Find Academic Supervisors

• Mathematical Statistics
• Applied Statistics
• Probability Theory
• +6 more

Holger Dette is a Professor and Chair Holder of Stochastics (specializing in Statistics) at the Faculty of Mathematics, Ruhr University Bochum. He leads the prominent Group Dette within the Institute of Statistics, overseeing a team of researchers, doctoral students, and administrative staff including Birgit Tormöhlen as team assistant. His research group is deeply integrated within the university's mathematical ecosystem, collaborating with other research groups across algebra, analysis, numerics, and topology. Dette's research spans mathematical statistics with strong applications in real-world problems. His primary interests include optimal experimental design, time series analysis, functional data, change point problems, nonparametric regression, biostatistics, special functions, goodness-of-fit tests, and random matrices . His work bridges theoretical statistics with practical applications, particularly evident in his collaborations with pharmaceutical giants Novartis and Bayer AG in biostatistics, as well as Quasol, a spin-off company from his statistics institute. His recent publications (2024-2025) reveal a research program increasingly focused on high-dimensional and functional data analysis, privacy-preserving statistics, and novel methodological approaches to longstanding statistical problems. Dette's work shows strong interdisciplinary connections, particularly with biomechanics (analyzing joint angles during fatigue phases) and data science (addressing challenges in the era of big data). His research group is actively involved in multiple DFG-funded projects including the newly established 'Small Data' collaborative research center (Sonderforschungsbereich 1597) and the Spatio-temporal Statistics for the Transition of Energy and Transport (Transregio 391). Dette has received significant recognition including the prestigious Humboldt Research Award . His paper 'With Great Power Come Great Side Channels: Statistical Timing Side-Channel Analyses with Bounded Type-1 Errors' achieved second place at the CSAW'24 Applied Research Competition MENA. His research group has also secured multiple significant funding awards from the German Research Foundation (DFG). As an advisor, Dette supervises numerous doctoral and master's students including Pascal Quanz, Marius Kroll, and Carina Graw. His group offers statistical consulting services for scientists and students across bachelor's, master's, and doctoral phases. The group maintains strong industrial partnerships, particularly in biostatistics applications, demonstrating Dette's commitment to translating theoretical statistics into practical solutions for real-world challenges.

Jilles VreekenView profile

Professor

• Causal Inference
• Unsupervised Learning
• Exploratory Data Analysis
• +7 more

Jilles Vreeken is a Professor of Computer Science at Saarland University and tenured faculty at the CISPA Helmholtz Center for Information Security, where he leads the Exploratory Data Analysis research group. He is also an ELLIS Fellow and Faculty of the Saarbrücken Unit on AI and ML. His work bridges theoretical foundations with practical applications in causal inference, unsupervised learning, and exploratory data analysis. Dr. Vreeken's research focuses on developing theory and algorithms for answering fundamentally exploratory questions about data: "what is going on in my data?", "what causes what and how?", and "what can we learn from this model?" without making unnecessary or unjustified assumptions. He takes a principled approach based on information theory to identify what is worth knowing, then develops efficient algorithms for extracting useful interpretable results. His work spans causal inference under realistic conditions (including hidden confounding, selection bias, and non-i.i.d. data), summarizing complex data and models in understandable terms, and combining these threads to create more robust and useful models across diverse data types. His recent publications demonstrate a strong trend toward causal discovery in increasingly realistic settings, including non-stationary time series, event sequences, and scenarios with hidden confounders. He has made significant contributions to federated learning, interpretable machine learning, and pattern mining. His work consistently applies information-theoretic principles to develop methods that are both theoretically sound and practically useful for extracting insights from complex data. Dr. Vreeken has received numerous prestigious awards including: IEEE ICDM'18 Tao Li Award for Excellence in Research IEEE ICDM'18 Best Paper Award UdS-CS'15 Busy Beaver Teaching Award ACM SIGKDD'11 Best Student Paper Award ACM SIGKDD'10 Doctoral Dissertation Runner-Up Award ECML PKDD'09 Best Student Paper Award As an advisor, Dr. Vreeken has mentored numerous doctoral researchers to completion, including Dr. Osman Ali Mian, Dr. David Kaltenpoth, Dr. Boris Wiegand, Dr. Sebastian Dalleiger, Dr. Janis Kalofolias, Dr. Jonas Fischer, Dr. Alexander Marx, Dr. Panagiotis Mandros, Dr. Kailash Budhathoki, Dr. Roel Bertens, Dr. Koen Smets, and Dr. Michael Mampaey. He has secured significant research funding as PI for multiple projects including "AI for Prediction and Therapy Guidance in Acute Stroke" (HAICU, 2025-2028), "Neuro-Explicit Models of Language, Vision and Action" (RTG, DFG, 2023-2028), and "Crushing Antimicrobial Resistance using Explainable AI" (HAICU, 2021-2024). Dr. Vreeken leads the Exploratory Data Analysis (EDA) research group at CISPA, which focuses on developing theory and algorithms for discovering novel insights from data, learning inherently interpretable models, and drawing reliable causal conclusions. The group has produced numerous influential algorithms and frameworks in causal inference, pattern mining, and exploratory data analysis, with applications spanning healthcare, materials science, and cybersecurity.

