematical research. His research specializes in: Birational geometry and applications of Hodge theory Analysis of singular varieties using Hodge modules Hyperbolicity phenomena and geometric structures Classification and properties of singularities in algebraic varieties Recent work emphasizes the intersection of Hodge theory with birational geometry, developing novel approaches to longstanding problems. Publication analysis reveals two dominant themes: Advanced algebraic geometry (5 preprints on singularities/Hodge theory) Contributions to commutative algebra and graph theory (2 peer-reviewed papers) This demonstrates both specialized depth in geometric methods and interdisciplinary versatility. Teaching experience includes: Upcoming instruction in Riemann Surfaces (MAT 531) and Multivariable Calculus (MAT 201) at Princeton Previous teaching roles in Multivariable Calculus (Math 21A) and Algebraic Topology (Math 231A) at Harvard His instructional responsibilities span foundational to advanced graduate-level mathematics courses.