Find Academic Supervisors

• Statistics
• Stochastic Processes
• Experimental Design
• +6 more

Professor Holger Dette holds the Chair of Stochastics, especially Statistics at the Faculty of Mathematics, Ruhr University Bochum. His research program is centrally focused on advancing statistical theory and methodology through sustained DFG funding. His primary research interests include: Optimal experimental design (both classical and space-time variants) High-dimensional data analysis with bootstrap and sublinear methods Spatial statistics and random field modeling Random matrix theory applications in statistics Covariance structure inference Current research demonstrates strong trends toward computationally efficient methods for complex data structures, particularly in spatial and high-dimensional domains. His work maintains theoretical rigor while addressing interdisciplinary applications in genetics, finance, and material science. Professor Dette actively supervises within major research frameworks: Principal investigator for two Research Groups and multiple In-kind grants Sub-project manager in Collaborative Research Centers (SFB/Transregio) Participating scientist in Cluster of Excellence CASA Former involvement in Graduate School GRK 2131 His research group operates through the Chair of Stochastics, especially Statistics, which serves as the organizational hub for his DFG-funded projects and methodological development.

• Mathematical Statistics
• High-Dimensional Statistics
• Statistical Learning
• +4 more

Professor Angelika Rohde is a faculty member at the University of Freiburg, holding a professorship in the Department of Mathematical Stochastics within the Mathematical Institute. She actively leads multiple German Research Foundation (DFG) projects including Research Group FOR 5381 and Collaborative Research Center sub-projects. Her research specializes in mathematical statistics for high-dimensional data environments, with core expertise in: Computationally feasible bootstrap methodologies Structural inference for covariance matrices under sparsity Discriminant analysis and classification frameworks Statistical inference under randomization constraints Clinical predictive modeling applications Forensic genetics classification systems Current DFG funding supports her leadership in: FOR 5381: Mathematical Statistics in the Information Age (as spokesperson) Integration of multi-site data for clinical predictive models (sub-project manager) Uncertainty quantification in forensic classification (sub-project manager) Prior projects include high-dimensional stochastic differential equations (Priority Program), covariance matrix inference (Research Group), and Graduate School GRK 2131 on high-dimensional stochastics phenomena. She directs the "Mathematical Statistics in the Information Age" research group, fostering interdisciplinary methodological development for modern statistical challenges.

• Resilience Mechanisms
• Clinical Psychology
• Neuropsychology
• +4 more

Michèle Wessa serves as Professor and Head of the Department of Clinical Psychology and Neuropsychology at Johannes Gutenberg University Mainz's University Medical Center, while leading research groups at both the Leibniz Institute for Resilience Research (LIR) and German Resilience Center (DRZ) Mainz since 2020 and 2018 respectively. Her academic credentials include a Dipl.-Psych. from Humboldt University Berlin (2000), Dr. sc. hum. in Neuropsychology from Heidelberg University (2004), and Habilitation in Clinical Psychology (2010). She completed postgraduate Cognitive Behavioral Therapy training (2000-2004) and holds medical licensure. Professor Wessa's research centers on neurobiological and behavioral resilience mechanisms, investigating emotional regulation under stress, reward processing, and cognitive interpretation through biopsychological methods. Her 2021 publications reveal strong emphasis on pandemic mental health impacts, neural stress controllability correlates, and physical fitness-resilience relationships using fMRI, longitudinal monitoring, and intervention protocols. Her scientific recognition includes DFG Emmy Noether funding (2008-present), Lilly Travel Fellowship (2007), and dual scholarships from Studientstiftung des Deutschen Volkes. DFG Emmy Noether research group (We3638/3-1) Lilly Travel Fellowship for 7th International Conference on Bipolar Disorder Ph.D. Scholarship from Studientstiftung des Deutschen Volkes (2000-2003) Study Scholarship from Studientstiftung des Deutschen Volkes (1997-1999) She supervises PhD students Annika Edelmann and Jana Meier while directing major funded projects including ResOn online training and BooSTERIT teacher resilience program, supported by Boehringer Ingelheim Foundation and DFG grants. Her Wessa research group develops evidence-based interventions using blended face-to-face and digital formats to enhance stress resilience across populations.

