جست‌وجوی استاد و پژوهشگر

Katrin Tentمشاهده پروفایل

استاد

• Model theory
• Group theory
• Geometry
• +۴ مورد دیگر

Professor Katrin Tent is a distinguished mathematician specializing in mathematical logic at the University of Münster, where she holds a professorship in the Faculty of Mathematics and Computer Science within the Institute for Mathematical Logic and Foundations Research. She is an active researcher in Mathematics Münster, an investigator in CRC 1442 Geometry: Deformations and Rigidity, and contributes to multiple research projects including Topics in Mathematics Münster T3: Models and universes, T4: Groups and actions, and T8: Random discrete structures and their limits. PhD in Linguistics, Christian-Albrechts-Universität zu Kiel (1988) Diplom in Mathematics, Christian-Albrechts-Universität zu Kiel (1989) PhD in Mathematics, University of Notre Dame (1994) Habilitation, "Model theory of groups and BN-pairs" (2000) Professor Tent's research bridges model theory, group theory, and geometry, with particular focus on finite Morley rank structures, BN-pairs, and sharply multiply transitive groups. Her work often combines methods from these areas to prove unexpected results, either constructing groups or incidence geometries with surprising model theoretic properties or using model theory to construct new and interesting geometries or groups. Her recent publications reveal a consistent trajectory connecting model theory with group-theoretic structures. She has made significant contributions to understanding sharply 2- and 3-transitive groups, finite Morley rank geometries, and the model theory of generalized polygons. Her work demonstrates how model-theoretic techniques can solve deep problems in group theory and geometry, particularly through the study of BN-pairs and incidence structures. DFG Research Fellowship (1996-1998) Bayerischer Habilitationsförderpreis (1998-2001) Heisenberg-Stipendium (2001-2004) ERC Consolidator Grants expert panel (2016, 2018) Elected to DFG Senate (2019) Professor Tent leads an active research group with current members including Marco Amelio, Dr. Benjamin Brück, Anna Cascioli, Lukas Jonuska, Silke Meissner, Zahra Mohammadi Khangheshlaghi, and Dr. Sam Shepherd. Her former research group members include Dr. Simon Andre, Dr. Isabel Müller, and Dr. Tim Clausen, among others. Her supervisory work spans both theoretical foundations and specific applications in geometric group theory and model theory. Her research group operates within the Institute for Mathematical Logic and Foundations Research at the University of Münster, collaborating closely with other researchers in the Mathematics Münster cluster. The group participates in various projects including CRC 1442 - C04: Group theoretic aspects of negative curvature, contributing to the vibrant mathematical research environment at one of Germany's leading mathematics institutions.

• Algorithms and Complexity
• Logic
• Database Theory
• +۲ مورد دیگر

Martin Grohe is a Professor at the School of Logic and Theory of Discrete Systems , part of the Department of Computer Science at RWTH Aachen University . His research spans Algorithms and Complexity , Logic , Database Theory , Graph Theory , and Machine Learning , with a focus on integrating logical frameworks into computational models. His recent work explores graph neural networks , Weisfeiler-Leman algorithms , and parameterized complexity , as seen in publications on isomorphism testing , database repairing , and probabilistic query evaluation . While no specific scientific awards are mentioned, his contributions to graph theory and machine learning are widely recognized through numerous peer-reviewed publications.

Manuel Penschuckمشاهده پروفایل

پژوهشگر ارشد

• Algorithm Engineering
• Random Graphs
• Parallel and Distributed Computing
• +۳ مورد دیگر

Manuel Penschuck is a Research Fellow at the Institute of Computer Science , Goethe University Frankfurt, Germany. His research focuses on algorithm engineering, graph theory, and scalable network generation, with emphasis on parallel computing, I/O-efficient algorithms, and random graph models. He actively contributes to conferences like ESA, SEA, and IPDPS, and has co-authored publications in top venues including LIPIcs , IEEE Transactions , and SIAM . His work includes engineering algorithms for non-linear preferential attachment , parallel shuffling , and hyperbolic graph generation . He has co-organized program committees for ESA, EuroPar, and SEA, and his collaborations span institutions such as MPI-INF, TU Darmstadt, and Australian National University. Recent publications highlight advances in uniform graph sampling, geometric network models, and distributed systems. His research integrates theoretical rigor with practical implementation, addressing challenges in big data and high-performance computing. He is a key contributor to the Networkit toolkit for large-scale network analysis.

