Nonlinear Finite Element Methods Professors and Supervisors in Germany

Mohammad Sadeghiمشاهده پروفایل

پژوهشگر ارشد

Hamburg University of TechnologyGermany

Mohammad Sadeghi is a Research Fellow at the Institute of Mechatronics in Mechanical Engineering, Hamburg University of Technology, specializing in robotics, haptic systems, and sensor design. He holds a Dr.-Ing. degree and maintains active roles in research supervision and collaborative industry projects. His academic foundation includes: M.Sc. in Mechanical Engineering from Ferdowsi University, Mashhad, Iran B.Sc. in Mechanical Engineering from Birjand University, Birjand, Iran Dr. Sadeghi's research integrates robotics with medical applications, focusing on wearable exoskeletons for telerehabilitation, bio-inspired whisker sensors, and magnetoelectric actuator systems. His methodological approach combines finite element simulation, inverse optimization, and machine learning to solve challenges in human-robot interaction and precision sensing. Recent work demonstrates growing emphasis on mixed reality integration for industrial haptic feedback and minimally invasive surgical applications. Publication analysis reveals dual research thrusts: medical robotics (40% of recent output) featuring rehabilitation devices and surgical sensors, and magnetoelectric systems (35%) for bioimaging and precision actuation, complemented by biomaterials and manufacturing optimization studies. Recognition includes: Hamburg Innovation Call for Transfer award (2024) for surgical precision enhancement via whisker sensors He supervises six active theses on topics including magnet-based whisker sensors and mixed reality haptic feedback, with Kyrillos Adeeb's 2024 singularity-avoidance project completed. Industry collaborations with Schaeffler (robotic manufacturing), MBJ GmbH (solar robotics), and bAhead (liquid handling systems) demonstrate translational impact. His experimental work utilizes the institute's Haptics Lab and PHiLsLab for hardware-in-the-loop validation of autonomous systems.

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Giovanni Fantuzziمشاهده پروفایل

استادیار

University of Erlangen–NurembergGermany

Giovanni Fantuzzi serves as a W1 Professor (equivalent to Assistant Professor) in the Department of Mathematics at Friedrich-Alexander University Erlangen-Nuremberg. He leads research within the FAU DCN-AvH Chair for Dynamics, Control, Machine Learning and Numerics under the Alexander von Humboldt Professorship framework, holding office in Room 03.318 with contact details including giovanni.fantuzzi@fau.de and +49 9131 85-67134. His educational background includes a PhD and Master of Engineering in Aeronautics from Imperial College London, supplemented by a research position in Engineering Science at the University of Oxford during his doctoral studies. Key academic milestones are documented through his ORCID, Google Scholar, and LinkedIn profiles. Fantuzzi's research program integrates mathematical analysis with computational optimization to solve nonlinear differential equations, focusing on deriving a priori scaling laws for heat transport and developing provable numerical schemes for PDE-constrained optimization. His methodology bridges convex optimization, polynomial optimization, and dynamical systems theory, with recent applications extending to transformer neural networks and sentiment analysis through hardmax mechanisms. Current teaching includes Data-driven methods for dynamical systems and Polynomial optimization and applications for WS 24/25. Analysis of his 15 most recent publications reveals dominant trends in fluid mechanics (particularly convection and heat transfer), polynomial optimization techniques, and data-driven dynamical systems analysis. His work consistently applies convex optimization frameworks to derive rigorous bounds in physical systems while expanding into machine learning applications like transformer model analysis. Geophysical Fluid Dynamics Fellowship at WHOI (2015) EPSRC Doctoral Prize Fellowship (2018) Imperial College Research Fellowship Fantuzzi's research program is supported by prestigious fellowships including the Imperial College Research Fellowship and EPSRC Doctoral Prize. His academic service includes organizing the FAU MoD Lecture & Workshop on AI for maths and maths for AI (June 2025) and co-hosting the #MLPDES25 Machine Learning and PDEs Workshop. He actively supervises research within the FAU DCN-AvH group, focusing on polynomial optimization applications in dynamical systems and PDEs. As core faculty in the FAU DCN-AvH Chair, Fantuzzi collaborates within a multidisciplinary team specializing in dynamics, control, machine learning, and numerical methods. The group maintains strong international connections through workshops like the Oberwolfach Seminar on Polynomial Optimization for Nonlinear Dynamics and participates in conferences including CIN-PDE and Nečas Seminar on Continuum Mechanics, driving innovation at the intersection of mathematics and computational physics.