Lifeng ChiView profile

Professor

• Supramolecular Chemistry
• Surface Science
• Nanomaterials
• +5 more

Prof. Dr. Lifeng Chi is a Chair Professor at Soochow University's Institute of Functional Nano & Soft Materials and an Adjunct Professor at the University of Münster. She holds a Hans Fischer Senior Fellowship at the Technical University of Munich Institute for Advanced Study (TUM-IAS) since 2019, where she leads the focus group on 'Molecular assemblies and covalent nanostructures on wide bandgap semiconductor surfaces'. Education B.S. and M.S. from Jilin University, China Ph.D. from University of Göttingen, Germany (1989) Habilitation from University of Münster, Germany (2000) Research Focus Her research spans three core areas: On-Surface Chemical Reactions including selective C-H bond activation and C-C coupling; Molecular Self-Assembly exploring chiral structures and covalent bonding; and Interfacial Engineering developing functional molecular architectures for sensing applications. Her work combines nanoscale fabrication with fundamental surface chemistry to create advanced functional materials. Publication Trends Over 370 publications demonstrate consistent focus on surface molecular phenomena, with recent work (2021-2025) emphasizing catalytic surface reactions, semiconductor interfaces, and molecular electronics. Earlier breakthroughs include alkane polymerization on gold surfaces and chiral network engineering, establishing foundational techniques in surface chemistry. Scientific Awards IUPAC Distinguished Women in Chemistry/Chemical Engineering (2017) ACS Nano Lectureship Award (2016) Molecular Science Frontier Lecture Professorship (2016) Distinguished Innovation Scientist, Jiangsu (2013) Lisa Meitner Scholarship (1997) Leadership & Labs Directs the Institute of Functional Nano & Soft Materials at Soochow University, overseeing research in molecular assembly and surface engineering. At TUM-IAS, collaborates with Prof. Johannes Barth and Prof. Martin Stutzmann on semiconductor surface modifications.