Torsten Ueckerdtمشاهده پروفایل

استاد

• Graph Theory
• Geometric Graph Theory
• Discrete Mathematics
• +۸ مورد دیگر

Torsten Ueckerdt is an Interim Professor in the Algorithmics I group at the Institute of Theoretical Informatics, Karlsruher Institut für Technologie (KIT). He has held academic positions since 2012, including postdoctoral roles and habilitation in Discrete Mathematics. His research focuses on combinatorial objects like graphs, posets, and hypergraphs in geometric settings, exploring structural properties, colorings, and geometric representations. Holds a PhD from TU Berlin (2011) and habilitation from KIT (2017). Professional service includes editorial roles (Annals of Combinatorics) and program committees for conferences like Graph Drawing, SoCG, and EuroCG. Supervised numerous students across Bachelor's, Master's, and diploma theses. Research interests span structural graph theory, geometric graph theory, Ramsey theory, discrete geometry, and combinatorial games. Active in graph drawing and algorithm design, with contributions to queue layouts, graph representations, and optimization problems like cartograms and wind farm cabling.

Samir Dattaمشاهده پروفایل

استاد

• Theoretical Computer Science
• Computational Complexity Theory
• Bounded Space Complexity
• +۹ مورد دیگر

Samir Datta is a Professor at the Chennai Mathematical Institute, where he conducts research in Theoretical Computer Science with a focus on Computational Complexity Theory. His work spans foundational graph problems, circuit complexity, and interdisciplinary applications in logic and numerical analysis. His research interests include: Bounded space complexity in restricted graph classes (planar graphs, bounded tree-width, H-minor free graphs) Reachability, graph isomorphism, matching, and Steiner Tree problems Characterizations and properties of arithmetic circuits Complexity aspects of game theory, proof theory, and numerical analysis His publications reflect a deep engagement with structural complexity and algorithmic graph theory. While specific titles are referenced, a detailed list is not provided in the source text. He has advised both current and past students, though their names are not listed. No scientific awards are mentioned in the available information. He is actively involved in research and academic mentoring at CMI, with no indication of part-time status, retirement, or former affiliation.

V. Arvindمشاهده پروفایل

استاد

• Computational Complexity Theory
• Structural Complexity
• Randomized Computation
• +۵ مورد دیگر

V. Arvind is a Professor in the Theoretical Computer Science faculty at the Institute of Mathematical Sciences (IMSc) , Chennai. His research is centered on computational complexity theory, with a focus on structural complexity, randomized and algebraic computation, and quantum information and computation. He explores the deep connections between theoretical computer science and mathematics. Institution: Institute of Mathematical Sciences (IMSc), Chennai School: Theoretical Computer Science Academic Rank: Professor Arvind's research interests include computational complexity, structural complexity theory, algebraic computation, derandomization, and quantum computing. He is particularly interested in the interplay between mathematical structures and computation. His work often bridges theoretical computer science with algebra, combinatorics, and logic. His recent publications, primarily expository articles in the EATCS Bulletin’s Computational Complexity Column, cover a wide range of topics such as robust oracle machines, the Alon-Roichman theorem, noncommutative arithmetic circuits, graph isomorphism, and quantum computation. These works reflect trends in foundational complexity theory, algebraic methods in computation, and the exploration of quantum models. The articles emphasize structural insights, lower bounds, and connections to mathematical disciplines. Professional Service and Editorial Roles: Associate Editor, ACM Transactions on Computation Theory Editor, EATCS Computational Complexity Column (since June 2011) Editorial Board Member, International Journal of Computer Mathematics (2009–2013) Co-organizer, ICM Satellite Conference on Algebraic and Probabilistic Aspects of Combinatorics and Computing Program Committee Member for WALCOM 2014, STACS 2012, COCOON 2009, FSTTCS (multiple years, including chair roles), CCC 2006, INDOCRYPT (2002, 2005), and others Teaching: Arvind has taught advanced courses including Computational Complexity, Algorithms, Algebra and Computation, and Discrete Mathematics, often based on foundational texts and notes from leading experts. Lecture notes from his courses have been compiled by students and collaborators. Collaborations: He has an extensive list of co-authors, including prominent researchers such as Manindra Agrawal, Eric Allender, Johannes Köbler, Meena Mahajan, Jacobo Torán, and Ramprasad Saptharishi, indicating strong collaborative research networks in complexity theory and algorithms.

