Find Academic Supervisors

• Materials Science
• Metallurgy
• Crystal Plasticity Modeling
• +5 more

Prof. Sebastian Münstermann is a Universitätsprofessor at RWTH Aachen University, leading the Lehrstuhl für Werkstoffmodellierung in der Umformtechnik (Chair of Material Modeling in Forming Technology). He holds affiliations with the Materials Science & Engineering (MatSE) and Molecular Science & Engineering (MSE) profiles, as well as the Projekthaus ICMEaix. His research focuses on advanced materials science, particularly computational modeling of material behavior under various conditions, including crystal plasticity, fracture mechanics, and hydrogen embrittlement. He is involved in interdisciplinary projects such as the FOSTA HOCHFEST network, aiming to improve the performance of high-strength steels for automotive and structural applications. Key areas of expertise include the mechanical behavior of metallic materials, computational materials design, and the integration of machine learning into materials research. His work spans experimental and numerical methods, addressing challenges in material forming, fatigue life prediction, and damage mechanics. He collaborates with the Institute of Metal Forming (IBF), contributing to property-controlled forming processes and non-destructive monitoring techniques. Research trends in his publications emphasize multiscale modeling, data-driven approaches, and the development of novel materials for safety-critical components. His team explores topics such as coating failure mechanisms, microstructure-property relationships, and the optimization of material properties for crashworthiness. The lab’s activities are supported by先进 experimental setups and simulation frameworks, reflecting a strong commitment to bridging fundamental research and industrial applications.

Gero FrieseckeView profile

Professor

• Electronic structure of atoms and molecules
• Calculus of variations
• Molecular dynamics
• +3 more

Prof. Gero Friesecke is a Professor of Mathematics at the Technical University of Munich (TUM), leading the Chair of Analysis within the Department of Mathematics. He is affiliated with the TUM School of Computation, Information and Technology. His research focuses on electronic structure theory, calculus of variations, molecular dynamics, multiscale methods, and optimal transport. He has held academic positions at institutions like the University of Oxford and the University of Warwick before joining TUM in 2004. Education includes a PhD from Heriot-Watt University (1993) and postdoctoral work at Carnegie Mellon University, Universität Freiburg, and ETH Zurich. Notable awards include the Whitehead Prize (1999) and the Oberwolfach Prize (1995). His work spans theoretical and applied mathematics, with contributions to quantum chemistry, materials science, and optimal transport algorithms. He co-edits journals like the Archive for Rational Mechanics and Analysis and serves on scientific advisory boards, including the Max Planck Institute for Mathematics in the Sciences. Recent research emphasizes optimal transport applications in data science and quantum chemistry, with publications on topics like Wasserstein barycenters and self-assembly processes. His leadership roles include Dean of the Faculty of Mathematics at TUM (2012-2015) and co-founding the GAMM activity group on molecular systems modeling.

Oliver JungeView profile

Associate Professor

• Numerical Mathematics
• Scientific Computing
• Dynamical Systems
• +4 more

Oliver Junge is an Associate Professor of Numerics of Complex Systems at the TUM School of Computation, Information and Technology, Technische Universität München. His research focuses on developing novel numerical methods for dynamical systems, with applications in molecular dynamics, astrodynamics, systems theory, and image processing. He holds a doctorate from the University of Paderborn (1999) and has conducted research at institutions like Georgia Tech and Caltech. Notable awards include the TopMath Supervisory Award (2020) and the Research Prize from the University of Paderborn (2004). Educational Background: He studied mathematics and computer science at the Universities of Darmstadt, Bordeaux, Hamburg, and Bayreuth before completing his PhD in Paderborn. His academic career includes roles as a junior professor in Paderborn and associate professor at TUM since 2005. Research Interests: Junge specializes in numerical mathematics and scientific computing, emphasizing the analysis and implementation of numerical methods for complex systems. His work bridges theoretical rigor and practical applications, particularly in computational fluid dynamics, optimal control, and topological data analysis. Awards: His accolades include the Dilthey Prize (1998) and recognition for his contributions to computational methods in dynamical systems. Grants & Advising: While specific grants or advisee names are not listed, his publications indicate extensive collaborative research and mentorship in computational mathematics and systems theory. Labs/Teams: Collaborates with interdisciplinary teams at TUM and internationally, focusing on numerical methods and their applications in engineering and natural sciences.