Stephanie PanierView profile

Research Professor

• Genome Stability
• DNA Damage Response
• Aging Research
• +4 more

Dr. Stephanie Panier serves as a Max Planck Research Group Leader at the Max Planck Institute for Biology of Ageing in Cologne, Germany, and as a Principal Investigator at the Institute for Genome Stability in Aging and Disease within the Medical Faculty of the University of Cologne. Her research program investigates the fundamental mechanisms by which cells maintain genome stability through sophisticated DNA damage response pathways. Her academic journey includes: PhD in Molecular Genetics from the University of Toronto (2008-2013) under Prof. Daniel Durocher Postdoctoral training at the Francis Crick Institute in London (2013-2019) with Prof. Simon Boulton Undergraduate studies in Biology at Ruprecht-Karls-Universität Heidelberg, Germany (2001-2006) Dr. Panier's laboratory focuses on two central questions in genome stability research: how DNA damage response pathways interact with telomere maintenance mechanisms, and how RNAs and RNA-binding proteins organize chromatin-based responses to DNA lesions. Her team employs cutting-edge cell biological and omics approaches to identify and characterize RNA-binding proteins at DNA damage sites, mapping their chromatin dynamics and interactions following genotoxic stress. This research has significant implications for understanding aging-associated diseases driven by genomic instability, including cancer and neurodegeneration. Analysis of her publication record reveals consistent contributions to understanding DNA repair mechanisms, with recent work expanding into cancer biology, telomere maintenance in alternative lengthening pathways, and the emerging role of RNA metabolism in genome stability. Her scientific achievements have been recognized through: Vivash Award for best PhD thesis (2013) FEBS Excellence Award (2023) EMBO Long-Term Fellowship (2013-2014) Vanier Canada Graduate Scholarship (2010-2013) Boehringer Ingelheim Fonds PhD Fellowship (2008-2010) EIRR21st Fellowship (2023) Dr. Panier actively contributes to the scientific community through leadership roles including Vice Coordinator of the DFG Research Unit FOR5504 (2023-2026), membership on the advisory board of the German Society for Research on DNA Repair since 2022, and representation on the Biology and Medicine Section of the Max Planck Society's scientific council since 2022. She also serves as a Principal Investigator in the Cologne Excellence Cluster 'Cellular Stress Responses in Aging-Associated Diseases' (CECAD). Her laboratory comprises postdoctoral researchers and PhD students working collaboratively to advance our understanding of genome stability mechanisms in aging, with current projects focusing on RNA-binding proteins in DNA damage response and telomere maintenance pathways.

Mircea RasteiView profile

Assistant Professor

• Ferroelectric materials
• Nanomaterials characterization
• Atomic force microscopy
• +7 more

Mircea Rastei is an Assistant Professor in the Department of Organic Materials (DMO) at IPCMS (Institut de Physique et Chimie des Matériaux de Strasbourg), University of Strasbourg. His research focuses on the electronic, magnetic, optical, and quantum mechanical properties of nanostructures using advanced atomic force microscopy techniques. Dr. Rastei's primary research interests include light-matter interaction, local photovoltaic effects, inversion symmetry breaking-driven charge generation, ferroelectric materials for data storage, and the discretization of interactions between solid-state nanostructures. His work bridges fundamental physics with practical applications in nanotechnology and materials science. His recent publications (2020-2025) demonstrate a consistent focus on ferroelectric Bi 2 FeCrO 6 thin films, photovoltaic effects, magnetic properties of nanoparticles, and advanced atomic force microscopy techniques. The research spans multiple disciplines including condensed matter physics, materials science, and nanotechnology, with significant contributions to understanding nanoscale phenomena. Dr. Rastei actively supervises PhD students including Antoine Bagard (2024), X. Henning (2024), M. D. Pichois (2022), and M. A. Hurier (2021), guiding research in ferroelectric materials, photovoltaic effects, and nanoscale characterization techniques. His laboratory features two specialized Atomic Force Microscopes coupled with wavelength-tunable lasers for optical excitation studies from 350-900 nm, enabling advanced photoinduced force microscopy/spectroscopy techniques (hν-CAFM, hν-KPFM, hν-PFM, PiFM-vis).

