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Thomas MachView profile

Researcher

• Numerical Linear Algebra
• Data Analysis
• Inverse and Ill-Posed Problems
• +5 more

Dr. Thomas Mach is a Postdoctoral Researcher at the Institute of Mathematics , University of Potsdam, Germany, focusing on Data Assimilation under Prof. Melina Freitag. His work bridges theoretical and applied numerical linear algebra. Research Interests Numerical linear algebra for large/structured matrices Krylov subspace methods and iterative eigenvalue solvers Adaptive cross approximation and regularization techniques Applications to inverse problems and parametric systems Publication Trends show expertise in matrix eigenvalue problems, regularization for ill-posed equations, and algorithm design for structured systems. Co-authored works with leading experts like David S. Watkins demonstrate methodological innovation. Awards : SIAM Outstanding Paper Prize (2015) for polynomial root-finding research Academic Service includes co-organizing workshops, serving as Associate Editor for numerical analysis journals, and active participation in international conferences like ILAS, SIAM, and GAMM.

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.

Mathias SawallView profile

Researcher

• Non-negative matrix factorization
• Kinetic modeling
• Blind source separation
• +3 more

PD Dr. Mathias Sawall is a researcher at the University of Rostock's Department of Mathematics, specializing in numerical mathematics and chemometrics. His work focuses on non-negative matrix factorizations, kinetic modeling, and multivariate curve resolution, with applications in spectroscopy and catalysis. He is affiliated with the Institute of Mathematics and has organized the Topics in Chemometrics (TIC) conference in 2023. His research emphasizes developing algorithms for feasible solution analysis, such as the FACPACK software, and exploring rank-deficiency in matrix factorization problems. Key contributions include the geometric construction of feasible solution areas and noise effects on spectral data analysis. Teaching includes courses like Numerics for Engineering and Analysis and Numerics of Partial Differential Equations. He has held office hours on weekdays and contributes to academic conferences and collaborations with researchers in catalysis and spectroscopy. Notable awards include the Kowalski Prize 2016 for best theoretical paper in J. Chemom. . His publications span over two decades, addressing topics from catalyst equilibrium studies to algorithmic advancements in multivariate data analysis.

Klaus NeymeyrView profile

Professor

• Numerical Analysis
• Linear Algebra
• Chemometrics
• +3 more

Prof. Dr. Klaus Neymeyr is a Professor of Numerical Mathematics at the University of Rostock, affiliated with the Faculty of Mathematics and Natural Sciences and the Institute of Mathematics. Since 2023, he serves as Prodekan of the faculty. Previously, he was Dean (2014–2023) and an associated member at the Leibniz Institute for Catalysis (LIKAT). He obtained his habilitation in mathematics at the University of Tübingen (2001) and has held academic roles since 2003. His research spans numerical linear algebra, chemometrics, and catalysis, with a focus on eigenvalue problems, multivariate curve resolution (MCR), and spectral data analysis. Notable contributions include advancements in preconditioned eigensolvers and the development of FAC-PACK for feasible solution computation. Neymeyr’s work integrates computational methods with chemical applications, such as catalyst characterization via FTIR and NMR spectroscopy. He has been recognized with awards including the Kowalski Prize (2016) and a highly cited paper designation by ISI (2003). His collaborations extend to interdisciplinary projects in catalysis and biopharmaceutical data analysis. Publications emphasize algorithm development, convergence analysis, and data-driven methodologies. Scientific achievements include patents on energy-optimized pump regulation and contributions to the theoretical foundations of MCR and eigensolver convergence. His research group actively publishes in top journals like SIAM Journal on Matrix Analysis , Analytica Chimica Acta , and Journal of Chemometrics .