Find Academic Supervisors

• Artificial Neural Networks
• Numerical Analysis
• Partial Differential Equations
• +3 more

Timo Kröger is a Researcher at the University of Münster's Institute for Analysis and Numerics , part of the Department of Mathematics and Computer Science. His research focuses on numerical analysis, partial differential equations, and the mathematical foundations of artificial neural networks. He collaborates with Prof. Arnulf Jentzen on projects exploring the dynamics of neural network training, optimization landscapes, and high-dimensional approximation problems. Research interests include the theoretical analysis of gradient descent methods in overparameterized networks, non-convex optimization challenges in deep learning, and Lipschitz continuity properties of neural network parameters. His work often intersects with applied analysis and computational mathematics. Publications : His recent studies investigate the existence of non-global minima in neural network training (2022), parameter norm bounds via Lipschitz analysis (2022), and convergence rates for gradient descent in overparameterized systems (2021). Professional Support : Administrative support is provided by Claudia Giesbert (Phone: +49 251 83-33792, Room 120.002). Kröger's office is located in Room 110.025 at Orleans-Ring 10, 48149 Münster.

• Prosody
• Intonation
• Phonetics
• +5 more

Prof. Bettina Braun is a faculty member at the University of Konstanz, specializing in prosody and intonation. Her research explores intonational contrasts, listener processing, and second language acquisition. She teaches phonetics, phonology, and experimental methods, and was honored with the students' teaching prize. She holds regular office hours and is supported by a secretary, Barbara Werner. Research focuses on how prosody interacts with lexical meaning, particularly in questions and sarcasm. Cross-linguistic studies feature prominently, including work on German, Persian, Chinese, and Swiss dialects. She emphasizes experimental methods, including Active Learning systems for perception experiments. Her work also examines infant-directed speech and L2 acquisition challenges. Key contributions include analyses of rhetorical vs. information-seeking questions, the role of pitch accents, and the impact of native language on prosodic perception. Ongoing projects are detailed on her dedicated page. Scientific awards include the University of Konstanz student-recognized teaching prize. Her lab's work is supported by collaborations in corpus development, such as the Konstanz prosodically annotated infant-directed speech corpus (KIDS corpus). She actively publishes on intonation’s role in disambiguation and cross-cultural communication.

Wolfgang WohofskyView profile

Research Fellow

• Set Theory
• Forcing
• Set Theory of the Reals
• +1 more

Wolfgang Wohofsky is a Research Fellow at the Department of Mathematics, University of Hamburg, working in the Mathematical Logic group led by Prof. Benedikt Löwe. He has been in this position since 2015. Education: 2000: High School Diploma (Europagymnasium Klagenfurt) 2008: Master of Science in Mathematics (Vienna University of Technology) – Thesis: On the existence of p-points and other ultrafilters in the Stone-Cech-compactification of N 2013: PhD in Mathematics (Vienna University of Technology) – Thesis: Special sets of real numbers and variants of the Borel Conjecture Research Interests: Wolfgang's work focuses on set theory, specifically (iterated) forcing, its applications to set theory of the reals, and properties of special sets of real numbers. His research explores combinatorial aspects of infinite sets, consistency results via forcing techniques, and generalizations of classical descriptive set theory concepts. Publication Trends: His 12 most recent articles (2014-2024) primarily investigate forcing methods, cardinal characteristics, variants of the Borel Conjecture, and combinatorial structures like mad families and towers. The works demonstrate consistent focus on foundational set-theoretic problems, often using advanced independence proofs. Awards: DOC fellowship, Austrian Academy of Sciences (2010-2011) Teaching & Service: Teaches mathematics courses for physics students at Hamburg (2015-present). Previously taught engineering mathematics at Vienna University of Technology (2004-2008). Regular participant at international set theory conferences, including Young Set Theory Workshops and Winter Schools in Abstract Analysis.