Johannes KrebsView profile

Professor

• Topological Data Analysis
• Persistent Homology
• Spatial Statistics
• +3 more

Prof. Dr. Johannes Krebs holds the Chair of Mathematics - Statistics at the Faculty of Mathematics and Geography, Catholic University of Eichstätt-Ingolstadt since 2021. His academic service includes membership on the editorial board of Statistics , the tenure track board, examination committees for B.Sc. Mathematics and Data Science programs, and the faculty council. His research focuses on topological data analysis, persistent homology, and spatial statistics with applications in stochastic geometry. Funded by Deutsche Forschungsgemeinschaft (KR 4977/2-1 and KR 4977/1-1), his work bridges theoretical statistics with computational topology to develop novel methods for analyzing complex data structures. His methodological contributions span wavelet analysis, functional data, and bootstrap techniques for dependent data. Analysis of his recent publications reveals strong emphasis on topological inference (persistent homology, Betti numbers), spatial statistics, and wavelet methods across multiple high-impact journals including Bernoulli , Annals of Statistics , and Stochastic Processes and their Applications . His work demonstrates consistent innovation in applying topological concepts to statistical problems with theoretical guarantees. Academic service highlights include: Editorial Board Member, Statistics journal Member of Tenure Track Board Examination Committee for B.Sc. Mathematics & Data Science Faculty Council Member His research program is supported by significant DFG funding for projects on Topological Data Analysis (2021-2023) and Dynamic Objects on Random Fields (2017-2020), reflecting sustained contribution to advancing statistical methodology through topological frameworks. He maintains active collaborations with researchers at UC Davis, KU Leuven, and Heidelberg University.

Agnes FlöelView profile

Professor

• Cognitive Neuroscience
• Sleep Physiology
• Brain Stimulation
• +7 more

Prof Dr Agnes Flöel is a Professor at the University of Greifswald Medical School, where she leads research at the intersection of cognitive neuroscience, sleep physiology, and brain stimulation. Her work focuses on understanding neural mechanisms underlying memory formation and cognitive decline in aging, with particular emphasis on sleep-related processes and non-invasive brain stimulation techniques. Her research interests center on sleep physiology , cognitive neuroscience , and neurostimulation . Dr. Flöel investigates how slow oscillations, spindles, and delta waves interact during sleep to support memory consolidation, particularly in older adults and those with cognitive impairment. Her work extends to developing interventions combining cognitive training with transcranial direct current stimulation (tDCS) to enhance cognitive function in aging and early Alzheimer's disease. She also contributes to methodological advancements in sleep staging through deep learning approaches and addresses technical challenges in neuroimaging. Dr. Flöel's publication record demonstrates consistent productivity with multiple high-impact papers annually, primarily focused on sleep neuroscience, brain stimulation, and cognitive aging. Her work shows strong collaborative patterns with researchers across Germany, particularly within the SFB 1315 research consortium. Recent publications (2022-2024) increasingly incorporate computational approaches, deep learning, and multimodal neuroimaging to address fundamental questions about neural plasticity and memory. Her research has been supported through the Collaborative Research Center 1315 (SFB 1315) funded by the German Research Foundation, focusing on neuronal circuits in aging. Dr. Flöel serves as principal investigator for multiple clinical trials examining brain stimulation approaches for cognitive enhancement in older adults and those with mild cognitive impairment. Dr. Flöel leads a research group investigating sleep-brain interactions in aging, collaborating closely with computational neuroscientists, neurologists, and psychologists. Her team utilizes multimodal approaches including EEG, MRI, and behavioral assessments to understand neural mechanisms of cognitive decline and potential interventions.

Manuel BehrendtView profile

Research Fellow

• Astrophysics
• Computational Astrophysics
• Galaxy Formation and Evolution
• +3 more

Dr. Manuel Behrendt is a Research Fellow at the Ludwig-Maximilians-Universität München, where he serves as a staff scientist at the University Observatory in the CAST-group led by Prof. Andreas Burkert. He also holds a position with the Physics of Galactic Nuclei (PGN) group at the Max-Planck-Institute for Extraterrestrial Physics in Garching, Bavaria. His primary research focuses on the structure-formation and evolution of galactic discs in the early universe, utilizing high-resolution hydrodynamic simulations within the framework of gravitational disc instability. Dr. Behrendt's work addresses fundamental questions about: The formation and evolution mechanisms of giant clumps and small-scale structures in high-redshift galaxies The hierarchical organization of clumps, including whether observed kpc-scale clumps are composed of sub-clump clusters The role of stellar feedback in shaping galactic structure formation and kinematics The energetic sources driving high random motions observed in young galaxies A significant contribution to the field is his development of MERA.jl, a high-performance Julia package designed for analyzing large-scale astrophysical simulation data. This tool provides: Efficient numerical performance through Julia's JIT compilation Unified API for handling multi-resolution AMR grids and particle datasets Interactive development capabilities that scale from notebooks to production scripts Memory-conscious design for processing large datasets Multi-threaded I/O operations for improved performance Dr. Behrendt's publication record demonstrates a consistent research trajectory focused on galaxy formation processes, particularly examining clump structures in high-redshift galaxies. His work bridges theoretical astrophysics with practical computational methods, making important contributions both to our understanding of galaxy evolution and to the development of advanced analysis tools for the broader astrophysics community. As an educator, Dr. Behrendt actively supervises students, teaches tutorials and astrophysical laboratory courses, and serves as a substitute lecturer for Prof. Burkert's courses. His dual commitment to research excellence and educational mentorship highlights his comprehensive contribution to the academic community.