• Graph Theory
• Operations Research
• Discrete Mathematics
• +۳ مورد دیگر

Dr. Maximilian Fürst is a researcher at the Institute of Optimization and Operations Research of the University of Ulm , focusing on graph theory, discrete mathematics, and algorithmic complexity. His work primarily investigates matching problems in graphs, including uniquely restricted matchings, induced matchings, and acyclic matchings, with applications in theoretical computer science and optimization. Research Interests: Graph Theory (matching theory, subcubic graphs, cycle-free graphs) Operations Research (approximation algorithms, linear programming) Computational Complexity (NP-hardness, graph invariants) Discrete Mathematics (combinatorics, degree sequences) Trends in Recent Publications: His publications emphasize theoretical analysis of graph problems, particularly matching-related algorithms and bounds. Key areas include hardness proofs, approximation methods, and extremal graph theory, with collaborations across European institutions. Teaching: He has taught courses such as Optimization and OR 2 and Graph Theory 2 at the University of Ulm since 2017. Collaborations: Regularly works with colleagues like Dr. Julien Baste, Prof. Dieter Rautenbach, and Prof. Michael A. Henning on graph theory and optimization challenges.

• Automata Theory
• Concurrency Theory
• Formal Verification
• +۱ مورد دیگر

Slawek Lasota is a Professor at the Automata Theory Group within the Faculty of Mathematics, Informatics and Mechanics, University of Warsaw. His research focuses on automata theory, concurrency theory, formal verification, and systems biology, with a strong emphasis on computational complexity and algorithmic analysis of systems with infinite-state spaces. Research Interests : Automata theory (infinite alphabets, nominal sets), concurrency theory (timed automata, vector addition systems), formal verification (reachability problems, model checking), systems biology (computational models of biological systems). Grants : Coordinator of NCN grants on data-enriched models and automatic analysis of concurrent systems; participant in ERC projects Lipa and FOX . Community Service : Managing editor of Fundamenta Informaticae (2018-), member of EATCS Council (2019-), and Rada Doskonalosci Naukowej (2019-). His work has received recognition including the STOC'19 Best Paper Award and EATCS BEST ETAPS PAPER AWARD . He supervises PhD students in topics ranging from Petri nets to timed automata and has contributed extensively to advancing verification techniques for systems with data, timed models, and concurrency.

• Molecular Biology
• Neurobiology
• Machine Learning
• +۲ مورد دیگر

Prof. Frank Müller is a Universitätsprofessor at Forschungszentrum Jülich GmbH , leading the Molecular Sensory and Neurobiology research group. His work bridges computational methods and biological systems. Research focuses on: Graph-based machine learning for biological networks Transformer architectures for molecular data Computational approaches to sensory neuroscience Parameter-efficient models for multi-task learning Key article trends show expertise in graph transformers , molecular foundation models , and multi-agent reasoning systems . No awards explicitly mentioned. Current affiliation: IBI (Institute of Biological Information Processing), Forschungszentrum Jülich

• Discrete Optimization
• Quantum Computing Applications in Optimization
• Bayesian Optimization
• +۳ مورد دیگر

Dr. Alexey Bochkarev is a researcher in the Optimization Department at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU), affiliated with the Felix Klein Center. His work focuses on discrete optimization, quantum computing applications, and network security. Current affiliation: RPTU, Optimization Department Contact: Building 31, Room 455, Paul Ehrlich Street, 67663 Kaiserslautern | a.bochkarev@math.rptu.de Research Interests Quantum computing for combinatorial optimization Monte Carlo tree search in adversarial network scenarios BDD-based representations for facility location problems Dynamic optimization under uncertainty Recent Publications His 2024 publications highlight quantum computing advancements and Monte Carlo methods for interdiction problems, while earlier works explore BDD alignment in network optimization. Key trends include hybrid quantum-classical algorithms and stochastic search frameworks for infrastructure protection.

Vincent Guirardelمشاهده پروفایل

پژوهشگر

• Geometric Group Theory
• Hyperbolic Geometry
• Group Actions on Trees
• +۳ مورد دیگر

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.