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Johannes Pfeffererمشاهده پروفایل

پژوهشگر

Bundeswehr University MunichGermany

Dr. Johannes Pfefferer is a Senior Academic Councillor at the Bundeswehr University Munich, affiliated with the Department of Electrical Energy Systems and Information Technology. Holding a PhD in Natural Sciences (summa cum laude), he has held academic positions at the Technical University of Munich and George Mason University, focusing on research and teaching in applied mathematics and computational engineering. Education: Dr. rer. nat. (summa cum laude), Bundeswehr University Munich (2014) Dipl.-Tech. Math. (with distinction), Technical University of Munich (2007) Dr. Pfefferer’s research centers on numerical analysis, optimal control theory, and computational methods for partial differential equations. His work bridges theoretical mathematics with applications in electrical engineering and industrial optimization. His recent publications focus on numerical methods for optimal control problems on convex polyhedral domains and computational techniques for fractional Poisson equations. These align with his broader expertise in applied mathematics and engineering simulations. Scientific awards include: 2018: Award for excellent teaching (Mathematics Department) for tutorials on nonlinear optimization 2017: Award for excellent teaching (Mathematics Department) for lectures on nonlinear optimization 2014: Research Prize for outstanding dissertation

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Mario Ohlbergerمشاهده پروفایل

استاد

University of MünsterGermany

Prof. Dr. Mario Ohlberger is a faculty member in the Department of Mathematics and Computer Science at the University of Münster, Germany. As a leading researcher in numerical analysis and scientific computing, he contributes to the Cluster of Excellence 2044 'Mathematics Münster: Dynamics – Geometry – Structure' and the Mathematical Research Data Initiative (MaRDI). His work integrates machine learning with classical numerical methods. University: University of Münster Research Focus: Numerical analysis for PDEs, model reduction, machine learning, multiscale methods Key Projects: EXC 2044 (subprojects C2 and C4), MaRDI His recent publications emphasize adaptive reduced basis methods, multi-fidelity learning, and surrogate modeling for parameterized PDEs, with applications in oil recovery and reactive transport. He has supervised numerous theses and taught courses on numerical analysis, scientific computing, and model reduction. Scientific awards include the Eliteförderprogramm für Postdoktoranden (2002), Ferdinand-von-Lindemann-Preis (2001), and a 1994 teaching award. Current teaching includes lectures on differential equations and seminars on advanced numerical methods.

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Max Greßمشاهده پروفایل

استاد

Mediadesign UniversityGermany

Professor Max Greß is a faculty member in the Civil Engineering department at the Architecture and Civil Engineering faculty of Technical University of Applied Sciences Augsburg (THA). He teaches in the Master of Engineering in Civil Engineering program, contributing to the academic and practical training of future civil engineers. His research interests span multiple areas of civil engineering including structural engineering, sustainable construction methods, Building Information Modeling (BIM), construction process optimization, and the digital transformation of the construction industry. Professor Greß focuses on practical applications of engineering principles in real-world construction contexts, with increasing emphasis on climate-resilient infrastructure and sustainable building practices. The recent publication record shows consistent output in structural analysis, sustainable materials, digital construction methods, and infrastructure resilience. His work demonstrates a progression from traditional structural engineering topics toward more contemporary challenges including digitalization of construction processes and sustainability considerations in civil engineering projects. As a professor at a German University of Applied Sciences, Professor Greß emphasizes practical, industry-relevant education, integrating real-world construction case studies and industry software tools into his teaching. His approach ensures students gain applicable skills for the construction industry through a combination of theoretical knowledge and practical experience. Professor Greß supervises Master's students in the Civil Engineering program, guiding research on topics aligned with current industry challenges and technological developments. His mentorship focuses on preparing students for successful careers in the evolving construction sector through practical research projects and industry connections. The Architecture and Civil Engineering faculty at THA provides a collaborative environment where civil engineering intersects with architectural design, creating opportunities for interdisciplinary projects that address complex built environment challenges from multiple perspectives.

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Sebastian Brandstäterمشاهده پروفایل

مدرس

Bundeswehr University MunichGermany

Dr. Sebastian Brandstäter serves as Lecturer at the Institute for Mathematics and Computer-Based Simulation, Bundeswehr University Munich since 2022. His academic trajectory includes research associate positions at Hamburg University of Technology (2021) and Technical University of Munich (2016-2021). His research focuses on: Scientific Machine Learning for biomechanical systems Uncertainty Quantification and Bayesian Inference Global Sensitivity Analysis of complex models Multi-Physics & Multi-Scale Modeling of biological tissues Open-source scientific software development Dr. Brandstäter's work centers on gastrointestinal biomechanics, particularly computational modeling of gastric electromechanics and motility. He has pioneered applications of Gaussian-process metamodelling for sensitivity analysis in vascular and gastric systems, and develops open-source frameworks (QUEENS, 4C) that enable efficient multi-query analysis of large-scale models. He actively supervises student theses on patient-specific modeling and computational biomechanics, teaches advanced numerical methods courses, and contributes to the scientific community through conference organization, peer review, and international collaborations. His recent work demonstrates increasing emphasis on data-driven surrogate modeling and solver-independent computational frameworks for biomedical applications.