• Health Economics
• Applied Microeconomics
• Medical Innovation
• +4 more

Julian Reif is Associate Professor of Finance and Economics at Gies College of Business, University of Illinois. He maintains significant research affiliations with the National Bureau of Economic Research, J-PAL North America, the Wilson Sheehan Lab for Economic Opportunities, and the Institute of Government and Public Affairs. Professor Reif is an applied microeconomist specializing in health economics, with research focusing on the determinants and value of health. His work examines the health and medical spending effects of air pollution, Medicare Part D impacts on drug utilization, and the value of medical innovation. He serves as Principal Investigator of the Illinois Workplace Wellness Study and as coeditor at The American Journal of Health Economics . His research has been supported by major funding organizations including J-PAL North America, the National Institutes of Health, the National Science Foundation, and the Robert Wood Johnson Foundation. Professor Reif's work has received significant recognition including the Kenneth J. Arrow Award for the best published paper in health economics and the NIHCM Foundation Research Award. Kenneth J. Arrow Award for the best published paper in health economics NIHCM Foundation Research Award for outstanding published work in health care Professor Reif has been featured in major media outlets including The New York Times , The Wall Street Journal , and The Washington Post . His methodological contributions include developing statistical tools like the 'dobatch' command for Stata that enables parallel processing of dofiles. His educational background includes a PhD in Economics from the University of Chicago and a BA from Vanderbilt University, with prior professional experience as a Senior Consultant at Bates White.

Simon ApersView profile

Researcher

• Quantum Algorithms
• Theoretical Computer Science
• Random Walks
• +4 more

Simon Apers is a CNRS researcher at IRIF (Institut de Recherche en Informatique Fondamentale) at Université Paris Cité. He focuses on quantum algorithms with broader interests in theoretical computer science, including random walks, graph theory, and combinatorial optimization. His primary research interests span quantum computing, theoretical computer science, and algorithms. Apers has made significant contributions to quantum walks, quantum property testing, graph algorithms, and computational complexity. His work often bridges quantum information with classical theoretical computer science, exploring how quantum techniques can improve classical algorithms and solve problems more efficiently. He has developed quantum speedups for various computational tasks including sampling, optimization, and graph problems. Simon Apers serves as a program committee member for prestigious conferences including TQC'25, QIP'25, TQC'23, SODA'23, and ESA '21. He also serves as an editor for the journal Quantum. His teaching activities include courses at Sorbonne University (2022-present) on Advanced Quantum Algorithms, MPRI (2021-present) on Quantum Algorithms and Complexity, and Bad Honnef (2022). His publication record shows a strong trend toward quantum algorithms for graph problems, quantum walks, and connections between quantum computing and classical theoretical computer science. He frequently collaborates with researchers from various institutions across Europe and has published in top venues including FOCS, STACS, ESA, PRL, and JMLR. Simon Apers actively mentors students and has open positions for PhD students and postdocs in quantum algorithms at IRIF. His research group is involved in cutting-edge work at the intersection of quantum computing and theoretical computer science, with significant contributions to quantum walks, property testing, and computational complexity.

Michael MayleView profile

Research Professor

• Computational Physics
• Sensor Technologies
• Ultracold Quantum Gases
• +2 more

Michael Mayle is a Research Professor for Applied Computational Physics at Nuremberg University of Applied Sciences. He serves as a member of the Doctoral Center for Physical and Biomedical Engineering (CPaB) and holds a deputy position on the CPaB doctoral committee. His office is located at space KA.434, with contact details including phone +49 (0)911 5880-1309 and email michael.mayle@th-nuernberg.de. His research centers on Computational Physics with specialized focus in Sensor Technologies , Ultracold Quantum Gases , and Acoustics . He leads the Computational Physics for Sensor Technologies research group, developing advanced computational models for physical systems with direct applications in sensor design and analysis. His work bridges theoretical physics with practical engineering solutions. Analysis of his publication trajectory (2006-2025) reveals a distinct evolution from fundamental quantum research to applied sensor technology. Early work (2006-2013) established expertise in ultracold molecules and Rydberg atom physics, while recent publications (2019-2025) demonstrate a strategic pivot toward industrial applications including piezoelectric material analysis, ultrasonic flow metering, and water consumption pattern recognition. Professor Mayle actively contributes to doctoral education through the CPaB framework and teaches core courses including Simulation of Physical Systems (Continuum Mechanics) for M-AMP, Physics (Oscillations and Waves) for B-MED, and Building Physics for B-EGT/B-BI programs. His research group maintains strong industry connections through sensor technology development and applied computational modeling projects.