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Johannes CarmesinView profile

Professor

• Graph Theory
• Combinatorics
• Topology
• +3 more

Prof. Johannes Carmesin is a Professor at the Faculty for Mathematics and Computer Science, Technische Universität Bergakademie Freiberg. His research focuses on advanced topics in Graph Theory, Combinatorics, and Topology, with notable contributions to 3-dimensional Kuratowski-type theorems and the extension of Structural Graph Theory to simplicial complexes. He leads the Discrete Structures group, which explores areas including Graph Minors, Matroid Theory, and Infinite Graphs. Education and Career: He holds a PhD (2015) and Habilitation (2018) in Mathematics, with earlier work on harmonic functions in networks (Master's 2012). His academic journey includes research on infinite matroids and tree-decompositions. Research Interests: Carmesin’s work bridges discrete mathematics and topology, emphasizing structural properties of graphs and their embeddings. Key areas include 3D graph embeddings, connectivity in infinite graphs, and matroid characterizations. He has pioneered methods for analyzing 2-dimensional simplicial complexes and their topological representations. Recent Trends in Publications: His recent work extends Graph Minor Theory to temporal networks and 3D spaces, with a focus on canonical decompositions, tangle theory, and applications in large-scale network analysis. His 2023 European Prize in Combinatorics recognizes breakthroughs in 3D Kuratowski analogues. Awards: European Prize in Combinatorics (2023) Advising and Team: Supervised PhD students Emily Nevinson and Tsvetomir Mihaylov, and mentored master’s students like Will J. Turner. His research team includes Dr. Jan Kurkofka and Dr. Matthew Kroeker. Notable collaborations address infinite graph connectivity and Stallings-type theorems for finite groups. Labs/Groups: Directs the Discrete Structures research group, which hosts regular seminars and collaborates internationally. Past members include Georgios Kontogeorgiou and Lyuben Lichev as interns.

Zevi MillerView profile

Professor

• Graph Theory
• Combinatorics
• Complexity Theory
• +1 more

Zevi Miller is a Professor in the Department of Mathematics at Miami University, located in Oxford, Ohio. He holds a B.S. (Honors Mathematics) from the University of Michigan (1972) and a Ph.D. in Mathematics from the same institution (1979). His research focuses on Graph Theory, Combinatorics, Complexity Theory, and Theoretical Computer Science, with particular emphasis on graph embeddings, permutation arrays, and algorithm design. Professional History: Miller began as a Teaching Fellow at the University of Michigan (1972–1978), then joined Miami University as Assistant Professor (1978–1982), progressing to Associate Professor (1982–1988) and Full Professor (1988–present). He has held visiting roles, including Visiting Professor at the University of Texas–Dallas (1985) and Visiting Scholar at UC Berkeley (1986), where he participated in the Mathematical Sciences Research Institute’s complexity theory program. Research interests include graph theory applications, combinatorial optimization, and theoretical computer science challenges such as Steiner trees and hypercube embeddings. His work often intersects algorithm design and discrete mathematics, with contributions to bandwidth optimization, graph layouts, and permutation arrays. Publications span over four decades, including foundational papers on graph embeddings, Steiner trees, and algorithmic graph theory. His collaborative research with scholars like I.H. Sudborough and D. Pritikin highlights interdisciplinary approaches to complex computational problems.

Ferit ÖztürkView profile

Professor

• Singularity Theory
• Contact Topology
• Symplectic Topology
• +1 more

Ferit Öztürk is a Professor in the Mathematics Department at Bogazici University, specializing in singularity theory, contact topology, and symplectic topology. He leads the Geometry/Topology Seminar and supervises numerous graduate students in these fields. His research bridges topological methods with applications in robotics and dynamical systems. Recent work includes exotic manifold construction, real contact structures on 3-manifolds, and Morse-Bott theory on Lie groups. Dr. Öztürk holds a Ph.D. from Middle East Technical University (2001) and has developed course materials on Morse Theory and Projective Geometry. Student Supervision: 12+ M.S./Ph.D. students in topology and geometry Research Tools: Contact branched covers, real algebraic models, geometric surgery