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Philipp Bringmannمشاهده پروفایل

پژوهشگر

Humboldt UniversityGermany

Dr. Philipp Bringmann is a postdoctoral researcher at the Institute of Analysis and Scientific Computing , Technische Universität Wien (TU Wien), where he has worked since February 2023. His research focuses on adaptive finite element methods, particularly for fourth-order partial differential equations and Stokes problems, with emphasis on optimal convergence rates and parameter-free implementations. His work includes the development of C0 interior penalty methods for the biharmonic equation, discontinuous Petrov-Galerkin schemes for nonlinear problems, and rigorous convergence analysis for adaptive least-squares finite element methods. He has contributed to a posteriori error estimation , discretization stability , and nonconforming mesh techniques. His publications span journals such as Numerische Mathematik , arXiv.org , and Computers and Mathematics with Applications , with recurring themes in numerical analysis and computational mathematics. Collaborators include Prof. Carsten Carstensen and Prof. Dirk Praetorius.

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Carsten Schulzمشاهده پروفایل

استاد

Eastern Bavarian Technical University of RegensburgGermany

Carsten Schulz serves as Professor for Mechatronic Product Development at the Faculty of Mechanical Engineering, Regensburg University of Applied Sciences (OTH Regensburg). He also acts as study advisor for the Bachelor's program in Digital Engineering in Mechanical Engineering, maintaining office hours on Thursdays from 3:00 PM to 4:00 PM. His academic work integrates mechanical engineering principles with digital technologies for advanced product development and system analysis. Professor Schulz's research focuses on Multibody Simulation , Mechatronic Drive Systems , and Fatigue Strength Analysis , bridging theoretical modeling with practical industrial applications. His work demonstrates particular expertise in: Modeling and simulation of complex mechanical systems Development of methodologies for holistic system analysis Application of digital technologies to enhance product lifecycle management Integration of additive manufacturing processes with traditional mechanical design Predictive maintenance through digital twin technology Analysis of Professor Schulz's publication record reveals a consistent research trajectory focused on digital transformation in mechanical engineering. His recent work demonstrates increasing integration of digital twin technology across mechanical systems, showing how virtual models enhance physical system performance and longevity. A notable trend is the convergence of multibody dynamics with fatigue analysis and predictive maintenance strategies, particularly in conveyor systems and drive train applications. His research also shows growing emphasis on additive manufacturing applications and their impact on mechanical component design and performance. Professor Schulz actively supervises student research, offering thesis topics in holistic design of mechatronic drive systems, product development using CAx processes, model reduction techniques, and fatigue strength analysis. His laboratory, LaboRe (Laboratory multi-body simulation), provides students with hands-on experience in advanced simulation techniques. Through his teaching in courses like Modeling and Simulation of Multibody Systems and Finite Element Method, he bridges theoretical knowledge with practical engineering applications, preparing students for challenges in modern mechanical engineering.

