جست‌وجوی استاد و پژوهشگر

• Commutative Algebra
• Algebraic Geometry
• Hyperplane Arrangements
• +۴ مورد دیگر

Ştefan Tohăneanu is a Professor in the Department of Mathematics and Statistical Science at the University of Idaho , affiliated with the College of Science. His academic journey includes a Ph.D. in Mathematics from Texas A&M University (2007), and M.S. degrees in Algebra (2001) and Analysis (2001) from the University of Bucharest, where he also earned a B.S. in Mathematics (1997). Research Focus: Commutative Algebra, Hyperplane Arrangements, Matroid Theory, and applications to Coding Theory, including generalized Hamming weights, Orlik-Terao algebras, and homological properties of ideals. Publications: Recent work explores Betti numbers, Jacobian ideals, logarithmic derivations, and connections between algebraic invariants and coding theory problems like minimum distance computation and error correction. Collaborations: Engages with global research networks through affiliations with institutions such as Texas A&M University, University of Bucharest, and University of Idaho.

Illya V. Hicksمشاهده پروفایل

استاد

• Combinatorial Optimization
• Integer Programming
• Graph Theory
• +۵ مورد دیگر

Illya V. Hicks is a Professor in the Computational and Applied Mathematics Department at Rice University. He holds a PhD from Rice University (2000) and a BS from Texas State University (1995). His research focuses on combinatorial optimization, integer programming, graph theory, and matroid theory, with applications in social networks, cancer treatment, and network design. He has advised numerous doctoral, post-doctoral, and masters students. Education: PhD and MA in Computational and Applied Mathematics, Rice University, 2000 BS in Mathematics, Texas State University, 1995 Research Interests: Utilizing graph decomposition techniques to solve NP-complete problems, including branch decompositions and matroid circuit problems. Applications include sensor network design, healthcare logistics, and algorithmic graph theory. Awards: Recognized with the 2015 Presidential Mentoring Award (Rice University), 2010 Forum Moving Spirit Award (INFORMS), and the 2005 Optimization Prize for Young Researchers. Grants and Projects: Includes NSF-funded research on branch decomposition techniques, submodular optimization, and healthcare service distribution. Active in promoting minority participation in operations research through travel grants and mentoring initiatives. Labs/Teams: Engaged in collaborative research on graph algorithms, combinatorial optimization, and interdisciplinary applications in healthcare and engineering.

Laura Andersonمشاهده پروفایل

دانشیار

• Combinatorics
• Topology
• Matroid Theory
• +۳ مورد دیگر

Laura Anderson is an Associate Professor in the Department of Mathematics at Binghamton University. She holds a Ph.D. from MIT (1994) and has been affiliated with Binghamton since 2001. Her research focuses on Combinatorics and Topology, with a specialization in matroid theory, hyperplane transversals, and topological combinatorics. She teaches advanced courses such as Introduction to Combinatorics (Math 511) and Discrete Mathematics (Math 314). Her academic contributions include groundbreaking work on oriented matroids, combinatorial Grassmannians, and hyperfield applications. Anderson has advised multiple Ph.D. students, including Olakunle Abawonse, Ulysses Alvarez, and Leandro Junes, whose theses explore topics like matroid extensions and tropical phased matroids. She actively participates in academic conferences, co-organizing the Binghamton University Graduate Conference in Algebra and Topology (BUGCAT). Anderson’s research integrates algebraic topology with discrete mathematics, addressing geometric realizations, hyperfield structures, and topological invariants. Her pedagogical innovations include experimenting with flipped classroom methods in calculus education. She maintains an active presence in academic service, contributing to journal reviews and editorial work in combinatorial geometry.