Christoph HolstView profile

Professor

• Engineering Geodesy
• Geodetic Monitoring
• Terrestrial Laser Scanning
• +6 more

Prof. Dr.-Ing. Christoph Holst is a Full Professor of Engineering Geodesy at the Technical University of Munich (TUM), leading the Chair of Engineering Geodesy since 2021. His academic journey includes a PhD from the University of Bonn (2015) and prior roles as research associate, lecturer, and group leader there. He specializes in geodetic monitoring using terrestrial laser scanning (TLS), focusing on infrastructure, industrial, and environmental applications. His research emphasizes high-precision static/mobile TLS automation, sensor calibration, and deformation analysis. Education: Bachelor and Master in Geodesy & Geoinformation, University of Bonn (Focus: Engineering Geodesy & Parameter Estimation) PhD in Geodesy, University of Bonn (2015, summa cum laude ) Research Interests: His work bridges engineering and environmental geodesy, with key areas: - Advanced TLS Methods : Calibration, registration, and error modeling for deformation analysis. - Interdisciplinary Applications : Monitoring radio telescopes, landslides, and agricultural systems. - Digitalization & Automation : AI integration, 3D point cloud processing, and real-time monitoring systems. His team develops innovative tools like the Simulation Tool for Point Accuracy , enhancing TLS reliability in complex environments. Publications & Awards: Over 100 peer-reviewed articles in journals like Remote Sensing and ISPRS Journal . Notable awards include the GKGM Prize (2019) for TLS calibration and the Teaching Award (2019) from the University of Bonn. His work has been recognized by the Bavarian Academy of Sciences and IEEE societies. Grants & Leadership: He leads TUM's Leonhard Obermeyer Center for Digital Methods and chairs the DVW Working Group on Mobile Sensor Systems. Active in national/international committees (DGK, IEEE, PhenoRob cluster). Labs & Teams: Runs the Geodetic Testing Laboratory with calibration fields and monitoring setups. Collaborates on projects like AImon5.0 for landslide AI monitoring and TUM2TWIN urban digital twin benchmarking.

• Medical Imaging
• Signal Processing
• Machine Learning
• +3 more

Prof. Matthias Eiber holds the position of Professor in Nuclear Medicine at the TUM School of Medicine and Health, Technical University of Munich. He is distinguished as a Humboldt Professor and Heisenberg Professor, reflecting his esteemed academic standing. His research focuses on sparse representation models, analysis operator learning, and applications in signal processing and machine learning. Key contributions include advancements in dictionary learning theory, sample complexity analysis, and optimization techniques on Riemannian manifolds. Eiber’s work bridges mathematical foundations with practical applications in medical imaging and high-dimensional data analysis. Education and Career: While specific educational details are not provided here, his academic trajectory includes prominent roles such as Humboldt and Heisenberg Professorships, indicating a trajectory of exceptional scholarly achievement. He is affiliated with the Department of Nuclear Medicine, integrating computational methods into medical diagnostic technologies. Research Interests: Eiber’s research emphasizes sparse representation theory, co-sparse analysis operators, and the theoretical underpinnings of dictionary learning. His work explores sample complexity bounds in machine learning, optimization algorithms for structured data, and applications in medical imaging. Recent publications address separable models, operator learning, and geometric optimization methods. Awards: Humboldt Professor Heisenberg Professor Advising & Grants: While specific student names or grant details are not listed here, his research output suggests active involvement in supervising PhD students and securing grants related to computational medicine and signal processing. His collaborations likely span interdisciplinary teams within TUM’s medical and engineering divisions. Labs & Teams: Affiliated with the Nuclear Medicine department’s research groups focused on computational diagnostics and medical imaging algorithm development. His work contributes to TUM’s broader initiatives in precision medicine and data-driven healthcare solutions.