Olga SmirnovaView profile

Professor

• Nonlinear Optics
• Attosecond Science
• Strong-Field Physics
• +4 more

Prof. Olga Smirnova is a leading researcher at the Max Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, heading the Strongfield Theory Group. Her work focuses on ultrafast phenomena, attosecond science, and quantum control in strong laser fields. She specializes in chiral dynamics, valleytronics, and high-harmonic generation, with contributions to understanding spin polarization and enantiosensitivity in molecular systems. Research interests include manipulating light-matter interactions at attosecond timescales, exploring topological photonics, and developing novel spectroscopic techniques like TACOS (Terahertz-Assisted Chiro-Optical Spectroscopy). Her theoretical advancements bridge fundamental physics and applications in chiral discrimination, ultrafast imaging, and valleytronics in 2D materials. Recent studies highlight discoveries such as multi-THz quantum beats in superfluorescent emission and polarization-shaped control of valley polarization in MoS 2 . Her work frequently interfaces with experimental groups, driving advancements in free-electron laser technologies and attosecond interferometry. Awards: Ahmed Zewail Award in Ultrafast Science and Technology (2020) Collaborations: Extensive international partnerships with institutions like DESY, Lund University, and the University of Rostock. Labs/Groups: Strongfield Theory Group at MBI, focusing on theoretical and computational modeling of ultrafast processes in intense laser fields.

Frieder LadischView profile

Associate Professor

• Quantum Physics
• Quantum Information
• Photonics
• +2 more

PD Dr. Frieder Ladisch serves as an Associate Professor at the Institute for Mathematics within the Faculty of Mathematics and Natural Sciences at the University of Rostock, Germany. His institutional affiliation includes membership in the Geometry working group (AG Geometry), with office location at Ulmenstraße 69, Haus 3, Room 231, and contact via university email and phone. His research program centers on Quantum Physics and Quantum Information , with specialized expertise in: Non-Hermitian quantum systems and PT-symmetry phenomena Topological photonic implementations including Su-Schrieffer-Heeger lattices Non-Abelian geometric phases and quantum holonomy Quantum random number generation using solid-state photon sources Experimental quantum optics with integrated photonic circuits Analysis of his 15 most recent publications (2019-2025) reveals consistent focus on PT-symmetry breaking experiments, quantum walk implementations in topological photonic structures, and quantum random number generation using hexagonal boron nitride emitters. His work bridges theoretical non-Hermitian quantum mechanics with practical photonic implementations. Dr. Ladisch operates within the Geometry working group at Rostock's Institute for Mathematics, where his research integrates mathematical geometry concepts with quantum information processing through photonic chip technologies and single-photon source applications.

• Theoretical Chemistry
• Quantum Chemistry
• Molecular Physics
• +6 more

R. Berger is a Professor at the Department of Chemistry , Philipps-University Marburg , leading the Theoretical Chemistry research group (AG Berger). He has been actively involved in teaching and research since at least 1998, with a focus on theoretical chemistry, computational spectroscopy, and fundamental symmetry tests. Active in symposium organization (e.g., Symmetries in Science Symposium XX, 2025) Hosts doctoral candidates in his group (Mihnea Mlak-Mărginean, Namrata Gohain, Kjell Janke) Develops theoretical frameworks for parity violation, relativistic effects, and chiral systems His research spans quantum chemistry for fundamental physics experiments, including parity-violating energy differences , laser cooling of molecules, and electroweak effects in molecular systems. Recent publications highlight studies on radioactive molecules (RaF, AcF) and highly charged ions for precision tests of fundamental symmetries. Key scientific awards include the 2008 Hellmann Award and the 2012 Outstanding Young German Investigator Award Lectureship . He collaborates internationally with institutions like CERN , ETH Zurich , and University of Mainz .

• Computational Algebra
• Finite Group Theory
• Combinatorics
• +7 more

Alice Niemeyer is a Professor at the Algebra Teaching and Research Area of RWTH Aachen University , specializing in computational algebra, finite group theory, and interdisciplinary applications in civil engineering. She has co-authored over 30 publications in journals like PNAS Nexus , Linear Algebra and Its Applications , and International Journal of Solids and Structures , with recent work bridging abstract algebra and topological interlocking concrete systems. Research Interests : Finite groups, matrix decomposition algorithms, combinatorial design, and applications to sustainable construction. Key Collaborators : Cheryl Praeger, Tomasz Popiel, Wilhelm Plesken, Daniel Robertz, Reymond Akpanya. Notable Grants : Funding from the Simons Foundation for computational algebra research. Awards : No explicit awards mentioned in the provided text.

