Dominik Liebl is a Professor of Statistics at the University of Bonn's Department of Economics and a member of the Hausdorff Center for Mathematics (HCM), a Cluster of Excellence funded by the German Science Foundation (DFG). He also holds a visiting associate position at Colorado State University's Department of Statistics. His research spans Functional Data Analysis , Nonparametric Statistics , and Longitudinal Data Analysis , with applications in energy economics, finance, e-commerce, emotion psychology, and biomechanics. Recent methodological work focuses on simultaneous inference and statistical fairness . The articles in his profile demonstrate a strong emphasis on functional data methodologies applied to diverse domains like COVID-19 seroprevalence , electricity markets , and human movement science . Key subfields include confidence band design , biomechanical hypothesis testing , and high-dimensional econometric modeling . He actively contributes to open science through R-packages at CRAN/GitHub and serves as Associate Editor for the Journal of the Royal Statistical Society: Series C.
Prof. Jörn Ostermann is a Full Professor and Head of the Institut für Informationsverarbeitung at Leibniz Universität Hannover since 2003, with prior roles at AT&T Bell Labs and AT&T Labs-Research. He served as Dean of the Faculty of Electrical Engineering and Computer Science (2011–2013) and member of the Senat (since 2020). His research spans video coding, computer vision, machine learning, 3D modeling, and computer-human interfaces , with applications in SAR imaging, predictive maintenance, children's speech analysis, and cochlear implants. Key projects include Next Generation Video Coding , Conditional Coding for Learned Compression , and GreenAutoML4FAS . Notable trends in his recent publications (2025–2023) include Neural network-based video compression Uncertainty estimation in speech recognition Zero-delay coding for cochlear implants Domain adaptation for aerial image segmentation 3D mesh compression standards Error concealment in VVC coding Scientific recognitions: AT&T Standards Recognition Award (1998) ISO Award (1998) IEEE Fellow (2005) Distinguished Lecturer, IEEE CAS Society (2002/2003) MPEG Convenor (2020–2023) He co-authored a graduate textbook on Video Communications , holds >30 patents, and has led >20 research projects. His work bridges academic research and industrial standardization, particularly in MPEG and IEEE committees.
Dr. Michael Gentner is a researcher at the Institute of Optimization and Operations Research, Ulm University, where he teaches courses including Angewandte Diskrete Mathematik (Combinatorics) and Advanced Discrete Algorithms. His institutional contact details include office Helmholtzstr. 18, Room 1.47, with Thursday office hours (14:00-16:00) and phone number +49 731 50-23637. His primary research focuses on structural graph theory and combinatorics, with expertise in domination theory, independence number, zero forcing sets, and extremal graph problems. Gentner investigates properties of graphs through degree sequences, clustering coefficients, and dynamic monopolies, particularly in specialized graph classes like forests and graphs without short cycles. Analysis of his 2015-2018 publications reveals consistent emphasis on establishing bounds and extremal values for graph invariants. His work bridges theoretical combinatorics with applications in network science, frequently collaborating with Dieter Rautenbach and other researchers in the field. Scientific Awards No scientific awards or honors were mentioned in the provided information. Advising and Grants No details regarding student supervision, PhD advisees, or research grants were found in the source material. Labs and Teams Gentner operates within Ulm University's Institute of Optimization and Operations Research, though specific laboratory structures or research team compositions are not detailed in the available text.
Stefan Kratsch is a Professor of Theoretical Computer Science at the Institute of Computer Science, Humboldt University of Berlin. He holds this position since September 2017 and has previously held academic roles at the University of Bonn (2015–2017) and Technical University Berlin (2012–2014). His research focuses on parameterized complexity, efficient preprocessing, and computational complexity, with a strong emphasis on theoretical foundations and algorithm design. University: Humboldt University of Berlin Department: Institute of Computer Science (Algorithm Engineering group) Academic Rank: Professor Email: stefan.kratsch@hu-berlin.de, kratsch@informatik.hu-berlin.de Kratsch’s recent publications highlight his work on advanced algorithmic techniques for graph problems. Key areas include kernelization methods, flow-augmentation for connectivity problems, and tight complexity bounds for classical problems parameterized by structural measures like clique-width and cutwidth. His theoretical contributions aim to bridge preprocessing efficiency with computational hardness. Stefan actively engages in academic service, including organizing workshops and serving on program committees for leading conferences such as IPEC, LATIN, and SWAT. He has reviewed for numerous journals and grant panels, including the European Research Council and German Research Foundation. Advising: He supervised PhD candidate Michael Piechotta, whose defense is scheduled for September 2025.
