Find Academic Supervisors

• Applied Topology
• Sheaf Theory
• Category Theory
• +5 more

Justin M. Curry is a tenured Associate Professor in the Department of Mathematics and Statistics at the University at Albany SUNY. His research focuses on developing theoretical foundations for Topological Data Analysis (TDA) using sheaf theory and category theory. He completed his PhD at the University of Pennsylvania under Robert Ghrist and held a postdoc at Duke University. Recent activities include sabbaticals at the University of Oxford, VU Amsterdam, and the Max Planck Institute for Mathematics in the Sciences (MPI MiS). Education: PhD in Mathematics from University of Pennsylvania (2014) Visiting Associate at the Institute for Advanced Study (2009-2011) Research interests span applied topology with emphasis on algebraic and geometric models for space communications, topological deep learning, and inverse problems in TDA. Notable collaborations include NASA's TIMAEUS project (2020-2025) and contributions to the IEEE Aerospace Conference. His work bridges pure mathematics and engineering applications, particularly in distributed space networks and topological signal processing. Recent publications (2021–2024) explore decorated Reeb spaces, universal ℓ^p-metrics on merge trees, and topological attributed graphs for shape discrimination. He has delivered invited lectures at venues like the International Conference on Machine Learning (ICML) and the Max Planck Institute. Awards: NSF CRII Award (2020), NSF Grant for Enriched Topological Summaries (2019) Advising 5 PhD students and leading the NASA-funded TIMAEUS initiative ($650k), his lab integrates categorical methods with geometric deep learning frameworks. Current work includes algebraic models for space communication protocols and sheaf-theoretic approaches to shape space construction. Labs/Teams: Active member of the ATiA (Applied Topology and Inverse Problems) research group and collaborator with NASA's DTN (Disruption Tolerant Networking) working group.

• Nonlinear Partial Differential Equations
• Numerical Analysis
• Applied Computational Mathematics
• +3 more

Tori Fisher is a doctoral student and Graduate Research Assistant in the School of Mathematical and Statistical Sciences at Clemson University. She holds a B.S. in Mathematical Sciences from Clemson (2023) and focuses on applied and computational mathematics with emphases on nonlinear PDE analysis, numerical methods, and coding theory. Education: B.S., Mathematical Sciences, Clemson University, 2023 Her research interests include nonlinear partial differential equations , nonlinear solvers , Anderson Acceleration , and CSS-T code construction from Reed Muller codes . She has presented work at NCUWM 2023 and the AMS Southeast Sectional 2023 conferences. Notable achievements include the Samuel M. Martin Outstanding Senior Award (2023) and the Michael Case Award for promising PhD research (2024). She is expected to graduate in May 2028.

Dan A. SimoviciView profile

Professor

• Data Mining
• Machine Learning
• Information Theory
• +5 more

Dan A. Simovici is a Professor of Computer Science at the University of Massachusetts Boston, where he has served since 1985 and currently directs the Computer Science Graduate Program. He also holds an Honorary Professorship at the University of Iasi (Romania) and has held visiting positions at the University of Science and Technology Lille and Tohoku University. A Senior Member of IEEE and active in ACM and AAAI, his research integrates information theory, data mining, formal logic, and algebra. Education Ph.D. in Mathematics, University of Bucharest (1974) M.S. in Mathematics, University of Iasi (1970) M.S. in Electrical Engineering, Polytechnical Institute of Iasi (1965) Research Interests Dr. Simovici’s work centers on information-theoretic and linear-algebraic techniques in data mining , semantic database models, and the algebraic foundations of multiple-valued logic. His recent focus includes clustering validation via entropy measures, ultrametric structures in dissimilarity spaces, and the mathematical underpinnings of machine-learning algorithms. These themes are unified by a rigorous mathematical approach that bridges theory and practical data-analysis challenges. Books & Recent Publications Over the past decade, he has authored or co-authored major reference texts including Clustering – Theoretical and Practical Aspects (2021), Mathematical Analysis for Machine Learning and Data Mining (2018), and the 1004-page Linear Algebra Tools for Data Mining (2nd ed., 2023). His 2024 volumes Logical Foundations of Computer Science (2 vols.) and Introduction to the Theory of Formal Languages consolidate decades of scholarship. Scientific Awards & Honors Best Paper Award, AFIA (2000) Senior Member, IEEE Vice Chair, IEEE Computer Society Technical Committee for Multiple-Valued Logic Managing Editor, Journal of Multiple-Valued Logic and Soft Computing Editorial roles: International Journal of Parallel, Emergent and Distributed Systems and International Journal of Software and Information Technologies PhD Advising & Graduate Program Leadership Since 1984, Dr. Simovici has directed the Computer Science Graduate Program at UMass Boston, mentoring 12 PhD graduates (2002–2021) whose work spans data-mining algorithms, clustering, and machine-learning theory. He regularly organizes and chairs premier conferences such as ISMVL (International Symposium on Multiple-Valued Logic) and serves on program committees for KDD, PKDD, and DAWAK. Laboratories & Teams While no specific laboratory name is provided, Dr. Simovici’s graduate program leadership and extensive editorial and conference responsibilities effectively coordinate a distributed research group focused on theoretical computer science and data mining, collaborating with institutions in the U.S., Europe, and Asia.