Peter SollichView profile

Professor

• Non-equilibrium statistical physics
• Soft matter rheology
• Active matter
• +7 more

Prof. Dr. Peter Sollich is a Professor of Theoretical Physics at Georg-August-Universität Göttingen, affiliated with the Institute for Theoretical Physics. His research spans non-equilibrium statistical physics with applications to soft matter, active systems, and complex networks. He maintains a small part-time appointment at King's College London. His primary research interests focus on non-equilibrium statistical physics , particularly soft and active matter rheology, jamming transitions, glassy dynamics, dynamical phase transitions, and inference from dynamical data. His work bridges theoretical physics with applications in materials science and network theory, emphasizing both fundamental mechanisms and quantitative modeling approaches. Analysis of his recent publications reveals strong thematic consistency in studying glassy dynamics and active matter systems , with increasing integration of machine learning techniques for network analysis. Key methodological threads include coarse-grained modeling, spectral analysis of complex systems, and non-equilibrium thermodynamics frameworks. His 2023-2025 work shows growing emphasis on nonreciprocal interactions in active mixtures and physics-inspired machine learning applications. Prof. Sollich actively supervises Bachelor's, Master's, and PhD students, welcoming thesis inquiries in theoretical physics. His group develops analytical and computational approaches to complex dynamical systems, with recent grants likely supporting work on network dynamics and active matter modeling (specific grants not detailed in source text). His research group operates within the Institute for Theoretical Physics at Göttingen, focusing on computational and analytical modeling of disordered systems. Current projects involve elastoplastic modeling of amorphous solids, spectral analysis of heterogeneous networks, and theoretical frameworks for active matter phase separation.

• Econometrics
• Financial Economics
• Time Series Analysis
• +2 more

Karsten Schweikert is a Professor at the Computational Science Hub (CSH) and an affiliate scientist at the Institute for Economics at Stuttgart University of Applied Sciences. He leads the Data and Statistical Consulting module and teaches the Financial Econometrics Seminar . Academic Rank: Professor Department: Institute for Economics Key Affiliation: Computational Science Hub (CSH) His research focuses on econometrics , financial economics , and time series analysis . He specializes in structural breaks, dynamic factor models, cointegration, and market microstructure. Recent work includes studies on integrated variance estimation, price discovery mechanisms, and urban crime forecasting. The 15 most recent publications highlight his expertise in econometric modeling for financial markets, macroeconomic nowcasting, and applied statistics. Key subfields include structural break detection, mixed-frequency data analysis, and market information share estimation. He leads statistical consulting initiatives and teaches advanced econometrics topics. No scientific awards or student advisement information were explicitly mentioned in the provided texts.

Johann OstmeyerView profile

Researcher

• Condensed Matter Theory
• Lattice Gauge Theory
• Quantum Computing
• +4 more

Johann Ostmeyer is a post-doctoral researcher at the Helmholtz Institute for Radiation and Nuclear Physics at the University of Bonn. He holds a PhD and MSc in Physics from the University of Bonn (2021 and 2018, respectively). His research focuses on Condensed Matter Theory , Lattice Gauge Theory , and Quantum Computing . Key interests include developing Monte Carlo algorithms to address the fermion sign problem , studying quantum spin chains , and simulating organic molecular semiconductors . He also explores Hamiltonian lattice formulations and algorithmic optimization for high-precision simulations. Recent work includes advancements in radial updates for ergodicity, Fourier acceleration for autocorrelation reduction, and high-precision studies of charge transport in organic materials. His methods bridge theoretical frameworks with computational efficiency, addressing challenges in quantum many-body systems. Awards: Mario Markus Prize for Ludic Science (2022) Pineapple Science Award in Physics (2021) Initiativ-Preis der Universitätsgesellschaft Bonn (2021) His GitHub repositories showcase contributions to quantum Monte Carlo , lattice field theory , and machine learning applications . Collaborations include work on the Thirring model with domain wall fermions and Trotter decomposition optimizations for classical/quantum computing.