Sharat Ibrahimpur is a Postdoctoral Researcher at the Research Institute for Discrete Mathematics (University of Bonn, Germany). His research focuses on approximation algorithms for combinatorial optimization problems, with recent emphasis on stochastic optimization in network design, scheduling, and caching systems. Previously, he held postdoctoral positions at the London School of Economics (Mathematics Department) and Google Research (Discrete Algorithms Group). Education: PhD and M.Math in Combinatorics and Optimization (University of Waterloo), B.Sc. in Applied Mathematics (IIT Roorkee) Advisor: Chaitanya Swamy (University of Waterloo) Research interests span network design , load balancing , caching , and stochastic optimization . His publications in venues like IPCO , ICALP , and MathProg demonstrate expertise in primal-dual methods, independent rounding, and uncrossable functions. Key collaborations include Vera Traub, László Végh, and Manish Purohit.
Pascal Maillard is a Professor at the Department of Mathematics at Université Toulouse III - Paul Sabatier, affiliated with the Institut de Mathématiques de Toulouse (CNRS UMR5219). He has been a Junior member of the Institut Universitaire de France since October 2021. His research focuses on probability theory, particularly branching random walks, multiplicative cascades, and random energy models, with applications in statistical mechanics and mathematical physics. Maillard has coordinated the ANR-DFG funded project REMECO (2021-2024), investigating extreme value distributions, partition functions at complex temperatures, and optimization algorithms in random energy models. He has also co-organized the annual 'Les probabilités de demain' conference (2016–2019) to support early-career researchers in probability. His teaching spans advanced modules in stochastic modeling, probability theory, and mathematical statistics at both undergraduate and graduate levels. He is currently developing lecture notes on branching random walks and multiplicative cascades based on his Master's course at Université Paris-Sud. Research Interests: Extremal processes in branching systems, random energy landscapes, stochastic optimization, and applications to statistical physics. Awards: Junior member of Institut Universitaire de France (2021–present). Advising: Supervised three PhD students and multiple research projects in probability theory, including studies on SLE, Markov chain mixing times, and Erdős-Rényi graphs. Labs/Teams: Co-lead of REMECO project with Lisa Hartung, involving institutions in Toulouse and Mainz.
Yury Person is a University Professor and Head of the Large Networks and Random Graphs Group at Technische Universität Ilmenau's Department of Mathematics. He previously served as Endowed Junior Professor at the Carl Zeiss Foundation (2018–2021) and Junior Professor of Discrete Mathematics and its Applications at Goethe University Frankfurt (2013–2018). His research focuses on identifying patterns in large discrete structures, leveraging the interplay of structure and randomness, with applications in computer science, particularly property testing. Education: Mathematics Degree from Technical University of Munich; PhD in Computer Science from Humboldt University of Berlin (2010) PostDoc: Institute of Mathematics at Free University of Berlin Research interests include discrete mathematics, random graph theory, and algorithm design. He has conducted research stays at institutions like the Institute for Pure and Applied Mathematics (Los Angeles), Hebrew University Jerusalem, and Universidade de São Paulo. Recognized for teaching excellence, he was nominated for the 1822 University Award for Excellence in Teaching in 2017. Professional contributions include a fellowship in the Main-Campus-educator program (2014–2016) and leadership of the Large Networks and Random Graphs Group at TU Ilmenau.