David Perkinsonمشاهده پروفایل

استاد

• Combinatorics
• Graph Theory
• Algebraic Geometry
• +۵ مورد دیگر

David Perkinson is a Professor of Mathematics at Reed College, where he holds a position in the Department of Mathematics. His research focuses on combinatorics, algebraic geometry, and discrete mathematics, with a particular emphasis on sandpile models, graph theory, and matroid theory. He is the author of the textbook *Divisors and Sandpiles: An Introduction to Chip-Firing*, which explores the combinatorial theory of chip-firing on graphs. Perkinson has also developed software tools like the Sandpile Java App, which visualizes and analyzes the Abelian Sandpile Model. He organizes the Cascade Lectures in Combinatorics (CALICO), a series of conferences funded by the National Science Foundation, aimed at fostering collaboration among researchers in combinatorics. His work bridges discrete mathematics with algebraic geometry, emphasizing connections between graph theory and geometric structures. Perkinson teaches advanced courses in analysis and contributes to the academic community through his research on topics such as divisor theory on graphs, sandpile groups, and combinatorial game theory. His recent publications (2015–2024) address matroid theory, sandpile dynamics, and applications of algebraic methods to discrete systems.

John MacLaren Walshمشاهده پروفایل

استاد

• Information Theory
• Network Coding
• Distributed Computing
• +۴ مورد دیگر

John MacLaren Walsh is a Professor in the Department of Electrical and Computer Engineering at Drexel University, where he leads the Adaptive Signal Processing and Information Theory Research Group. He holds BS, MS, and PhD degrees from Cornell University, all completed under Dr. C. Richard Johnson, Jr. His research spans information theory, network coding, distributed computing, and machine learning applications in patent analysis. His work focuses on: Bounding entropic vectors and their impact on communication networks Rate region computation for network coding and distributed storage Information theory for distributed function computation Machine learning-enhanced patent processing systems Publications emphasize entropy geometry, network coding complexity, distributed algorithms, and patent analysis, with consistent themes of optimization and combinatorial methods. Recent work (2016-2019) shows increased focus on probabilistic supports and computational efficiency in network coding. Awards: 2011 NSF CAREER Award for 'Entropy Geometry in Variational Inference Signal Processing' He has advised PhD students on topics like entropy region mapping, network coding, and distributed control. Key grants include NSF CAREER and AFOSR funding for wireless network overhead control. He directs the Adaptive Signal Processing and Information Theory Research Group, which develops algorithms for network coding, distributed storage, and patent analysis systems.

Jose Israel Rodriguezمشاهده پروفایل

دانشیار

• Applied Algebraic Geometry
• Algebraic Statistics
• Nonlinear Algebra
• +۷ مورد دیگر

Jose Israel Rodriguez is an Associate Professor in the Department of Mathematics at the University of Wisconsin-Madison. His research bridges applied algebraic geometry and algebraic statistics, focusing on nonlinear algebra, maximum likelihood estimation, monodromy, and polynomial systems in engineering and science applications. Primary Affiliation: Department of Mathematics , UW-Madison Additional Affiliations: Department of Electrical & Computer Engineering , Institute for Foundations of Data Science Research Interests : Applied algebraic geometry for nonlinear eigenvalue problems and kinematics Algebraic statistics in nearest point problems and likelihood geometry Numerical methods for monodromy, Galois groups, and polynomial optimization Teaching and Mentorship : Co-organized the Collaborative Undergraduate Research Laboratory (CURL) for Spring 2020 Advises PhD students Julia Lindberg and Zinan Wang , with Bernd Sturmfels as his own PhD advisor Developed software tools like Multiregeneration and Decomposable Sparse Polynomial Systems Academic Contributions : Authored over 20 peer-reviewed publications in journals like SIAM Journal on Applied Algebra and Geometry, Foundations of Computational Mathematics, and Journal of Symbolic Computation Organized international conferences including Monodromy and Galois Groups in Enumerative Geometry and SIAM AG19 Active member of the SIAM community and developer of the Matroids Day seminar