• Multivariate time series analysis
• Statistical analysis and modelling of energy commodities
• Time series forecasting
• +3 more

Professor Dr. Stephan Schlüter leads the Research Group for Applied Mathematics for Energy Markets at THU (Technische Hochschule Ulm). His expertise spans multivariate time series analysis, statistical modelling of energy commodities, and forecasting renewable energy systems. Co-Editor, Spatial Information Research Teaching: Advanced Mathematics, Operations Research, Stochastics, Applied Time Series Analysis Research focuses on: Electricity and gas price forecasting using neural networks and Bayesian models Climate anomaly detection via satellite data and AI Energy market optimization with battery storage and hydrogen integration Environmental statistics linking CO2 fluxes with economic indicators Recent publications emphasize regime-aware forecasting, uncertainty quantification, and interdisciplinary climate-energy policy analysis. Supervising PhD candidates Abhinav Das and Erick Michel Lara Pinal, plus Master's students Martin Neumann and Andreas Lebedev.

• Time Series Econometrics
• Cointegrated VAR Models
• Structural VAR/VECM Models
• +3 more

Professor Ralf Brüggemann is a full-time faculty member at the University of Konstanz , holding the Chair of Statistics and Econometrics since October 2007. He completed his Habilitation in Time Series Econometrics at Humboldt-Universität zu Berlin in 2007 and received his Ph.D. in Economics in 2003 for work on VAR model reduction techniques. Education : Habilitation: "Topics in Time Series Econometrics", Humboldt University Berlin (2007) Ph.D.: Economics, Humboldt University Berlin (2003) Diplom: Economics, Humboldt University Berlin (1999) His research spans Time Series Econometrics with focus on Cointegrated VAR Models , Structural VAR/VECM , Forecasting Methods , and Empirical Macroeconomics . Key contributions include methodological work on structural identification, variable selection in high-dimensional VAR, and monetary policy analysis using microeconomic data. Recent publications address External instruments in SVAR identification (2022) Directed graphs for VAR variable selection (2022) Stochastic aggregation weights in forecasting (2023) Asymmetric impulse responses in European financial markets (2014) with methodological innovations in heteroskedasticity-robust inference and stochastic aggregation weights. Scientific Awards : Jean Monnet Fellow, European University Institute (2003-2004) He leads research on monetary policy transmission mechanisms and macroeconomic risk through collaborative projects with institutions like the German Research Foundation Collaborative Research Center 649 (2005-present) and serves as editor for the Journal of Economics and Statistics special issue on Economic Forecasts (2011).

Dominik WiedView profile

Professor

• Statistics
• Financial Econometrics
• Portfolio Management
• +5 more

Dominik Wied is a Professor of Statistics and Econometrics at the Faculty of Management, Economics and Social Sciences at the University of Cologne. Previously, he held positions as Assistant Professor (2011–2016) and Visiting Professor (2015–2016) at TU Dortmund. His research focuses on Financial Econometrics , Structural Breaks , and Microeconometrics , with applications in portfolio management and risk assessment. Education: Diploma in Statistics (TU Dortmund, 2008), Ph.D. in Statistics (TU Dortmund, 2009). Affiliations: Institute for Statistics and Econometrics (University of Cologne), ECONtribute Cluster of Excellence (Markets & Public Policy). His recent publications emphasize conditional distribution modeling , structural break detection , and copula-based dependence analysis , particularly in financial and economic contexts. He has contributed to advanced statistical methodologies in time series and spatial modeling, including applications to banking risk assessment and health insurance data. Notable trends in his work include: Developing robust tests for nonlinear endogeneity corrections and quantile regression stability. Advancing factor copula models with exogenous covariates for financial dependence structures. Improving spatial dependence and time series cointegration monitoring techniques. Contact: dwied@uni-koeln.de | Phone: +49 221 470 4514