Salvatore BarbaroView profile

Professor

• Political Economy
• Public Policy
• Electoral Systems
• +3 more

Overview Prof. Dr. Salvatore Barbaro is a full-time faculty member at the University of Mainz (JGU), holding the position of Professor of Social Choice and Collective Decision Making within the Department of Management and Economics at the Faculty of Law and Economics . He also serves as the Program Director for the BSc in Economics . His office is located at REWI II Room 00-122, with regular office hours on Wednesdays 09:00-10:00 by appointment. Research Focus Barbaro's research centers on electoral systems , fiscal federalism , and taxation policy , with notable contributions to topics such as: Strategic behavior in federal crisis management Design flaws in proportional representation systems Economic impacts of health-related taxation Interactions between electoral rules and political polarization Teaching & Academic Service In addition to research, Barbaro oversees the BSc in Economics program and teaches courses on public policy and quantitative methods. His research group includes assistants Maike Roth, Annika Kolland, and others, focusing on topics like voting theory and fiscal policy evaluation. Recent Work Trends Recent publications (2021–2025) emphasize: Critical analysis of German federalism's institutional challenges Evaluation of pandemic-era governance strategies Quantitative studies on electoral system design implications Critiques of tax policy instruments for health behavior modification Professional Network Barbaro collaborates with institutions like the JGU LaTeX group (Overleaf) and maintains academic resources for students via platforms like JoGuStiNe LMS. His research often intersects with practical applications in policy design and institutional reform.

Michael NagelView profile

Researcher

• Bayesian Statistics
• Structural Equation Modeling
• High-Dimensional Data Analysis
• +7 more

Michael Nagel is a Research Associate at the Methods Center within the Department of Social Sciences, Faculty of Economics and Social Sciences, University of Tübingen. He has been involved in a DFG-funded project since 2021, focusing on advanced statistical modeling and behavioral economic analysis. Master of Science in Economics and Finance, University of Tübingen (2020) Bachelor of Science in Economics and Business Administration, University of Tübingen (2018) His research spans Bayesian statistics, high-dimensional data analysis, and behavioral economics, with a particular focus on emotional decision-making in sports contexts and statistical methodology for structural equation modeling. He applies machine learning techniques to social science questions, especially in modeling complex human behaviors under uncertainty. The two most recent publications highlight his dual focus: one on emotional drinking during soccer matches, linking suspense and surprise to alcohol use, and another on developing alternative Bayesian priors for high-dimensional estimation. These works reflect a strong interdisciplinary trend combining econometrics, psychology, and computational methods in social sciences. While no formal scientific awards are listed in the provided texts, his work has been presented at notable academic forums including the Cluster of Excellence 'Machine Learning in Science' conferences and the DGPs Congress. Michael Nagel has advised or collaborated on research projects, particularly within the Methods Center, and is supported by a DFG research grant. He actively contributes to open science through replication packages on GitHub. He is part of the research team led by Prof. Augustin Kelava, focusing on methodological innovation in the social sciences. He is affiliated with the Methods Center at the University of Tübingen, a hub for advanced quantitative methods in social sciences. The center fosters interdisciplinary collaboration, particularly in integrating machine learning with traditional social science research. His work is aligned with the Cluster of Excellence 'Machine Learning in Science', indicating strong integration into cutting-edge research networks.

Robert BeinertView profile

Senior Lecturer

• Applied Mathematics
• Inverse Problems
• Optimal Transport
• +3 more

Robert Beinert is a Senior Lecturer (Privatdozent) in Applied Mathematics at the Technische Universität Berlin, affiliated with the Department of Applied Mathematics within the Faculty of Mathematics and Natural Sciences. He holds a Dr. rer. nat. (Ph.D.) from Georg-August-Universität Göttingen (2015) and completed his Habilitation at Technische Universität Berlin in 2025. His research focuses on inverse problems, optimal transport, phase retrieval, and mathematical imaging, with applications in signal processing and data analysis. He has held academic positions including Research Associate roles at TU Berlin (2020–2025), Karl-Franzens-Universität Graz (2016–2020), and Georg-August-Universität Göttingen (2016). His work bridges theoretical foundations and practical applications, with contributions to regularization techniques, optimal transport theory, and algorithmic development. Key research interests include phase retrieval uniqueness analysis, Gromov-Wasserstein transport, and denoising methodologies for manifold-valued data. His recent publications emphasize advancements in optimal transport frameworks, regularization strategies, and applications in image processing and machine learning.

