جست‌وجوی استاد و پژوهشگر

Margaret Bayerمشاهده پروفایل

استاد

• Combinatorics
• Discrete Geometry
• Convex Polytopes
• +۳ مورد دیگر

Margaret Bayer is a Professor in the Department of Mathematics at the University of Kansas, within the College of Liberal Arts & Sciences. She specializes in combinatorics and discrete geometry, with research focusing on convex polytopes, hyperplane arrangements, Eulerian posets, and flag vectors. Her work bridges combinatorics with algebraic geometry, particularly through connections to toric varieties. Her research explores the combinatorial structure of geometric objects, including face lattices of polytopes and the interplay between algebraic and geometric properties. Recent work includes studies on cut complexes of graphs, matching complexes, and applications of combinatorial methods in education and algorithm design. Bayer has authored/co-authored over 40 publications, including foundational works on flag vectors, the cd-index of Eulerian posets, and lattice polytopes derived from Schur polynomials. Her articles often address topics like polytope enumeration, topological properties of graph complexes, and combinatorial optimization in exam design. She serves as Book Review Editor for the Association for Women in Mathematics Newsletter and has advised numerous collaborative projects. Her teaching includes intermediate analysis and discrete mathematics courses.

• Algorithms
• Computational Geometry
• Shortest Path Planning
• +۴ مورد دیگر

Stefan Funke is a Professor at the University of Stuttgart's Institute for Formal Methods in Computer Science, part of the Faculty of Computer Science, Electrical Engineering and Information Technology. His work focuses on algorithm design and computational geometry with applications in road networks, trajectory analysis, and geographic information systems. He leads the Algorithmics Group, developing efficient algorithms for shortest path planning, network optimization, and privacy-preserving queries. Research interests include geometric algorithms, graph theory, and practical implementations of theoretical results in transportation and spatial data analysis. Notable contributions involve contraction hierarchies for fast shortest path queries, trajectory mining techniques, and methods for preserving privacy in network-based computations. Recent work emphasizes scalable solutions for large-scale road networks, including simplification methods that preserve topological features and energy-efficient routing strategies for electric vehicles. His research often bridges theoretical foundations with real-world applications in navigation systems and smart mobility solutions. Awards and grants are not explicitly listed in the provided data, but his extensive publication record indicates sustained recognition in algorithmic research. He advises on multiple interdisciplinary projects involving spatial data processing and algorithm engineering.

Saeed Boorboorمشاهده پروفایل

استادیار مدعو

• Visualization
• Computer Graphics
• Medical Imaging
• +۴ مورد دیگر

Saeed Boorboor is a Principal Research Scientist at Stony Brook University's Center for Visual Computing and an Adjunct Assistant Professor at the University of Illinois at Chicago. His research focuses on immersive visualization systems, AR/VR/MR, medical imaging, and applied AI. He received his Ph.D. from Stony Brook University under Arie E. Kaufman and a B.S. from LUMS, Pakistan. He will join UIC as an Assistant Professor in Fall 2025. Education: Ph.D. in Computer Science, Stony Brook University (2015–2023) B.S. in Computer Science, LUMS, Pakistan (2010–2014) Research Interests: Dr. Boorboor designs visualization systems for scientific data exploration, leveraging immersive technologies like AR/VR. His work emphasizes human-centered design, applied AI, and novel interaction methods. Recent projects include Explainable XR , Silo , and NeuRegenerate . Publications & Awards: Over 20 peer-reviewed papers, patents in medical imaging, and awards including the IACS Junior Researcher Award and Stony Brook Chair Fellowship. His work has been presented at IEEE VIS, SIGGRAPH, and EuroVis. Teaching: Taught courses like CSE 366 (VR), EMP 532 (Big Data Systems), and mentored 17+ students. Currently recruiting students for his UIC lab.

Istvan Tomonمشاهده پروفایل

دانشیار

• Discrete Mathematics
• Extremal and Probabilistic Combinatorics
• Geometry

Istvan Tomon is an Associate Professor in the Department of Mathematics and Mathematical Statistics at Umeå University in Sweden. His research focuses on discrete mathematics, extremal and probabilistic combinatorics, and geometry. He leads research in combinatorial structures and graph theory, with recent work exploring hereditary families, symmetric chain decompositions, and Zarankiewicz problems. His publications demonstrate broad expertise in combinatorial optimization, hypergraph theory, and geometric combinatorics. Recent articles show consistent focus on extremal problems in set systems, matrix combinatorics, and incidence geometry.