• Obesity
• Diabetes
• Bariatric Surgery
• +5 more

Roman Vangoitsenhoven serves as an Assistant Professor at KU Leuven's Faculty of Medicine within the Department of Chronic Diseases and Metabolism. He leads the Subdivision Metabolic unit at the Clinical and Experimental Endocrinology research group (UZ Herestraat 49, box 7003, 3000 Leuven) and holds membership in both the Council of the Faculty of Medicine and the Council of the Department of Chronic Diseases and Metabolism. His research focuses on obesity and diabetes, with particular emphasis on GLP-1 based pharmacotherapy , bariatric surgery outcomes , and cardiometabolic health optimization . Current projects investigate neuropsychobiological approaches to patient selection for weight management therapies, de novo serine biosynthesis in obesity-related cardiac dysfunction, and data-driven interventions for type 2 diabetes management in diverse populations including low-income settings and urban Uganda. Analysis of his 2025 publications reveals a strong thematic concentration on translational obesity research , with recurring subfields spanning pharmacotherapy mechanisms, surgical outcomes, nutritional interventions, and metabolic monitoring technologies. His work demonstrates consistent collaboration across European institutions with significant contributions to clinical guidelines development. Member of Faculty of Medicine Council Member of Department of Chronic Diseases and Metabolism Council Dr. Vangoitsenhoven actively supervises multiple major research projects including a €2.3M ERC-funded study on GLP-1 pharmacotherapy optimization (2025-2029) and international collaborations on diabetes management in low-resource settings. His teaching portfolio includes advanced courses in clinical nutrition, disease mechanisms, and evidence-based medicine within KU Leuven's medical curriculum. He leads the Clinical and Experimental Endocrinology unit's metabolic research subdivision, directing a multidisciplinary team of 12 researchers focused on obesity-diabetes pathophysiology and therapeutic interventions. Current initiatives include the SABO cohort study on post-bariatric sarcopenia in elderly patients and development of digital health tools for personalized diabetes management.

Joe D. WarrenView profile

Professor

• Computer Graphics
• Geometric Modeling
• Computational Geometry
• +3 more

Joe D. Warren is a Professor of Computer Science at Rice University, where he has served since 1986. His research focuses on computer graphics, geometric modeling, and computational geometry, with notable contributions to subdivision surfaces, as detailed in his book Subdivision Methods for Geometric Design . He also explores bioinformatics applications, including 3D modeling of mouse brain gene expression and lung motion analysis from 4D CT scans. Additionally, Warren teaches courses in computer game design and introductory programming, co-developing award-winning Coursera specializations. He earned his Ph.D. from Cornell University and previously served as Department Chair (2008-2013). Education: B.Sc. (Rice University, 1983), Ph.D. (Cornell University, 1986) Research Collaborators: Baylor College of Medicine, MD Anderson Cancer Center, Texas A&M Teaching: COMP460 (Game Design), COMP110 (Introductory Computing) His work on the GRACE tool (Graphical Ruler and Compass Editor) won the 1998 Quest for Java award. He has advised PhD students now at Washington University and Texas A&M. Current projects include game prototyping with Pi Studios and lung motion modeling for medical diagnostics.

Daniel PaulusmaView profile

Professor

• Structural Graph Theory
• Algorithmic Graph Theory
• Computational Complexity
• +6 more

Daniel Paulusma is a Professor in the Department of Computer Science at Durham University, where he serves as Head of the Algorithms and Complexity research group (ACiD). He obtained his PhD and Master's degrees from the University of Twente in 2001 and 1997 respectively, and has been at Durham University since 2004, progressing from Lecturer (2004-2011) to Senior Lecturer (2011-2013), Reader (2013-2015), and finally to Professor in 2015. He previously served as Director of Research for the School of Engineering and Computing Sciences from 2014 to 2017. Paulusma's research spans two main areas: structural and algorithmic graph theory, with a focus on computational complexity of graph problems under input restrictions; and cooperative game theory, particularly matching games related to kidney exchange. His work has resulted in numerous survey papers and significant contributions to the field. He has received several prestigious awards including the CIAC 2025 Best Paper Award, ISAAC 2024 and 2023 Best Paper Awards, and the Glover-Klingman Prize for his work on graph contractions. His recent publications demonstrate a strong focus on complexity frameworks for forbidden subgraphs, matching cuts, graph coloring, and kidney exchange algorithms. The research shows a consistent pattern of exploring computational complexity within specific graph classes, particularly H-free graphs, and developing frameworks to classify problems based on graph structure constraints. CIAC 2025 Best Paper Award for "Atoms versus avoiding simplicial vertices" ISAAC 2024 Best Paper Award for "Complexity framework for forbidden subgraphs II: Edge subdivision and the \"H\"-graphs" ISAAC 2023 Best Paper Award for "Matching cuts in graphs of high girth and H-free graphs" Glover-Klingman Prize for "The Computational Complexity of Graph Contractions I, II" Paulusma has successfully supervised numerous PhD students including Yilin Li, Tala Eagling-Vose, Xin Ye, Siani Smith, Giacomo Paesani, Anthony Stewart, Carl Feghali, Jian Song, and Pim van 't Hof. He has secured substantial research funding including grants from the Leverhulme Trust, EPSRC, and Royal Society for projects on graph coloring, kidney exchange algorithms, and network structure analysis. His current projects include "Algorithmic Meta-classifications for Graph Containment" (2025-2028) and "KidneyAlgo: New Algorithms for UK and International Kidney Exchange" (2023-2025). As Head of the Algorithms and Complexity research group (ACiD), Paulusma leads a vibrant research team focused on theoretical computer science problems with applications in network analysis, optimization, and game theory. The group regularly organizes workshops and collaborates with international researchers in the field.