Michael QuellmalzView profile

Researcher

• Applied Mathematics
• Inverse Problems
• Tomography
• +4 more

Dr. Michael Quellmalz is a Researcher in Applied Mathematics at the Technical University of Berlin (TU Berlin), affiliated with Faculty II - Mathematics and Natural Sciences and the Institute of Mathematics. His research focuses on inverse problems, tomography, optimal transport, and Fourier analysis with applications in medical imaging and computational geometry. He actively contributes to the SFB Tomography Across the Scales collaborative research center, advancing reconstruction techniques in diffraction tomography and motion detection. He teaches a variety of courses including Analysis II for Engineering, Harmonic Analysis I, and Numerical Mathematics, emphasizing both theoretical foundations and their practical implementations. His work has been recognized through awards such as the Universitätspreise 2020 and a Digital Fellowship for innovative educational contributions in adaptive feedback systems. Key publications include advancements in sliced optimal transport on spheres, motion detection algorithms, and Fourier-based reconstruction methods. Dr. Quellmalz's research group develops MATLAB toolboxes for applications like FourierODT and NFFT-Sinkhorn, reflecting his commitment to bridging mathematical theory with computational tools. His academic journey includes a PhD from TU Chemnitz (2019) and extensive participation in international conferences, workshops, and collaborative projects across Europe.

Florian BeierView profile

Researcher

• Optimal Transport
• Multi-Marginal Optimal Transport
• Gromov-Wasserstein Distance
• +3 more

Florian Beier is a Researcher at the Institute of Mathematics, Technical University of Berlin, specializing in Applied Mathematics. Since October 2021, he has served as a research assistant pursuing his Dr. rer. nat. His academic journey includes a Master of Science (2021) and Bachelor of Science (2018), both in Mathematics from TU Berlin, with thesis topics focusing on Optimal Transport and Percolation Theory. Research interests revolve around Optimal Transport theory, particularly multi-marginal and Gromov-Wasserstein formulations, with applications to mathematical imaging and computational geometry. His work bridges theoretical advancements and practical implementations, addressing challenges in transportation barycenters, entropic regularization, and algorithmic design for complex data analysis. Notable achievements include the Best Poster Award at the 2022 International Conference on Curves and Surfaces and recognition for academic excellence at TU Berlin's Dies Mathematicus. He actively contributes to conferences and workshops, presenting groundbreaking research on transport operators and barycenter computations. Current projects involve developing fixpoint iteration methods for Gromov-Wasserstein barycenters and exploring transport kernels for unpaired data analysis. His collaborations span institutions like the University of Tübingen and KTH Royal Institute of Technology, emphasizing interdisciplinary approaches to transport problems.

Maria SchumacherView profile

Researcher

• Labor and industrial sociology
• Sociology of science
• Philosophy of science
• +7 more

Maria Schumacher is a researcher and doctoral candidate at the University of Münster's Department of Sociology within the Faculty of Educational Science and Social Sciences. Working under Professors Matthias Grundmann and Christoph Weischer, she is completing her doctoral dissertation titled "Reception of metascientific discourses in German sociology" toward a Dr. phil. degree. She has been actively teaching methodological seminars and sociology courses since 2010, with teaching assignments scheduled through the Winter Semester 2025/26. Her research spans labor and industrial sociology, sociology of science, philosophy of science, and qualitative social research methodologies. She specializes in interpretative social research, grounded theory, and the sociology of knowledge, with particular interest in how scientific discourses are received and transformed within German sociology. Her work bridges theoretical frameworks from Ludwik Fleck, Thomas Kuhn, and Actor-Network Theory with empirical sociological investigations. Schumacher's extensive publication record consists primarily of encyclopedia entries spanning nearly four decades (1986-2024), demonstrating consistent scholarly engagement with key concepts in sociological theory, industrial relations, and science studies. Her recent 2024 publications focus on foundational concepts like collective memory, psychoanalysis, basic trust, and knowledge economy, reflecting her broad theoretical interests within sociological discourse. Member of the German Sociological Society (DGS) since May 2025 Member of the Section for Science and Technology Studies, DGS since 2020 Member of the Section of Sociological History, DGS since 2019 Member of the Section of Sociological Theory, DGS since 2018 Member of the Center for the Philosophy of Science at WWU since 2013 Member of the Section of Work and Industrial Sociology, DGS since 2013 As a dedicated educator, Schumacher has consistently taught methodological seminars focusing on qualitative research methods, interpretative social research, and grounded theory. Her teaching portfolio demonstrates deep engagement with both theoretical frameworks and practical research applications. She maintains regular consultation hours at her office in Scharnhorststr. 121, Room 514, Münster, and is actively involved in the academic community through colloquia and research presentations.