Robin Koytcheffمشاهده پروفایل

دانشیار

• Algebraic Topology
• Geometric Topology
• Knot Theory
• +۵ مورد دیگر

Robin Koytcheff is an Associate Professor in the Department of Mathematics at the University of Louisiana at Lafayette. He previously held postdoctoral positions at Brown University, the University of Victoria, and the University of Massachusetts Amherst. Ph.D., 2010, Stanford University B.S., 2005, Columbia University (Applied Math) His research lies at the intersection of algebraic and geometric topology, focusing on spaces of knots and links, configuration spaces, operads, and Vassiliev invariants. His work combines topological methods with algebraic structures to study embedding spaces and link homotopy. Recent publications analyze the homotopy types of knot spaces in solid tori (2021), cohomology classes via diagram complexes (2020), and Bott-Taubes integrals (2009–2020). His work often involves collaborations with mathematicians like Rafal Komendarczyk and Ismar Volić. Scientific awards include an NSF Postdoctoral Fellowship (2010–2013) and a PIMS Postdoctoral Fellowship (2013–2015). He currently holds NSF grant DMS-2405370 to support his research.

Yuly Billigمشاهده پروفایل

استاد

• Representation Theory
• Infinite-Dimensional Lie Algebras
• Vertex Algebras
• +۴ مورد دیگر

Yuly Billig is a Professor in the School of Mathematics and Statistics at Carleton University. He specializes in representation theory of infinite-dimensional Lie algebras, vertex algebras, and soliton theory. His research bridges algebraic structures with applications in mathematical physics, including studies of Kac-Moody algebras and their representations. He co-developed a Maple package for computations in Lie algebras and vertex algebras, available on GitHub. Billig founded the Carleton Math Enrichment Centre, offering courses in mathematics, physics, and computer science for students from grades 3 to 12. His work also extends to wavelet analysis and digital signal processing, reflected in his course MATH 4822/5822 on Wavelets and Signal Processing. His research has been published in leading journals such as Advances in Mathematics , Journal of Algebra , and Communications in Contemporary Mathematics . Key research interests include: Representation theory of infinite-dimensional Lie algebras Vertex algebras and their applications Soliton theory and nonlinear PDEs Geometric and algebraic structures in mathematical physics Recent publications focus on dense clusters in hypergraphs, sheaf modules on algebraic varieties, and gauge modules for vector field algebras. His contributions to computational tools and educational outreach highlight his dual role as a researcher and educator.

Prosenjit Boseمشاهده پروفایل

استاد

• Computational Geometry
• Algorithms
• Data Structures
• +۲ مورد دیگر

Prosenjit Bose is Chancellor's Professor in the School of Computer Science at Carleton University and Associate Dean of Research and International for the Faculty of Science. He holds PhD and MMath degrees from McGill University and University of Waterloo. Research specializes in computational geometry, graph algorithms, and geometric data structures. Core focuses: Geometric spanners and routing Online algorithms Graph embeddings Approximation methods Recipient of Carleton Research Achievement Award (2021), Premier's Research Excellence Award (2006), and multiple best paper awards. Directs the Computational Geometry Lab and has supervised 100+ graduate students. Served as NSERC Leader for Carleton University. Research applications include network routing, VLSI design, and geographic information systems.

Senja Barthelمشاهده پروفایل

استادیار

• Geometric topology
• Mathematical chemistry
• Spatial graphs
• +۵ مورد دیگر

Dr. Senja Barthel is an Assistant Professor at the Department of Mathematics, Faculty of Science, Vrije Universiteit Amsterdam. Her research bridges geometric topology and mathematical chemistry, focusing on spatial graphs and their applications in materials science. She is affiliated with the Center for Topology and Applications Amsterdam, Amsterdam Sustainability Institute, and NWO DIAMANT cluster. Current projects include Topology of molecular braids (NWO M1 grant), geometrical analysis for mass transport, and contributions to the NWA Emergence Consortium (WP4.3 and WP4.4). Research interests: entanglements in spatial graphs, embeddings in surfaces, pore geometry in materials, energy landscapes, crystal net topologies, and topological data analysis for molecular modeling. Teaching includes Linear Algebra, Differential Topology, and Calculus at BSc levels, with supervision of BSc and PhD projects. Her recent publications analyze ion diffusion in solids, thermal transport in ZIFs, and topological descriptors for crystal networks, reflecting interdisciplinary work combining mathematics, chemistry, and computational methods. Collaborators include Magnus Botnan (Dutch Applied Topology days) and Amber Mace (Uppsala Universitet).