Thomas Lamمشاهده پروفایل

استاد

• Algebraic Combinatorics
• Total Positivity
• Cluster Algebras
• +۵ مورد دیگر

Thomas Lam is a professor of mathematics at the University of Michigan , specializing in algebraic combinatorics, total positivity, and connections to mathematical physics. His work bridges cluster algebras, positive geometry, and integrable systems, with applications to scattering amplitudes in quantum field theory. Lam has collaborated extensively with physicists such as Nima Arkani-Hamed and mathematicians like Pavlo Pylyavskyy and Mark Shimozono. Key research areas: Cluster algebras, total positivity, electrical networks, positroid varieties, and quantum cohomology. Notable contributions: Defining polypositroids, proving regularity theorems for totally nonnegative flag varieties, and establishing cluster structures in braid varieties. Recent work focuses on positive geometries , including the amplituhedron and moduli spaces of points on projective lines, with implications for particle physics. His articles often explore dual graded graphs, K-theoretic Schubert calculus, and the interplay between combinatorics and algebraic structures. Lam's research has been supported by NSF grants, including DMS-0748636 and DMS-1249708 .

Euiwoong Leeمشاهده پروفایل

استادیار

• Approximation Algorithms
• Hardness of Approximation
• Discrete Optimization
• +۳ مورد دیگر

Euiwoong Lee is an Assistant Professor in the Computer Science and Engineering Division at the University of Michigan. He holds a PhD from Carnegie Mellon University, advised by Venkatesan Guruswami, and has held postdoctoral positions at New York University and the Simons Institute for the Theory of Computing. His research focuses on approximation algorithms, hardness of approximation, and parameterized complexity. **Education:** PhD in Computer Science, Carnegie Mellon University (2017), advised by Venkatesan Guruswami Postdoctoral Fellowships: NYU (2017–2020), Simons Institute (2017–2020) **Research Interests:** Approximation Algorithms & Hardness of Approximation Convex Hierarchies (e.g., Sum-of-Squares) Clustering Algorithms (e.g., Correlation Clustering) Parameterized Complexity Facility Location & Metric Optimization **Awards:** Edmund M. Clarke Doctoral Dissertation Award (2017) Simons Award for Graduate Students in Theoretical Computer Science **Advising & Grants:** PhD Students: Anthony Della Pella, Aditya Anand, Amatya Sharma, Ian DeHaan Co-organizes the Michigan Theory Seminar **Labs/Teams:** Collaborates with researchers in approximation algorithms, optimization, and theoretical computer science at the University of Michigan and beyond.

• Algebraic Combinatorics
• Quasisymmetric Functions
• Schubert Calculus
• +۴ مورد دیگر

Vasu Tewari is an Assistant Professor (CLTA) at the University of Toronto, working across both the Downtown Toronto (St. George) and Mississauga (UTM) campuses. Their office is located at HU1015 (215 Huron), and they can be reached at vasu.tewari@utoronto.ca. As a member of the Department of Mathematics within the Faculty of Arts and Science, Professor Tewari contributes to both teaching and research activities at the university. Professor Tewari's research focuses on advanced topics in algebraic combinatorics, with particular expertise in: Quasisymmetric functions and their geometric interpretations Schubert polynomial theory and related structures Representation theory of symmetric groups and related algebras Combinatorial aspects of algebraic geometry Enumerative combinatorics with connections to symmetric functions Algebraic structures arising from combinatorial objects Analysis of Professor Tewari's recent publications reveals a consistent focus on the interplay between combinatorial structures and algebraic frameworks. Their work often explores generalizations of classical symmetric function theory through the lens of quasisymmetric functions, providing new insights into Schubert calculus, permutation statistics, and geometric combinatorics. A notable trend in their research is the investigation of stability phenomena in combinatorial structures and the development of new algebraic tools for studying these phenomena. Professor Tewari has made significant contributions to understanding the geometry of combinatorial objects through algebraic methods, particularly in the areas of permutahedral varieties, zonotopal algebras, and quiver representations. Their work bridges pure mathematics with potential applications in theoretical physics and computer science.