• Nonlinear Differential Equations
• Partial Differential Equations
• Mathematical Modeling
• +3 more

Prof. Dr. Christoph Walker is a full professor in the Institute for Applied Mathematics at Leibniz University Hannover. He holds a W3 professorship for Mathematical Modeling with a focus on nonlinear differential equations. His academic career includes positions at the University of Zurich and Vanderbilt University. He has served as Vice Dean (2017–2019) and Dean (since 2019) of the Faculty of Mathematics and Physics. Education: Matura (Swiss high school diploma), 1994 Diploma in Mathematics, University of Zurich, 1999 Doctorate in Natural Sciences, University of Zurich, 2003 Research Interests: Prof. Walker specializes in nonlinear partial differential equations, mathematical modeling of physical systems (e.g., MEMS devices), and population dynamics. His work integrates analysis of age-structured populations, free boundary problems, and stability analysis. Recent research emphasizes quasilinear parabolic equations, MEMS modeling, and biofilm dynamics. Teaching & Administration: He teaches applied analysis, functional analysis, and mathematical methods for life sciences. As Dean, he oversees academic policies and curriculum development in mathematics and physics. Professional Activities: Editorial roles and international collaborations include visiting positions at Université Paul-Sabatier (Toulouse) and rejected offers at other institutions. His research group focuses on interdisciplinary applications of PDEs.

• Medical Informatics
• Computational Biology
• Machine Learning in Virology
• +7 more

Nico Pfeifer is a W3 Professor in Computer Science (Methods in Medical Informatics) at the Faculty of Science, University of Tübingen. He leads a research group focused on statistical learning in computational biology, with a strong emphasis on HIV and SARS-CoV-2 antibody dynamics, viral resistance, and machine learning applications in virology. His work bridges computer science and medical informatics, contributing to high-impact therapeutic and diagnostic developments. Educational Background: Dr. rer. nat. in Bioinformatics/Computational Biology, University of Tübingen (2009) M.Sc. in Applied Computer Science, University of Göttingen (2005) B.Sc. in Applied Computer Science (Bioinformatics), University of Göttingen (2004) His research interests include medical informatics, computational biology, machine learning in virology, HIV drug resistance, antibody dynamics, and next-generation sequencing analysis. His work leverages statistical learning and computational modeling to address critical challenges in viral evolution and immune response prediction. The recent publications highlight a strong trend in applying machine learning and bioinformatics to understand HIV-1 and SARS-CoV-2 antibody therapies, viral resistance mechanisms, and immune responses. His research spans computational modeling, clinical data analysis, and translational medical informatics, with a consistent focus on improving viral treatment strategies and diagnostics. Scientific Awards: No specific awards mentioned in the provided text. Nico Pfeifer has been actively involved in advising and collaborative research, particularly in large-scale virology studies involving monoclonal antibodies and viral resistance. His work has been supported through institutional and collaborative grants, especially during his time at the Max Planck Institute and Microsoft Research. He has led significant research projects in computational virology and continues to contribute to high-impact interdisciplinary science. He is associated with the Methods in Medical Informatics research group at the University of Tübingen, where he leads efforts in developing computational tools for viral genomics and antibody response modeling. His team likely includes researchers and students working on machine learning applications in medical informatics and virology.

Marian KrawietzView profile

Research Fellow

• Social Inequality
• Political Participation
• Voting Behavior
• +3 more

Dr. Marian Krawietz serves as a Research Fellow at the University of Potsdam within the Chair of Methods of Empirical Social Research. Employed since 2012 and holding her current position since 2018, she specializes in applying quantitative methodologies to sociological and political phenomena across European contexts. Her academic foundation includes: Studies in history, sociology, and Eastern European history at the Universities of Bonn, Cologne, and Poznan Doctoral degree from Hanover University examining cross-national value shifts following the Berlin Wall's collapse in Germany, Czech Republic, and Poland Research focuses intensively on: Social stratification and inequality mechanisms Voter/non-voter dynamics in democratic systems Historical sociology of post-communist transitions Educational pathway disparities Methodological innovation in survey research She directs German Research Foundation (DFG) projects analyzing GDR-era participation structures and currently leads three major initiatives: "Social Inequality of Participation," "Influence of non-voters," and "EDUCHANGE: Changing Inequality at Educational Transitions." Her technical expertise includes advanced web scraping techniques documented in university teaching materials. Dr. Krawietz actively supervises undergraduate and graduate theses while maintaining regular consultation hours via Zoom for student engagement.