• Combinatorial Group Theory
• Geometric Group Theory
• Decision Problems
• +۳ مورد دیگر

Gemma Crowe is a Heilbronn Fellow in Pure Mathematics, focusing on advanced research in combinatorial and geometric group theory. Her work addresses decision problems, conjugacy growth, formal language theory, and semigroups. She actively contributes to the theoretical foundations of group theory and its intersections with topology and algebra. Her research interests revolve around the structural properties of groups, particularly dihedral Artin groups, automorphism groups of free groups, and conjugacy languages. These topics explore the interplay between algebraic structures and geometric/topological frameworks, with applications in understanding group dynamics and language formalisms. Recent work highlights include studies on conjugacy geodesics in Artin groups, twisted conjugacy in torus knot groups, and the topology of automorphism groups. These contributions advance the field's understanding of group behavior and its computational aspects.

• Algebra
• Representation Theory
• Semigroup Theory
• +۳ مورد دیگر

Marianne Johnson is a Senior Lecturer in the School of Mathematics at the University of Manchester. She is a core member of the tropical mathematics research group and collaborates with institutions including Birmingham, Queen Mary University of London, and Warwick through an LMS Joint Research Network. Her research focuses on algebra and combinatorics, including free Lie algebras, representation theory, semigroup theory, and tropical algebra/geometry. She has contributed to EPSRC-funded projects such as 'Multiplicative Structure of Tropical Matrix Algebra' and 'Modular Lie Powers and Applications,' and participated in the CICADA interdisciplinary project. Her research interests span a wide array of algebraic topics: free Lie algebras explore the structure of non-associative algebras, while representation theory examines how algebraic structures act on vector spaces. Semigroup theory and tropical algebra involve studying combinatorial and geometric properties of matrices and monoids over semirings. Recent work includes studies on plactic-like monoids, tropical matrix identities, and linear functions preserving Green's relations. Johnson has co-authored over 29 publications, with recent trends emphasizing tropical algebra's applications to geometric and algorithmic problems, such as tropical matrix groups and hyperplane arrangements. Her work bridges pure mathematics with interdisciplinary fields like computational dynamics and healthcare through collaborations like CICADA. Notable projects include analyzing upper triangular tropical matrices and exploring NP-completeness in gossip monoids. She has advised three research students and contributed to grants involving EPSRC-funded projects. Her affiliations include the Data Science Institute, Algebra research group, and Tropical Mathematics cluster at Manchester. Her work also intersects with Digital Futures initiatives, reflecting her commitment to advancing computational and theoretical mathematics.

• Mathematics
• Analysis
• Mechanical Engineering
• +۲ مورد دیگر

Xiao Ma is a Donald J. Lewis Research Assistant Professor in the Department of Mathematics at the University of Michigan, located within the College of Literature, Science, and the Arts. His academic work bridges mathematics and interdisciplinary applications in mechanics, materials science, and soft matter. He holds a Ph.D. from Princeton University (2023) and a B.S. from the University of Science and Technology of China (2018). Dr. Ma’s research focuses on topological mechanics, metamaterials design, and geometric principles governing material behavior. His studies explore novel mechanical systems, such as origami-inspired structures, topological neural networks, and stress dynamics in colloidal gels. Recent work emphasizes wave control in auxetic media and fracture mechanics in topological lattices. His publications span topics including active matter dynamics, frustrated self-assembly, and mechanical metamaterials. Collaborative efforts involve interdisciplinary teams addressing challenges in structural engineering, biophysics, and computational mechanics. Despite no explicitly listed awards, his contributions reflect innovative approaches to complex mechanical systems. Advising and grants: While no specific grants or student advisees are mentioned, his role as a research professor suggests active involvement in mentoring graduate students and postdoctoral researchers. His laboratory likely focuses on experimental and theoretical studies of mechanical systems, though specific lab names are not provided in the text.