• Computer Vision
• Machine Learning
• Deep Learning
• +3 more

Dr. Alexandra Stang serves as the General Manager of the Munich Center for Machine Learning and is affiliated with the Computer Vision Group at the Technical University of Munich (TUM). She is part of the TUM School of Computation, Information and Technology and holds a position within the Department of Informatics. Her research focuses on advanced topics in computer vision and machine learning, including 3D reconstruction, visual SLAM, and deep learning applications. She contributes to the academic community through her role in managing the Munich Center for Machine Learning, fostering interdisciplinary research in AI and computational methods. In terms of education and professional background, specific details are not explicitly provided in the text, but her involvement with TUM's cutting-edge research groups indicates a strong academic and technical foundation. Her work aligns with the group’s broader goals in areas like photometry-based reconstruction, geometry processing, and foundational models in computer vision. Dr. Stang’s contributions to the field are reflected in the group’s achievements, such as the ECCV 2024 Koenderink Award for LSD SLAM. While her direct role in teaching is not detailed, she is associated with a team that offers advanced courses in computer vision, deep learning, and related fields. Her office is located at Boltzmannstrasse 3, 85748 Garching, and she can be reached via Alexandra.Stang@tum.de.

Junpeng WangView profile

Research Fellow

• lightweight structural design
• structural optimization
• scientific visualization
• +5 more

Dr. Junpeng Wang is a Postdoctoral Researcher (since June 2023) in the Chair of Computer Graphics and Visualization at the Technical University of Munich, working under Prof. Rüdiger Westermann. Previously, he completed his PhD at the same institution from November 2018 to June 2023. His research focuses on lightweight structural design and optimization with geometry-based approaches, as well as scientific visualization of tensor and mesh data. Wang's research interests span lightweight structural design , structural optimization , and scientific visualization . His work integrates computational mechanics with computer graphics to develop novel methods for stress analysis, lattice structure optimization, and 3D data visualization. His research has practical applications in mechanical engineering, additive manufacturing, and scientific data analysis. His publication portfolio shows a strong trend toward integrating machine learning with traditional computational mechanics methods, particularly in the areas of 3D Gaussian Splatting and neural data structures. Wang has developed the 3D-TSV (3D Trajectory-based Stress Visualizer), a significant tool for exploring principal stress directions in 3D solids under load, which has been published in Advances in Engineering Software (2022). Wang serves as a reviewer for prestigious journals including IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Methods in Applied Mechanics and Engineering (CMAME), Journal of Mechanical Design (JMD), Optics Express (OPTE), Computer-Aided Geometric Design (CAG), and Shape Modeling International Conference (SPM[C]). His collaborative work primarily involves Prof. Rüdiger Westermann at TUM and Jun Wu at other institutions, demonstrating strong interdisciplinary connections between computer graphics and mechanical engineering research groups.

• Topological Nanoelectronics
• Spintronics
• Condensed Matter Physics
• +7 more

Prof. Yuriy Mokrousov leads the Topological Nanoelectronics Group at the Peter Grünberg Institute (PGI) within the Quantum Theory of Materials (PGI-1) at Research Center Jülich. His research focuses on leveraging topological concepts and geometrical phases (e.g., Berry phases) to explore novel transport phenomena in nanoelectronic materials. Key areas include spintronics, noncollinear magnets, and topological phases in complex systems such as skyrmions and altermagnets. He employs density functional theory (DFT) and first-principles methodologies to bridge theoretical predictions with experimental advances. Research interests span: dissipationless spin currents, topological transport effects, spin-orbit torques, and the interplay between magnetism and quantum geometry. His group investigates materials like Mn2Au, transition metal interfaces, and van der Waals heterostructures to uncover mechanisms for future nanoelectronic applications. Recent articles highlight advancements in orbital magnetism, domain wall dynamics, and optical manipulation of magnetic textures. Collaborations involve developing computational tools to model electronic and spin properties, with applications in spintronics and energy-related materials.