Prof. Dr. Peter Bürgisser is a Professor at the Technical University of Berlin, affiliated with the Institute of Mathematics and the Algorithmic Algebra research group within Faculty II - Mathematics and Natural Sciences. His research focuses on algebraic complexity theory, computational algebra, and geometric methods in computer science. Bürgisser has made significant contributions to topics including invariant theory, numerical analysis of algorithms, and the computational complexity of algebraic problems. He has authored influential books such as *Algebraic Complexity Theory* and has published extensively in top-tier journals like the Journal of the ACM and SIAM Journal on Computing. His work includes developing polynomial-time algorithms for problems in invariant theory, analyzing the condition numbers of algebraic varieties, and studying the computational aspects of semialgebraic sets. Bürgisser's research also intersects with probability theory, particularly in understanding the statistical properties of zeros of random polynomials and the geometry of random algebraic varieties. Recent trends in his publications emphasize geometric complexity theory, non-commutative optimization, and the application of numerical methods to algebraic problems. He has collaborated with researchers such as Felipe Cucker, Michael Walter, and Avi Wigderson on foundational topics in computational mathematics and theoretical computer science. Bürgisser's office is located in room EB 116, and his contact information includes the email pbuerg@math.tu-berlin.de. His research has been supported through grants and collaborations, though specific grant details are not explicitly mentioned in the provided texts.
Vincent Guirardel is a Researcher at the Rennes Institute for Research in Mathematics (IRMAR) within the University of Rennes 1. He specializes in Geometric Group Theory, focusing on hyperbolic groups, group actions on trees, and JSJ decompositions. His research explores topics such as boundary amenability, automorphism groups, and the interplay between algebraic structures and geometric properties. Teaching responsibilities include the 'Mathematical Tools 2' course (OM2) for first-year students, emphasizing Markov chains, martingales, and linear algebra. He has developed course materials, tutorials, and organized workshops like 'Maths in jeans.' Distance learning resources, including video lectures and problem sets, are hosted on Moodle. Key research contributions include studies on hyperbolically embedded subgroups, rotating families in hyperbolic spaces, and the isomorphism problem for hyperbolic groups. His work often involves collaborations with leading mathematicians like Mladen Bestvina and Gilbert Levitt. Publications span over two decades, with notable contributions to Annals of Mathematics, Geometry & Topology, and Memoirs of the AMS. Recent preprints address boundary amenability of Out(Fₙ) and vastness properties of automorphism groups of RAAGs. His academic activities include advising on curriculum design and maintaining an active presence in geometric group theory through conferences, workshops, and editorial work.
Erika Roldán Roa is a mathematician with academic affiliations at Ohio State University (Visiting Assistant Professor, 2019-2020) and Technische Universität München (Marie Skłodowska-Curie Fellow, 2020-2022). She holds a Ph.D. in Probability and Statistics from CIMAT (2018) and has conducted postdoctoral research at institutions like EPFL and Ohio State. Her work bridges stochastic topology, combinatorics, and educational technology, focusing on topics like cubical sliding puzzles, Eden growth models, and extremal topological problems in polyominoes. Education: Ph.D. in Probability and Statistics, CIMAT (2018) M.Sc. in Mathematics, CIMAT (2014) B.Sc. in Mathematics, Universidad de Guanajuato (2010) Research Interests: Her research spans stochastic topology, extremal combinatorics, and applications of discrete geometry to puzzles and games. She explores configuration spaces, topological properties of random structures, and innovative educational approaches like the Music Math Project, which integrates music and mathematics. Awards: Includes the Marie Skłodowska-Curie Fellowship (2020-2022), Arana-Ordaz Prize (2019), and Sofia Kovalevskaia Prize (2019). She has also received grants from CONACYT and CIMAT. Grants & Outreach: Developed workshops in marginalized communities using music and math, and contributed to software tools like the Eden Model analysis package. Active in science popularization through articles and outreach programs. Labs/Teams: Collaborated on projects like the Eden Model (topology analysis software) and extremal animal configurations, often involving interdisciplinary teams in mathematics and computer science.