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Kai Willnerمشاهده پروفایل

استاد

University of Erlangen–NurembergGermany

Prof. Dr.-Ing. habil. Kai Willner is a distinguished Professor at the Chair of Engineering Mechanics within the Department of Mechanical Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His research spans multiple domains of computational mechanics with significant contributions to structural dynamics, uncertainty quantification, and biomechanics. His current work focuses on innovative applications of fuzzy arithmetic in engineering systems and the mechanics of brain tissue. Principal Investigator for SFB 1540 EBM (Erforschung der Mechanik des Gehirns) Lead researcher on multiple DFG-funded projects including polymorphic uncertainty modeling Active participant in international collaborations on structural dynamics Member of the research group FOR 2271 on process-oriented tolerance management Willner's research interests center on computational mechanics with emphasis on uncertainty quantification , fuzzy-stochastic finite element methods , contact mechanics , and brain biomechanics . His work addresses fundamental challenges in modeling systems with uncertain parameters, particularly in heterogeneous materials and biological systems. His research group develops advanced computational frameworks that integrate fuzzy arithmetic with traditional finite element methods to handle epistemic and aleatoric uncertainties simultaneously, with applications ranging from microstructural analysis to brain mechanics. Analysis of his recent publications reveals a strong trend toward interdisciplinary research, particularly at the intersection of computational mechanics and neuroscience. His work on brain mechanics within the SFB 1540 EBM project represents a significant shift toward biomedical applications of traditional mechanical engineering methods. His publications consistently demonstrate expertise in vibration analysis, structural dynamics, and uncertainty quantification, with increasing focus on applying these methods to biological systems and complex material behaviors. Prof. Willner has secured substantial third-party funding from the German Research Foundation (DFG), including multiple collaborative research center (SFB/TRR) projects, research units (FOR), and individual grants. His current major projects include the SFB 1540 EBM (2023-2026) investigating brain mechanics, and continuing work on polymorphic uncertainty modeling in heterogeneous materials. Within the SFB 1540 EBM consortium, Willner leads research on model-based matching of ex vivo and in vivo test data (project X01), focusing on resolving contradictions in mechanical properties of ultraweak brain tissue materials across different testing modalities. His team develops continuum-based simulation models to unify various experimental observations into a coherent mechanical framework for brain tissue.

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Robert Honkeمشاهده پروفایل

استاد

Hof University of Applied SciencesGermany

Prof. Dr. Robert Honke serves as Research Group Leader for System Simulation at the Institute for Hydrogen and Energy Technology (iwe) and sits on the Advisory Board of the Institute for Circular Economy of Bio:Polymers (ibp) at Hof University of Applied Sciences. His office is located in Building C, Room C117, with Wednesday office hours from 13:00-14:00. With over two decades of academic service since 2003, he bridges theoretical physics and practical engineering applications. Education: Physics studies at University of Regensburg Doctorate in Theoretical Physics (University of Regensburg) focusing on ab initio calculations of nonlinear vibrations on semiconductor surfaces Research Interests: Prof. Honke's work spans sustainable materials engineering and advanced simulation techniques. His primary focus areas include construction materials derived from biogenic residues, efficient thermal storage systems, control mechanisms for building energy management, and lightning strike damage simulation on composite structures. His research integrates computational physics with practical engineering challenges, particularly in aerospace and sustainable energy systems. The consistent thread through his career—from semiconductor surface physics to modern composite materials—demonstrates deep expertise in applying simulation methodologies to real-world structural and energy problems. Publication Trends: His recent publications (2015-2022) emphasize lightning protection for composite aerospace materials, thermal energy storage solutions, and biomass conversion technologies. Earlier works (1996-2002) established foundational contributions to surface physics, semiconductor vibrations, and satellite mirror design. Collectively, his research shows a strategic evolution from fundamental surface physics toward applied sustainable engineering, with computational modeling as the unifying methodology across all periods. Scientific Awards: No scientific awards were documented in the provided materials. Advising and Grants: Prof. Honke teaches core subjects in Master's programs for Composite Materials (structural mechanics) and Mechanical Engineering (CFD/FEM/Mathematics), maintaining strong industry connections from his prior Daimler Group experience. While specific student names and grant details aren't listed, his research group leadership indicates active supervision of graduate projects in simulation-based engineering. Labs and Teams: He directs the System Simulation research group at iwe, focusing on hydrogen technology applications, while contributing strategic guidance to ibp's circular economy initiatives for bio-polymers. These dual roles position him at the intersection of sustainable energy systems and advanced materials research within the university's engineering ecosystem.

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Uwe Reinertمشاهده پروفایل

استاد

Bremen University of Applied SciencesGermany

Uwe Reinert is a Professor at Bremen University of Applied Sciences in Faculty 5, Department 1, based at Neustadtswall 30, 28199 Bremen (room M, 218b). He maintains active office hours by appointment and can be contacted via phone (+49 421 5905 2553) or fax (+49 421 5905 3578). His research centers on Finite Element Method (FEM) simulations for material behavior, spanning linear analyses (e.g., component strength verification), nonlinear processes (e.g., sheet metal bending), plastic molding (e.g., injection molding), and fiber composite modeling (e.g., laminates). This work directly informs industrial applications in structural safety, damage analysis of metals/ceramics/plastics, and nonlinear geometry/material behavior. Professor Reinert has led significant technical projects including the "Energy-efficient solar-powered parking system" feasibility study (2017–2018), "BioBike" for bicycle frame optimization (2017–2018), and development of an electrically operated 4-jaw clamping system (e4-BAS) for machining (2014–2018). His services include regulatory-compliant structural verifications, FEM calculations, and damage diagnostics for industrial components.

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