• Materials Science
• Biodegradable Implants
• Corrosion Engineering
• +5 more

Prof. Dr.-Ing. Petra Maier is a Professor of Materials and Manufacturing Engineering at the Faculty of Mechanical Engineering, Stralsund University of Applied Sciences (Germany) and serves as Vice Dean. She holds a doctorate in Materials Science from Loughborough University (UK) and has extensive experience in magnesium alloy research, particularly in biodegradable Mg-based implants. Her work focuses on corrosion under stress, crack propagation, and microstructure-mechanical property correlations in magnesium alloys. She has held research positions at institutions including TU Berlin, Helmholtz-Zentrum Geesthacht, and TU Wildau, contributing to advancements in materials engineering and manufacturing processes. Education: PhD in Materials Science, Loughborough University (2002) Studies in Physical Technologies, Technical University of Wildau Research Interests: Petra Maier’s research emphasizes biodegradable Mg alloys for medical implants, stress corrosion, microstructure analysis, and forming processes. She investigates corrosion fatigue, LPSO phase transformations, and alloy development for biomedical and structural applications. Projects: Current and past projects include studies on Mg-Rare Earth alloys, corrosion behavior of Mg wires, and fracture toughness analysis. She collaborates on EU-funded initiatives and industry partnerships to advance materials science. Labs/Teams: She oversees labs specializing in mechanical material testing, scanning electron microscopy, and non-destructive analysis at Stralsund University. Her team works on corrosion testing and microstructural characterization using advanced techniques like μCT and nanoindentation.

Martin KolbView profile

Professor

• Stochastic Processes
• Probability Theory
• Mathematical Physics
• +3 more

Roles & Affiliations: Martin Kolb is a Professor (W3) at Paderborn University's Institute of Mathematics (Applied Mathematics and Stochastics group leader). He previously held roles including Professor (W2) at Paderborn (2014–2017), Lecturer at University of Reading (2012–2014), and Harrison Early Career Professor at Warwick University (2011–2012). Education: PhD in Mathematics from TU Kaiserslautern (2009), Diploma in Mathematics from Ludwig-Maximilians-University Munich (2005). Studied at University of Copenhagen (2002–2003). Research Interests: Focuses on stochastic processes, probability theory, and mathematical physics. Key topics include quasi-stationary distributions, Fleming-Viot models, spectral asymptotics, and applications in quantum computing (e.g., Photonic Quantum Computing project). His work bridges theoretical mathematics with computational methods and physical systems. Scientific Engagement: Organized major events like the Weierstrass-Lecture series (since 2019) featuring Fields medalists and co-organized workshops such as the Oberwolfach Workshop on Stochastic Processes (2020). Active in conference committees for topics like 'Stochastic Processes under Constraints' (2016). Labs/Teams: Leads research projects including 'PhoQC: Photonic Quantum Computing' and 'Super-Brownian Motion with single point source'.

Thorsten RiedelView profile

Lecturer

• Algebraic Geometry
• Number Theory
• Complex Analysis
• +3 more

Dr. Thorsten Riedel is a Lecturer at the Department 1 of Technische Hochschule Bingen. His academic work focuses on algebraic geometry, number theory, and complex analysis. He teaches courses including Engineering Mathematics 1 and 2, Statistics and Numerics for Biotechnology, Energy and Process Engineering, and Dynamical Systems for Bioinformatics. His contact information includes office Building 2 Room 223 and phone +49 6721 409 366. Dr. Riedel's research interests span foundational mathematical disciplines with applications to engineering and biotechnology. He is involved in curriculum development for programs such as Renewable Energy Management and Supply Engineering, and contributes to teaching across multiple engineering disciplines including energy systems, biotechnology, and process engineering. No scientific awards or grants are explicitly mentioned in the provided materials. His professional activities are centered on undergraduate and graduate education in technical fields.

Paul SeiferthView profile

Researcher

• Computational Geometry
• Algorithms
• Data Structures
• +3 more

Paul Seiferth is affiliated with the Department of Computer Science at Freie Universität Berlin. His research focuses on computational geometry, algorithms, data structures, and graph theory. He has contributed to topics like Voronoi diagrams, dynamic planar graphs, unit disk routing, and spanner construction. His work emphasizes algorithmic efficiency, time-space trade-offs, and geometric data structures. Education : PhD (2012–2016), Freie Universität Berlin Master's (2010–2012), Freie Universität Berlin Research Interests : His research addresses fundamental problems in computational geometry and graph theory, with applications to wireless networks and geometric algorithms. Key themes include dynamic data structures for proximity problems (e.g., Voronoi diagrams), routing in unit disk graphs, and efficient spanner constructions for directed transmission graphs. Key Contributions : His work on time-space trade-offs for Voronoi diagrams and dynamic planar Voronoi diagrams has advanced algorithmic techniques for geometric problems. He also developed efficient routing schemes for unit disk graphs and reachability oracles for transmission graphs, balancing theoretical guarantees with practical efficiency. Teaching : He teaches ProInformatik I: Logik und Diskrete Mathematik . Labs/Teams : Associated with the AG Theoretische Informatik research group at Freie Universität Berlin.