Chia-Wen ChenView profile

Researcher

• Item Response Theory
• Forced-Choice Items
• Computerized Adaptive Testing
• +3 more

Dr. Chia-Wen Chen is a Psychometrician at the Psychometrics Centre within the Cambridge Judge Business School , specializing in Executive Education. Originally from Taiwan, he holds a PhD in Psychometrics from the Education University of Hong Kong (2018), preceded by a master's degree in Psychology from National Chung Cheng University (2012). His career spans institutions in Taiwan, Hong Kong, Norway, and the UK, including postdoctoral research at the University of Oslo's Centre for Educational Measurement (2019-2023). PhD in Psychometrics (2018), Education University of Hong Kong MSc in Psychology (2012), National Chung Cheng University Postdoctoral Researcher (2019-2023), University of Oslo Chia-Wen's research focuses on Item Response Theory (IRT) models for forced-choice and compositional items , with applications in computerized adaptive testing (CAT) , differential item functioning (DIF) , and multilevel modeling . His work includes developing novel IRT methods for ranking items and Most-Least formats, addressing reliability/validity in educational scales like the Principal Instructional Management Rating Scale (PIMRS), and analyzing large-scale datasets (PISA) for cross-national educational insights. Recent publications demonstrate expertise in ipsative testing , online parameter estimation , and factor mixture modeling for educational diagnostics. He has also contributed to methodologies for CAT algorithms in educational evaluation and fault line analysis in school leadership teams.

Bin HanView profile

Professor

• Computational Mathematics
• Numerical Partial Differential Equations (PDEs)
• Applied Harmonic Analysis
• +4 more

Bin Han is a Professor of Mathematics at the Department of Mathematical and Statistical Sciences , University of Alberta, Canada. He holds a PhD (1998), MSc (1994), and BSc (1991) in Mathematics from the University of Alberta, Chinese Academy of Sciences, and Fudan University, respectively. Research Interests: Computational Mathematics: High-order finite difference methods, numerical solutions of PDEs (Helmholtz, elliptic interface, Burgers' equations), and Fourier/wavelet-based algorithms. Applied Harmonic Analysis: Framelets/wavelets with applications in image processing, data sciences, and deep learning, focusing on directional and quasi-tight properties. Wavelet Theory: Construction of wavelets on bounded intervals for boundary value problems, Gibbs phenomenon analysis, and stability of refinable functions. Computer Aided Geometric Design (CAGD): Subdivision schemes, spline approximation, and isogemetric analysis. Article Trends: His recent work (2021-2022) emphasizes high-order finite difference methods for Helmholtz and interface problems, directional tensor product complex tight framelets for image processing, and quasi-tight framelets with balancing orders for robustness and sparsity. Scientific Awards: NSERC Postdoctoral Fellowship (1999-2000) Advising & Grants: He has supervised PhD students Qiwei Feng, Michelle Michelle, Ran Lu, and Chenzhe Diao. His research is supported by NSERC, Westgrid, Compute Canada, and MITACS.

Martin BačaView profile

Professor

• Graph Theory
• Combinatorics
• Discrete Mathematics
• +1 more

Professor Martin Bača is affiliated with the Department of Applied Mathematics and Informatics at the Faculty of Mechanical Engineering , Technical University in Košice , Slovakia. His academic role involves advanced research and teaching in graph theory and discrete mathematics. Research Interests: Specializing in graph labelings including vertex irregular total labelings, magic and antimagic labelings, edge-magic labelings, face-magic labelings of type (a,b,c), and harmonious labelings. Key areas: irregularity strengths , modular labelings , doubly resolving sets , and antimagic graphs . Focus on applications in network topology , chemical graph theory , and combinatorial optimization . Recent Article Trends: His 2024-2023 works explore modular irregularity strengths for dense graphs, corona products, and flower graphs, alongside antimagic labelings for digraphs, fullerenes, and generalized prisms. Notable themes include graph evaluation techniques , edge-antimagic total labelings , and vertex-antimagic labelings .