Mathias Drtonمشاهده پروفایل

استاد

• Graphical models
• Algebraic statistics
• Causal inference
• +۳ مورد دیگر

Prof. Mathias Drton holds the Chair of Mathematical Statistics at the Technical University of Munich (TUM), within the Department of Mathematics and School of Computation, Information and Technology. His research focuses on graphical models, algebraic statistics, causal inference, and multivariate data analysis. He has authored numerous publications in top-tier journals and conferences, including work on conditional independence, sparse factor analysis, and causal discovery in linear models. Drton has supervised a large number of theses, mentoring students in areas like high-dimensional statistics, graphical models, and causal inference. He is actively involved in teaching advanced courses such as 'Graphical Models in Statistics' and 'Fundamentals of Mathematical Statistics.' His academic contributions span theoretical developments in statistical methodology and computational tools, including R packages like SEMID and symRC . Drton collaborates internationally, contributing to projects like the TUM-ICL Mathematical Sciences Hub and Exzellenzcluster MCQST. His work bridges algebraic methods with statistical challenges, addressing identifiability in latent variable models and robust graphical modeling under non-Gaussian assumptions. Recent research emphasizes causal structure learning under partial homoscedasticity, distribution-free independence tests, and multi-domain causal representation learning. Drton’s lab actively explores applications in genomics, epidemiology, and machine learning, leveraging both theoretical rigor and practical computational methods.

• Algebraic Geometry
• Tropical Geometry
• Combinatorics
• +۳ مورد دیگر

Kristin Shaw is a Professor in the Department of Mathematics at the University of Oslo, specializing in Algebra, Geometry and Topology. She leads the research group on Algebraic and Topological Cycles in Tropical and Complex Geometries, funded by the BFS. Her office is located in room 1114 of Niels Henrik Abels hus, with contact information including email krisshaw@math.uio.no and phone +47 22855940. Shaw's research focuses on the connections between combinatorics and algebraic geometry over the real and complex numbers, with particular emphasis on tropical geometry. Her work bridges abstract mathematical theory with concrete geometric structures, exploring how combinatorial methods can illuminate deep properties of algebraic varieties. She has made significant contributions to understanding matroids, real algebraic curves, and the topology of hypersurfaces through tropical techniques. Her research demonstrates how combinatorial structures can reveal fundamental insights about algebraic varieties and their topological properties. Analysis of Professor Shaw's recent publications reveals a consistent focus on tropical geometry and its applications to classical algebraic geometry problems. Her work frequently examines the interplay between real and complex geometries, with particular attention to combinatorial structures underlying algebraic varieties. Key themes include matroid theory, enumerative geometry, and the topology of algebraic varieties, demonstrating how tropical methods can provide new insights into longstanding problems in algebraic geometry. Her research shows remarkable depth across multiple subfields while maintaining a coherent theoretical framework that connects combinatorial and geometric approaches. Professor Shaw leads the research group on Algebraic and Topological Cycles in Tropical and Complex Geometries, which is funded by the BFS. Prior to her position at the University of Oslo, she held postdoctoral positions at the Max Planck Institute Leipzig, the Technical University of Berlin, the University of Toronto, and participated in the Fields' Institute semester in Combinatorial Algebraic Geometry. Her collaborative work spans multiple international institutions, reflecting her active engagement in the global mathematical research community.

• Tropical Geometry
• Cluster Algebras
• Combinatorics
• +۵ مورد دیگر

David E Speyer is a Professor in the Department of Mathematics at the University of Michigan . His research focuses on algebraic problems with combinatorial flavors , particularly in tropical geometry , cluster algebras , and geometry of Lie groups . He has supervised multiple PhD students, including Shelby Cox, Will Dana, and John Wiltshire-Gordon, and collaborated on projects with undergraduates like Grant Barkley and Benjamin Branman. Education: PhD in Mathematics from UC Berkeley under Bernd Sturmfels; undergraduate at Harvard. Research: Key areas include tropical geometry , cluster algebras , and flag manifolds . His work often bridges combinatorics, algebraic geometry, and representation theory. Publications: Over 40 papers, including breakthroughs in cluster algebras , affine weak order , and braid variety cluster structures . Awards: Clay Research Fellow (2005-2010). Teaching: Coordinates courses like Math 593 (graduate algebra) and Math 214 , with a focus on inquiry-based learning .