• 3D Shape Analysis
• Graph-Based Machine Learning
• Computer Vision
• +۴ مورد دیگر

Andrea Torsello is a researcher at the University of York, specializing in 3D shape analysis, graph-based machine learning, and quantum computing applications in computer vision. His work bridges theoretical and applied domains, focusing on pattern recognition, network thermodynamics, and remote sensing. PhD from University of York (2004) Published extensively in journals like IEEE Transactions and Pattern Recognition Research interests include: Quantum-inspired graph analysis 3D reconstruction techniques Manifold learning for complex networks Thermodynamic modeling of time-evolving systems Key contributions involve: Quantum walk-based graph similarity measures k-Anonymity for graph data Physics-driven CNN models for ocean wave reconstruction Game-theoretic approaches to shape matching

• Tensor Decompositions
• Quantum Computing
• Fredholm Integral Equations
• +۷ مورد دیگر

Patrick Gelß is a Postdoctoral Researcher at Zuse Institute Berlin, working in the AI in Society, Science, and Technology department. He leads the iol.QUANT research group focused on quantum-inspired and tensor-based methods, with affiliations to Freie Universität Berlin and collaborative projects like MATH+ Cluster of Excellence. Diploma in Mathematics/Physics (2013, Freie Universität Berlin) PhD in Mathematics (2017, summa cum laude, Freie Universität Berlin) Postdoctoral roles at Zuse Institute Berlin (2020-present) and CRC 1114 (2017-2022) His research bridges tensor decompositions, quantum computing, and dynamical systems, with notable contributions to: Graph Isomorphism: Continuous optimization approaches via doubly stochastic matrices and Frank-Wolfe algorithms Quantum Simulation: Tensor network representations for quantum circuits and the open-source WaveTrain package KvN Mechanics: Mathematical analysis of existence/uniqueness solutions for bounded domains Fredholm Networks: Novel training paradigms for neural networks using integral equations Scientific achievements include: Developing Scikit-TT for tensor-train computations Organizing major workshops (QML@SC2024, TMQS 2024) Leading the Thematic Einstein Semester 2024 on Mathematics for Quantum Technologies His work spans chemical kinetics, quantum dynamics, and quantum machine learning, with applications to CO oxidation models, exciton-phonon systems, and mutational hierarchies in medicine.

Michael Elberfeldمشاهده پروفایل

استاد

• Computer Science
• Theoretical Foundations
• Parameterized Complexity
• +۶ مورد دیگر

Prof. Dr. Michael Elberfeld is a faculty member at the Technical University of Central Hesse , affiliated with the Department of Mathematics, Natural Sciences and Computer Science . His research focuses on theoretical computer science, particularly in computational and parameterized complexity, logic in computer science, and algorithmic meta-theorems. Education : Doctorate in Theoretical Computer Science from the University of Lübeck (2012); Diploma (MSc) in Computer Science from the University of Lübeck (2007). His work explores the intersection of graph theory , logic , and space-bounded computation , with groundbreaking contributions to problems on bounded tree-width structures and order-invariant logics . He has developed logspace algorithms for graph canonization and studied succinctness tradeoffs in logical formalisms. Key publications include analyses of parameterized space complexity , algorithmic meta-theorems , and applications to bioinformatics like haplotype inference and network orientation. His research is supported by the European Commission through grants 648276 and P 28699 . He collaborates extensively with researchers such as Martin Grohe , Pascal Schweitzer , and Till Tantau , bridging theoretical logic with practical applications in staff rostering and biological network analysis .

• Theoretical Computer Science
• Graph Algorithms
• Computational Complexity
• +۴ مورد دیگر

Frank Fuhlbrück is a Researcher at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin, actively contributing to the Algorithms and Complexity II research group. His position as a scientific collaborator places him at the forefront of theoretical computer science research in Berlin. His research centers on fundamental problems in graph theory and computational complexity, with deep expertise in the Weisfeiler-Leman algorithm for graph isomorphism testing. Key interests include parameterized complexity, graph invariants, spectral properties, and combinatorial methods for distinguishing graph structures. His work bridges discrete mathematics, algebra, and theoretical computer science to address foundational questions in algorithm design. Analysis of his 2020-2024 publications reveals a cohesive research trajectory focused on the expressive power of combinatorial invariants, particularly through subgraph counts and spectral hierarchies. His contributions to understanding fixing numbers, vertex individualization, and fractional packing dimensions demonstrate innovative applications of algebraic and logical frameworks to graph classification problems. As an integral member of the Algorithms and Complexity II group, he collaborates on advancing core theoretical frameworks in algorithms while maintaining connections to empirical research methodologies as evidenced by his 2022 work on R-based statistical tools.