• Computer graphics
• Geometry processing
• Computer-aided geometric design
• +6 more

Leif Kobbelt is a Full Professor of Computer Science and Head of the Visual Computing Institute at RWTH Aachen University . He previously held academic positions at the Max-Planck-Institute for Computer Science, University of Erlangen-Nürnberg, and University of Wisconsin-Madison. Diploma in Computer Science (1992), Karlsruhe Institute of Technology PhD in Computer Science (1994), Karlsruhe Institute of Technology His research focuses on computer graphics and geometry processing , with specific interests in 3D reconstruction, quad mesh generation, real-time rendering, and geometric modeling algorithms. He has pioneered techniques for efficient mesh processing, anisotropic geodesic computation, and procedural facade visualization. Recent publications analyze nonlinear constraints in geometric modeling, quad layout optimization, and real-time rendering techniques. Key themes include mesh parameterization, multiresolution analysis, and computational geometry for interactive applications. Scientific recognitions include: 2014 Gottfried Wilhelm Leibniz Prize (Germany's most prestigious research award) 2013 ERC Advanced Grant (ACROSS project) 2008 Eurographics Fellow 2004 Eurographics Outstanding Technical Contribution Award 2000 Heinz-Maier-Leibnitz Award He leads major research initiatives like the excellence clusters UMIC (€40M) and AICES (€15M), and the ERC-funded ACROSS project (€2.5M, 2014-2018). He serves as principal investigator and reviewer for international journals and organizations.

Rudi PendavinghView profile

Assistant Professor

• Matroid Theory
• Topological Graph Theory
• Discrete Mathematics
• +4 more

Rudi Pendavingh is an Assistant Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology. Affiliated since 1999, he specializes in matroid theory , combinatorics , and topological graph theory within the Combinatorial Optimization group. Research Interests include: Matroid theory with focus on excluded minors and representability over partial fields Topological graph theory, particularly Colin de Verdière invariants for surface-embedded graphs Discrete optimization modeling and algorithmic complexity Geometric combinatorics in polyhedral complexes like Dressians Recent Publications highlight his work on: Stable tournament formats using finite projective planes (2025) Bounding topological graph parameters via combinatorial methods (2024) Computational enumeration of matroid minors (2024) Asymptotic analysis of Dressian dimensions (2024) Contact : Email: r.a.pendavingh@tue.nl Phone: +31 40 247 4235 Office: MetaForum 4.105, TU/e Campus

Oleg PikhurkoView profile

Professor

• Extremal combinatorics
• Graph theory
• Descriptive combinatorics
• +6 more

Oleg Pikhurko is a Professor of Mathematics at the University of Warwick, affiliated with both the Mathematics Institute and DIMAP (the Centre for Discrete Mathematics and its Applications). His office is located in room B2.12 at the University of Warwick in Coventry, UK. Pikhurko has established himself as a prominent researcher in combinatorics with significant contributions to extremal combinatorics, graph theory, and related fields. His research interests span a wide range of topics in discrete mathematics including extremal combinatorics and graph theory, descriptive combinatorics, graph limits, random structures, and algebraic, analytic and probabilistic methods in discrete mathematics. Pikhurko's work bridges theoretical foundations with practical applications, often employing sophisticated mathematical techniques to solve challenging problems in combinatorial structures. The analysis of Pikhurko's recent publications reveals a consistent focus on extremal combinatorics, particularly Turan-type problems, hypergraph theory, and graph limits. His work demonstrates increasing sophistication in handling complex combinatorial structures, with recent papers exploring connections to measure theory, geometry, and coding theory. Notably, his research shows a progression from classical combinatorial problems toward more abstract and interdisciplinary approaches, including measurable versions of combinatorial theorems and applications to high-dimensional spaces. ERC Advanced Grant 'Finite and Descriptive Combinatorics' (2022-2026) Pikhurko has successfully supervised numerous PhD students including Teresa Sousa (2006), David Offner (2009), Zelealem Yilma (2011), Matthew Fitch (2019), and Matteo Mazzamurro (2023). He currently co-advises Irene Gil Fernández and Zhuo Wu, both expected to complete their PhDs in 2025. His research group focuses on 'Finite and Descriptive Combinatorics,' reflecting his dual interest in finite combinatorial structures and their descriptive (measurable) counterparts. The ERC Advanced Grant awarded in 2022 has provided significant funding to support this research program through 2026. Beyond traditional research, Pikhurko founded the Hedgehog Fund, which encourages innovative proofs of mathematical results presented in his lectures. He also maintains an Erdos Lap Number of 2, having sat on the lap of Barbie Freidin (Erdos Lap Number 1) who herself sat on Paul Erdos's lap.