Lauren K. Williamsمشاهده پروفایل

استاد

• Algebraic Combinatorics
• Cluster Algebras
• Mathematical Physics
• +۴ مورد دیگر

Lauren K. Williams is the Dwight Parker Robinson Professor of Mathematics at Harvard University and the Sally Starling Seaver Professor at the Radcliffe Institute. Her research focuses on algebraic combinatorics, cluster algebras, and mathematical physics, with notable contributions to the study of the positive Grassmannian, amplituhedron geometry, and integrable systems. She holds affiliations with Harvard’s Department of Mathematics and the Radcliffe Institute for Advanced Study. Her work bridges combinatorics, algebraic geometry, and physics, particularly in understanding geometric structures like the amplituhedron, which encode scattering amplitudes in quantum field theory. Key areas include cluster algebras, Schubert varieties, and applications of combinatorial methods to stochastic processes such as the asymmetric exclusion process (ASEP). Recent activities include organizing conferences on combinatorics, mathematical physics, and the legacy of mathematicians like Richard P. Stanley. Her research often explores connections between discrete structures and continuous systems, with a focus on positivity and geometric positivity principles. Awards and grants are not explicitly listed in the provided texts, but her contributions have been recognized through invitations to major international conferences and leadership in the field. She actively mentors students and postdocs in combinatorics and algebraic geometry.

June Huhمشاهده پروفایل

استاد

• Algebraic Geometry
• Combinatorics
• Matroid Theory
• +۵ مورد دیگر

June Huh is a Mathematics Professor at Princeton University's Department of Mathematics. His research focuses on the interplay between algebraic geometry, combinatorics, and matroid theory, with notable contributions to Hodge theory, tropical geometry, and log-concavity phenomena. He is actively involved in collaborative projects such as the FRG initiative on matroids, graphs, and algebraic geometry. Key research interests include matroid polytopes, Chow rings, Lagrangian geometry, and combinatorial applications of Hodge-Riemann relations. His work bridges discrete and continuous mathematics, with implications for enumerative geometry and geometric combinatorics. Recent publications explore topics like volume polynomials, Bergman fans, and singular Hodge theory in combinatorial geometries. He has received funding for interdisciplinary research through grants like the FRG Collaborative Research program. His contributions highlight innovative methods in geometric and algebraic combinatorics.

Mohit Singhمشاهده پروفایل

استاد

• Discrete Optimization
• Approximation Algorithms
• Combinatorial Optimization
• +۴ مورد دیگر

Mohit Singh is the Coca-Cola Foundation Professor at the H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology. He previously held positions at Microsoft Research (2011-2016) and as an Assistant Professor at McGill University (2010-2012). PhD in Algorithms, Combinatorics, and Optimization (ACO) at Carnegie Mellon University His research focuses on discrete optimization , approximation algorithms , and convex optimization , with applications to combinatorial optimization, submodular functions, and network design. He has contributed to topics like Sticky Brownian Rounding, integrality gaps, and online adaptive algorithms. His recent work includes theoretical advancements in matroid constraints, dimensionality reduction, and submodular maximization. He has published extensively in top conferences such as FOCS, SODA, ICML, and NeurIPS. He has been recognized with the Coca-Cola Foundation Professorship and served as Director of the Algorithms and Randomness Center at Georgia Tech (2019-2023). He has also held editorial roles and organized key academic workshops like the Bellairs Workshop on Approximation Algorithms (2011). His teaching includes advanced courses on approximation algorithms, combinatorial optimization, and linear inequalities. He has collaborated with institutions such as Microsoft Research and McGill University.