• Mathematics
• Stochastics
• Analysis
• +5 more

Maximilian Hettmann is a researcher at the Faculty of Mathematics, University of Bielefeld, Germany. He is based in Gebäude X E1-290 and can be reached via phone at +49 521 106-4683. His work is situated within Bielefeld's strategic research area of The Mathematical World , which emphasizes fundamental and applied mathematics, particularly in stochastics, analysis, and modeling of complex systems. The Faculty of Mathematics at Bielefeld is internationally recognized for its research excellence, ranked 5th in Germany by the DFG Funding Atlas 2024. It participates in major collaborative projects such as CRC 1283 ( Taming Uncertainty and Profiting from Randomness ), CRC TRR 358 ( Integral Structures in Geometry and Representation Theory ), and IRTG 2235 ( Searching for the Regular in the Irregular ), often in collaboration with institutions like Seoul National University and supported by ERC grants. Research involves spectral structures, topological methods, randomness, low regularity, and mathematical finance. Key affiliated institutes include the Institute of Mathematical Economics (IMW) and the Research Centre for Mathematical Modeling (RCM²). While specific details about Dr. Hettmann’s publications, advisees, or awards are not available in the current text, his institutional context places him at the forefront of interdisciplinary mathematical research aimed at solving open problems in economics and the natural sciences.

• Partial Differential Equations
• Nonlocal Problems
• Regularity Theory
• +3 more

Dr. Ho-Sik Lee is a researcher affiliated with the Faculty of Mathematics at Bielefeld University, specializing in partial differential equations, nonlocal problems, and regularity theory. He contributes to projects within the International Research Training Group 2235 and the Bielefeld Graduate School in Theoretical Sciences. Faculty of Mathematics, Bielefeld University Bielefeld Graduate School in Theoretical Sciences International Research Training Group 2235 His research focuses on advanced mathematical analysis of nonlinear and nonlocal equations, including degenerate weights, mixed local/nonlocal operators, and regularity estimates for problems arising in calculus of variations and applied contexts. Recent work explores the Zaremba problem, fractional p-Laplacian, kinetic Fokker-Planck equations, and double phase functionals. Analysis of his 15 most recent publications (2023–2025) reveals expertise in parabolic equations, nonlocal diffusion, Hölder continuity, gradient estimates, and weighted Sobolev spaces. These works intersect with mathematical physics, functional analysis, and applications in nonlinear dynamics.

• Ultrafast Laser Spectroscopy
• Biophysical Chemistry
• Molecular Dynamics
• +7 more

Prof. Dr. Joachim Heberle is a Subproject Leader (C5) in the Collaborative Research Centre (CRC) 1349 Fluorine-Specific Interactions: Fundamentals and Applications at Freie Universität Berlin. He is affiliated with the Institute of Experimental Physics within the Department of Physics, Faculty of Mathematics and Natural Sciences. His research focuses on advanced spectroscopic techniques to study dynamic processes in biological and chemical systems, particularly involving fluorine-specific interactions and photoactive proteins. His research interests lie at the intersection of physics and chemistry, with a strong emphasis on ultrafast laser spectroscopy , molecular dynamics , and biophysical chemistry . He investigates light-induced processes in proteins and synthetic systems, leveraging time-resolved methods to probe structural and electronic changes on femtosecond to millisecond timescales. His work contributes to understanding fundamental mechanisms in photobiology and chemical physics , particularly in the context of fluorinated environments, which are increasingly important in materials science and medicinal chemistry. The absence of listed publications in the provided text prevents a detailed trend analysis; however, his role in a DFG-funded CRC subproject suggests active contributions to high-impact interdisciplinary research in physical chemistry and spectroscopy. Scientific Awards: No awards listed in the provided text. As a subproject leader in CRC 1349, Prof. Heberle is involved in guiding research, mentoring early-career scientists, and managing collaborative projects within the Integrated Research Training Group (MGK). While specific grants and students are not listed, his leadership position implies active participation in research funding acquisition and academic supervision. He works within a large, interdisciplinary consortium focused on fluorine chemistry, involving multiple principal investigators across Berlin institutions. Prof. Heberle is part of the research team in CRC 1349 at Freie Universität Berlin, contributing to subproject C5. His work is embedded in a structured, collaborative environment that includes graduate training, regular workshops, and interdisciplinary exchange. The CRC provides a comprehensive framework for fundamental and applied research on fluorine-specific interactions, positioning his lab at the forefront of spectroscopic and mechanistic studies in this domain.