Hans-Peter SeidelView profile

Professor

• Computer Graphics
• 3D Image Analysis
• Digital Geometry Processing
• +3 more

Hans-Peter Seidel is a leading academic in computer graphics, serving as Director of the Max Planck Institute for Informatics and Full Professor at Saarland University since 1999. Previously held roles include Full Professor at University of Erlangen (1992–1999) and Assistant Professor at University of Waterloo (1989–1992). Holds a PhD in Mathematics (1987) and Habilitation in Informatics (1989) from University of Tübingen. Research focuses on 3D image analysis, digital geometry processing, visual computing, and free viewpoint rendering. Key achievements include pioneering work in surface editing, motion capture, and multi-view video processing. Has organized major conferences like Eurographics and SIGGRAPH, serving as editor for journals including IEEE TVCG and Computer Aided Geometric Design. Recipient of the Eurographics Distinguished Career Award (2012), Gottfried Wilhelm Leibniz Prize (2003), and numerous fellowships. Led initiatives such as the Cluster of Excellence on Multimodal Computing and Interaction (M2CI) and the Max Planck Center for Visual Computing and Communication (MPC-VCC). Active in academic leadership roles including Eurographics Chair and DFG committees. Publications span over 30 SIGGRAPH and 50 Eurographics contributions, with an h-index of 62 and 14,000+ citations. Recognized as a top-cited researcher in computer graphics. Current research explores advanced visualization techniques and geometric modeling innovations.

• Applied Mathematics
• Computational Methods
• Control Theory
• +5 more

Sara Grundel is a leading researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. Her work focuses on computational methods in systems and control theory, particularly in model order reduction, gas network simulation, and optimization of energy systems. Education: Diplom in Mathematics, ETH Zurich (2005) PhD in Mathematics, Courant Institute of Mathematical Sciences, New York University (2011) Research Interests: Sara’s research encompasses mathematical control theory, stability analysis, and numerical methods for differential-algebraic equations. She applies these techniques to gas and energy networks, epidemic modeling, and multi-agent systems. Her interdisciplinary work bridges computational mathematics with real-world engineering and public health challenges. Recent Publications: Her 15 most recent articles (2024–2012) demonstrate expertise in parametrized PDEs, model reduction for coupled systems, and control strategies for SARS-CoV-2 containment. Key subtopics include adaptive meshing, stability-preserving algorithms, and optimization of nonlinear network dynamics. Scientific Contributions: Developed clustering-based model reduction techniques for networked systems Investigated hyperbolic discretization methods using Riemann invariants Advanced polynomial root radius optimization with affine constraints Collaborations: Sara frequently collaborates with researchers like Peter Benner and Martin Gersen on energy grid simulations and control theory. She participates in international conferences (GAMM, IEEE CDC, MTNS) and contributes to edited volumes in applied mathematics.

• Mathematical Optimization
• Nonsmooth Optimization
• Multiobjective Optimization
• +4 more

Bennet Gebken is a researcher at the Department of Mathematics , Technical University of Munich , affiliated with the Chair of Mathematical Optimization led by Prof. Ulbrich. His work focuses on nonsmooth and multiobjective optimization, particularly in PDE-constrained problems and numerical continuation methods. Research Interests: Bennet specializes in nonsmooth optimization, multiobjective optimization, and regularization techniques. His recent work explores convergence analysis in nonsmooth settings, second-order gradient sampling, and inverse optimization methods for data-driven decision criteria. Publications: His research spans topics like PDE-constrained multiobjective optimization, L1 penalty terms, and the hierarchical structure of Pareto critical sets. Key trends include reduced-order modeling, computational efficiency, and the interplay between optimization and machine learning. Contact: bennet.gebken@tum.de . Based at Boltzmannstr. 3, Garching b. München, Germany.