Prof. Dr. Erich Grädel is a full professor in the Mathematical Foundations of Informatik group at RWTH Aachen University, where he conducts research at the intersection of logic, computer science, and mathematics. His work lies in the Department of Mathematics, Computer Science and Natural Sciences, focusing on logic and theoretical computer science. Institution: RWTH Aachen University Department: Mathematical Foundations of Informatik Research Focus: Logic in Computer Science, Algorithmic Model Theory, Semiring Semantics, Dependence Logic His primary research interests include logic and games, algorithmic model theory, fixed-point logics, and semiring semantics for provenance analysis. He has pioneered work in logics of dependence and independence, extending classical logical frameworks to model information flow and uncertainty. His recent publications emphasize semiring-based provenance in first-order and fixed-point logic, Büchi games, and team semantics, often in collaboration with Val Tannen and Matthias Naaf. The trend in his recent articles (2021–2025) reveals a deep and sustained investigation into the algebraic and semantic foundations of logic, particularly through semiring semantics. His work applies logical methods to database theory, verification, and game theory, focusing on how information and strategies can be tracked and analyzed via algebraic structures. Topics include provenance in infinite structures, locality theorems, zero-one laws, and logical characterizations of computational phenomena. Erich Grädel has held significant editorial responsibilities in the logic community: Editor, Logical Methods in Computer Science (since 2004) Editor, Mathematical Logic Quarterly (since 2012) Editorial Board Member (Corner Editor for Logic and Games), Journal of Logic and Computation (since 2007) Editor, Journal of Symbolic Logic (2008–2013) He chaired the European GAMES Research-Training Network (2002–2013) and has co-edited five books, including Lectures in Game Theory for Computer Scientists (Cambridge University Press, 2011). He has advised numerous PhD students, including Faried Abu Zaid, Łukasz Kaiser, and Wied Pakusa. His research group has included long-term collaborators and former members such as Dietmar Berwanger, Martin Otto, and Richard Wilke. He has received no explicitly listed scientific awards in the provided text, but his sustained editorial roles and leadership in major research networks indicate high recognition in the field. His research group, associated with the Mathematical Foundations of Informatik, has been active for decades, with current members including Sophie Brinke and former members forming a substantial list of researchers in logic and theoretical computer science. The group has contributed significantly to algorithmic model theory, automata, and logic games.
Alberto Espuny Díaz is a postdoctoral researcher at the Institute of Computer Science, Faculty of Mathematics and Computer Science, Universität Heidelberg, where he is part of the Theoretical Computer Science and Discrete Mathematics group led by Prof. Felix Joos, supported by a DFG-funded project. He previously held a postdoctoral position at TU Ilmenau in the Large Networks and Random Graphs group under Univ.-Prof. Dr. Yury Person. He completed his PhD at the University of Birmingham under the supervision of Daniela Kühn and Deryk Osthus. Starting in September, he will take up a position as professor agregat at Universitat de Barcelona. Research Interests: Alberto's research lies at the intersection of combinatorics and theoretical computer science. His primary focus is on extremal and probabilistic combinatorics , with significant work in random graphs , random geometric graphs , graph resilience , Hamiltonicity , spanning structures , and additive combinatorics . He investigates threshold phenomena, embedding problems, and structural properties of graphs under random perturbations. The most recent publications reveal a strong trend in analyzing the resilience and structural richness of random and perturbed graphs, particularly focusing on Hamilton cycles, spanning trees, and graph factors. His work frequently combines probabilistic methods with deep structural insights from extremal graph theory, often targeting sharp thresholds and robustness in discrete systems. Scientific Awards: Ramon Llull Prize (2024) for PhD thesis Best Pure Maths Poster Award, University of Birmingham (2019) Second Best Poster Award, LSE (2019) Third Best Poster Award, LSE (2018) Advising and Grants: While no formal students are listed, Alberto has supervised dissemination and editorial work through student journals. He is currently supported by a DFG-funded project at Heidelberg. He has been actively involved in organizing academic events and committees, including serving on the grants committee for BYMAT and organizing the Combinatorics Research Seminar in Heidelberg. Labs and Teams: He is a member of the Theoretical Computer Science and Discrete Mathematics group at Universität Heidelberg and previously worked in the Large Networks and Random Graphs group at TU Ilmenau. He is also affiliated with the Young Mathematicians community through the Real Sociedad Matemática Española and has coordinated national student events.