Charith Abhayaratneمشاهده پروفایل

مدرس ارشد

• Signal Processing
• Machine Learning
• Multimedia Security
• +۷ مورد دیگر

Dr. Charith Abhayaratne is a Senior Lecturer and EEE Foundation Year Tutor at the School of Electrical and Electronic Engineering, University of Sheffield. He leads the Communications Research Group and serves as the accreditation team lead for the school. With qualifications including a PhD from the University of Bath and a B.E. from the University of Adelaide, his research focuses on signal processing, machine learning, multimedia security, and video coding. His work explores blockchain for content protection, visual salience in robotics, human activity recognition, and advanced video coding techniques (HDR, UHD, 360° video). His research has been funded by Innovate UK, EPSRC, and industry partners. Education: B.E. (Electrical and Electronic Engineering), The University of Adelaide, Australia (1998) PhD (Electronic and Electrical Engineering), University of Bath, UK (2002) PGCertHE (Higher Education), University of Sheffield (2008) Fellow of the Higher Education Academy (FHEA), Member of the Institution of Engineering and Technology (MIET), Member of IEEE (MIEEE) Research Interests: His work spans multimedia security (data hiding, blockchain), computer vision (visual salience, object recognition), and video coding (HDR/UHD). Current projects include robotic vision applications, assisted living through activity recognition, and international standards development (JPEG/MPEG). He has contributed to scalable video standards and serves on technical committees for IEEE, EURASIP, and APSIPA. Awards & Service: Recipient of the Alain Bensoussan Fellowship (ERCIM, 2002) Associate Editor for IEEE Transactions on Image Processing, IEEE Access, and Elsevier JISA Member of EPSRC Peer Review College and British Standards Institution (BSI) Grants & Labs: Active grants from Innovate UK and EPSRC support projects in multimedia security and video coding. His lab leads interdisciplinary work in AI-driven visual analytics and secure media distribution frameworks.

Jens Vygenمشاهده پروفایل

استاد

• Combinatorial Optimization
• Approximation Algorithms
• Chip Design
• +۴ مورد دیگر

Prof. Jens Vygen is a full Professor of Discrete Mathematics at the University of Bonn's Research Institute for Discrete Mathematics. He specializes in combinatorial optimization, approximation algorithms, and their applications to chip design and vehicle routing. He has directed large-scale industrial collaborations and supervised over 20 PhD students, including Vera Traub. His work includes co-authoring influential textbooks like Combinatorial Optimization: Theory and Algorithms and Approximation Algorithms for Traveling Salesman Problems . Research highlights include advancements in TSP approximation algorithms, Steiner tree optimization, and network flow algorithms. He has organized major events like the IPCO conference and served on editorial boards of leading journals. Awards include teaching excellence and best paper recognitions at SODA and IPCO. Teaching focuses on advanced topics in discrete mathematics, approximation algorithms, and combinatorial optimization. Courses span undergraduate to graduate levels, emphasizing algorithm design, graph theory, and practical implementations. Labs/teams: Core contributor to Bonn's Hausdorff Center for Mathematics and Bonn's discrete optimization research group. Active in developing algorithms for VLSI routing (BonnRoute) and chip design tools (BonnPlace).

Petra Mutzelمشاهده پروفایل

استاد

• Graph Algorithmics
• Graph Learning
• Combinatorial Optimization
• +۳ مورد دیگر

Petra Mutzel is a Professor of Computer Science at the University of Bonn. Her research focuses on graph algorithmics, temporal networks, and combinatorial optimization with applications in data science and bioinformatics. She holds a PhD in Computer Science from the University of Cologne (1994) and a Diplom in Mathematics from the University of Augsburg (1990). Her work emphasizes algorithmic solutions for complex graph problems, including temporal graph analysis, graph learning, and optimization frameworks for real-world networks. She has contributed to open-source libraries like Tglib for temporal graph processing and frameworks like Scaffold Hunter for medicinal chemistry. Her research spans theoretical foundations and practical implementations, with notable contributions to graph drawing, vehicle routing optimization, and protein complex analysis. Mutzel’s recent publications (2022-2025) explore temporal network dynamics, robust combinatorial optimization, and scalable graph kernel methods. She actively engages in academic leadership, organizing conferences such as WALCOM 2022, and serves on editorial boards for journals in algorithms and computational geometry.

Roman Vershyninمشاهده پروفایل

استاد

• High-Dimensional Probability
• Random Matrices
• Applied Mathematics
• +۴ مورد دیگر

Roman Vershynin is a Professor in the Department of Mathematics at the University of California, Irvine (UCI). His research focuses on high-dimensional probability, random matrices, and their applications in data science, machine learning, and privacy-preserving technologies. He is particularly known for his work on the theoretical foundations of differential privacy, synthetic data generation, and the mathematical underpinnings of neural networks. Vershynin’s contributions bridge probability theory with practical challenges in high-dimensional data analysis. His research interests include random matrix theory, geometric functional analysis, and the interplay between probability and computational complexity. Notable works include developing frameworks for differentially private synthetic data and analyzing the capacity of neural networks. He authored the influential textbook High-Dimensional Probability: An Introduction with Applications in Data Science , which is a key resource in the field. Vershynin’s recent work emphasizes the privacy-utility tradeoff in synthetic data generation, leveraging tools from metric geometry and stochastic processes. He collaborates on projects funded by the National Science Foundation, focusing on mathematical frameworks for high-dimensional data analysis and algorithmic privacy. His research has implications for secure machine learning, compressed sensing, and robust statistical estimation.