Henning HellerView profile

Researcher

• History of Mathematics
• Philosophy of Mathematics
• Mathematics Education
• +4 more

Henning Heller is a Researcher (Post-Doc) in the Mathematics Education Group (Arbeitsgruppe Mathematikdidaktik) at the University of Bonn’s Mathematical Institute. His academic career includes a PhD in Philosophy from the University of Vienna (2017–2022) under Georg Schiemer, focusing on integrating history and philosophy of mathematics through his dissertation on modern algebra’s historiography. He also holds an M.Ed. from KU Leuven (2022–2023) and an M.A. in Logic and Philosophy of Mathematics from the University of Bristol (2015–2016). His research emphasizes the history and philosophy of mathematics, particularly 19th century algebraic developments like group theory and Felix Klein’s pedagogical innovations. Key research focuses include structuralist approaches in mathematics, Felix Klein’s educational reforms, and the didactic implications of historical mathematical concepts. He has conducted research stays at the Isaac Newton Institute for Mathematical Sciences in Cambridge (2025) and contributed to the ERC Starting Grant project "The Roots of Mathematical Structuralism" (2017–2022). His work bridges historical analysis with contemporary teaching practices, evident in publications like Felix Klein’s Foreign Students (2025) and analyses of Galois theory pedagogy. Research Interests: History of mathematics education, Felix Klein’s legacy, structuralist philosophy of mathematics, group theory historiography Teaching: Current courses include Rechen- und Argumentationstechniken and supervising student research projects on geometric analogies and historical textbooks His awards include the 2023 Dissertationspreis from the Faculty of Philosophy and Education, and he has received multiple stipends including the Friedrich-Ebert-Stiftung grant (2012–2016). He actively participates in international conferences, presenting on topics ranging from quotient group emergence to Klein’s transnational academic networks.

Tomass AndersonsView profile

Part-Time Lecturer

• Factor Analysis
• Analytical Boundary Curve Construction
• Rank Deficiency Problems
• +5 more

Tomass Andersons is a PartTime Lecturer at the University of Rostock's Department of Mathematics, specializing in chemometrics and numerical analysis. His research focuses on factor analysis, analytical boundary curve construction, and addressing rank deficiency problems in multivariate curve resolution (MCR) and spectral data analysis. He has contributed to understanding feasible solutions in rank-deficient systems and developing automated tools for vibrational spectra analysis. His recent publications (2022-2025) explore topics like the geometric construction of feasible solutions, sensor-wise N-BANDS, and algorithms for peak group analysis. These works emphasize resolving ambiguities in MCR problems, handling incomplete data, and improving numerical modeling techniques. His research intersects mathematics, chemistry, and computational methods. He has taught courses on numerical methods for differential equations and programming since 2018, including exercises and practical labs. His contact email is tomass.andersons@uni-rostock.de , and he is affiliated with the Numerical Mathematics Team at the University of Rostock.

• Computational Fluid Dynamics
• Turbulence
• Heat Transfer
• +3 more

Dr.-Ing. Denis Sotomayor-Zakharov is a postdoctoral researcher at the Institute of Fluid Mechanics, Faculty of Mechanical Engineering, Technische Universität Braunschweig. His work focuses on computational fluid dynamics (CFD), turbulence, and heat transfer, particularly in the context of aircraft icing and cooling systems for fuel-cell-powered aircraft engines. Research Interests : CFD, turbulence modeling, heat transfer, aircraft icing simulations, numerical analysis (LES/RANS), and development of the DICEPS software for ice accretion prediction. Projects : Involved in European initiatives like ICE GENESIS, HyMovDeIce, TRACES, and FAME. Collaborations with Airbus, DLR, and ONERA. Publication Trends : Recent articles emphasize LES/RANS comparisons, ice roughness modeling, and numerical methods for particle-laden flows. Key applications include aircraft safety and thermal management in aerospace systems. Collaborations : Active in interdisciplinary research with regional institutions such as DLR and Fraunhofer WKI. Supports international scientific exchange through EU-funded programs.