Roland Speicher is a Professor at the Department of Mathematics, Saarland University. His research focuses on Free Probability Theory , Random Matrices , and Operator Algebras , with applications in quantum physics, machine learning, and statistical mechanics. University: Saarland University Department: Mathematics Academic Rank: Professor Email: speicher@math.uni-sb.de Roland Speicher's research explores the interplay between free probability and random matrices, particularly through the lens of quantum mechanics and computational mathematics. He has contributed to understanding the effects of non-linear transformations on random matrices and their eigenvalue distributions, extending free probability tools to problems in machine learning and quantum information theory. His recent publications address: Non-linear functions on orthogonally invariant matrices Fuglede-Kadison determinants in operator-valued free probability Structured random matrices and cyclic cumulants Free probability applications in quantum gravity and black hole entropy Connections to the replica trick and quantum de Finetti theorems Key scientific recognitions include the ERC Advanced Grant (2014-2019) for non-commutative distributions. He leads a research group at Saarland University, collaborating with Dr. Johannes Hoffmann, Dr. Tobias Mai, and M.Sc. Alexander Wendel. His teaching includes advanced courses on random matrices, with lecture notes published by EMS Press.
Prof. Dr. Gesine Stephan is Professor of Economics, particularly Empirical Microeconomics, at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) since May 2009 and heads the 'Employment Promotion and Employment' research department at the Institute for Employment Research (IAB) in Nuremberg. Her work focuses on analyzing and evaluating labor market policy instruments and programs, with particular attention to effectiveness and public perceptions of fairness. Her educational background includes: Studied Economics at the University of Hannover until 1990 Scientific Assistant at Institute for Quantitative Economic Research, University of Hannover Promoted (PhD) in 1994 Habilitation in 2000 Research stays at universities in Austin and Berkeley, USA (1996/1997) Prof. Stephan's research centers on labor and personnel economics, labor and social policy, microeconometrics, and policy evaluation. She specializes in empirical methods to examine the effectiveness of labor market policies, particularly through field and survey experiments. Her work investigates how institutional frameworks influence labor market structures, the effectiveness of placement and training measures for the unemployed, and public perceptions of justice regarding unemployment benefits and sanctions. She frequently employs innovative methodologies including factorial survey experiments, high-frequency panel data analysis, and biomarker measurements to address complex questions in labor economics. Her publication record demonstrates consistent scholarly output with a clear thematic focus on labor market policy evaluation. Recent work examines justice perceptions regarding minimum wage increases, unemployment benefit durations, and training subsidies, often with attention to demographic differences and crisis contexts like the pandemic. The research shows methodological sophistication through the use of experimental designs and diverse data sources. Prof. Stephan holds several significant academic affiliations: Fellow of the Labor and Socio-Economic Research Center (LASER) at FAU Research fellow at the Institute for the Study of Labor (IZA) Member of the Standing Field Committees Social Policy and Population Economics of the Verein für Socialpolitik Her research department at IAB addresses critical questions about labor market policy effectiveness, access to support through these instruments, and institutional influences on labor market structures. This work has direct relevance for policymakers designing effective and socially accepted labor market interventions.
Prof. Dr. Alexander Drewitz is a Professor in the Department of Mathematics and Computer Science at the University of Cologne, specifically within the Division of Mathematics. His research focuses on probability theory, with primary interests in percolation theory, random geometric structures, transport processes in random media, and applications of high-dimensional probability to data science. He has held prior positions as an ETH Fellow at ETH Zurich and as a J.F. Ritt Assistant Professor at Columbia University. His work bridges theoretical advancements with practical applications, particularly in understanding critical phenomena and stochastic processes in complex systems. Education: Doctorate in Mathematics (details not explicitly provided in text). Research Interests: Prof. Drewitz explores percolation models, Gaussian free fields, random interlacements, and concentration of measure phenomena. His studies often address geometric and dynamic properties of random structures, with implications for data science and statistical physics. Recent work includes investigations into cluster volumes, arm exponents, and universality classes in percolation models. Publications Trends: His 15 most recent articles (2008–2025) reflect a focus on Gaussian free fields, random interlacements, branching processes, and long-range correlations. Key themes include percolation thresholds, invariance principles, and high-dimensional asymptotics. Grants & Activities: Organized conferences like 'Long-range phenomena in percolation' (2024) and 'Geometric and Topological Properties of Random Algebraic Varieties' (2023). Co-founded the Scientific Network on Stochastic Processes on Evolving Networks. Labs/Teams: Active in the Center for Data and Simulation Science at Cologne, contributing to interdisciplinary research on random geometry and data-driven methods. Leads the stochastics seminar and Bonn Cologne Mathematics-Physics seminar.