Catalin ZaraView profile

Professor

• Differential Geometry
• Equivariant Cohomology
• K-Theory
• +3 more

Catalin Zara is a Professor in the Department of Mathematics at the University of Massachusetts Boston (UMass Boston), serving as Interim Associate Dean of the College of Science and Mathematics (CSM). He holds a Ph.D. in Mathematics from the Massachusetts Institute of Technology (MIT). His research focuses on differential geometry, equivariant cohomology and K-theory, combinatorial structures, and applications of distance metrics in finite spaces. He has published extensively in top-tier journals such as Advances in Mathematics and Journal of Combinatorics . Dr. Zara's work bridges pure and applied mathematics, with notable contributions to GKM theory, polynomial assignments, and combinatorial optimization. His recent projects include studies on balance weighing problems, windfarm geometry impacts, and Thue-Morse sequences. Teaching evaluations highlight his engaging style, challenging yet supportive approach, and ability to foster deep conceptual understanding across courses like Calculus, Linear Algebra, and advanced topics in combinatorics. He maintains an active research program with interdisciplinary applications, including collaborations in environmental science (bird mortality modeling) and computer science (medoid-based clustering). His office is located in Wheatley Hall and he is regularly involved in academic service roles such as department leadership and curriculum development.

Eric MoorhouseView profile

Professor

• Projective Geometry
• Codes and Designs
• Non-Associative Structures
• +6 more

Eric Moorhouse is a Professor of Mathematics in the Department of Mathematics and Statistics at the University of Wyoming, where he has served since joining the faculty in 1989 after appointments at the University of Oregon. His academic credentials include a Ph.D. in Mathematics (1987), M.Sc. in Mathematics (1984), and B.Sc. in Mathematics (1980), all from the University of Toronto. Dr. Moorhouse's research spans projective geometry, codes and designs, non-associative structures, algebraic combinatorics, and information theory, employing both experimental programming and theoretical methods from group theory, algebraic geometry, number theory, and mathematical logic. His interdisciplinary approach bridges combinatorial structures with algebraic and geometric frameworks to solve complex problems in finite geometry. His publication record demonstrates sustained focus on projective planes and combinatorial designs, with recent works emphasizing computational techniques and algebraic geometry applications. These contributions reveal evolving trends toward algorithmic solutions and cross-disciplinary synthesis in geometric combinatorics. He maintains active engagement in teaching across undergraduate and graduate mathematics curricula, reflecting his commitment to academic instruction at all levels.

Dane TaylorView profile

Assistant Professor

• Networks
• Data Science
• Complex Systems
• +4 more

Dane Taylor is an Assistant Professor at the University of Wyoming's School of Computing and Department of Mathematics and Statistics, with an adjunct appointment in Electrical Engineering and Computer Science. He joined UW in 2023 after serving as assistant professor at University at Buffalo (2017-2023). His research focuses on network science, complex systems, and data science methodologies. Education includes: Ph.D. Applied Mathematics, University of Colorado Boulder (2013) B.S. Electrical Engineering (bioengineering), University of Wyoming (2008) B.S. Physics, University of Wyoming (2008) Research interests span: network-based modeling, spectral theory, random matrix theory, neurocomputation, and self-organization in complex systems. His work develops mathematical frameworks for temporal/multilayer networks and simplicial complexes. Publication trends show consistent focus on network dynamics, topological data analysis, and applications in neuroscience, epidemiology, and social systems. Recent work explores machine learning integration with network theory and pandemic-related human mobility patterns. Awards and research support: NSF Algorithms for Threat Detection (ATD) grant NSF Mathematical Biology grant Nakatani Foundation (2020-2021) Simons Foundation (2018-2024) Postdoctoral Award for Research Excellence, UNC (2015) Teaching Award, UNC/HHMI (2014) ARCS Foundation Fellowship (2009-2012) NASA Space Grant Fellowship (2006) Organizational leadership includes: 2022 Northeast Regional Conference on Complex Systems, 2020 SIAM Workshop on Network Science, and multiple minisymposia for major conferences. Outside academia, enjoys hiking, snowboarding, and mountain biking.

Daniel HerdenView profile

Associate Professor

• Algebra
• Set Theory
• Combinatorics
• +2 more

Daniel Herden is an Associate Professor in the Department of Mathematics at Baylor University's College of Arts & Sciences. He earned his Habilitation (2013) and Dr. rer. nat. (2005) from the University of Duisburg-Essen, Germany. His research spans algebra-set theory interactions, combinatorics applications, and coding theory. Herden maintains strong international collaborations and currently serves on the problem proposal committee of the German Mathematical Olympiad. Research interests focus on constructing large algebraic structures under set-theoretic constraints, applications of infinite combinatorics to algebra, finite combinatorics in symplectic geometry and partitions, and emerging work in coding theory at the algebra-combinatorics interface. Herden's publication trends demonstrate sustained contributions to pure mathematics, with recent work expanding into applied combinatorics and coding theory. Earlier research emphasized foundational work in set-theoretic algebra and module theory. Scientific honors include: 3 Silver Medals at International Mathematical Olympiad (1997-1999) Ranked #2 in German Math Olympiad Hall of Fame 5 First Prizes in German Mathematical Olympiad 3 First Prizes at German Federal Math Competition He advises PhD students in algebra and combinatorics, with current joint supervision in coding theory. Former students have completed dissertations on incidence algebras, group automorphisms, and forcing methods in group theory.

Reeve HunterView profile

Lecturer

• Math Pedagogy
• Topological Dynamics
• Coding Applications
• +2 more

Reeve Hunter is a full-time Lecturer of Mathematics at Baylor University's College of Arts and Sciences. He teaches courses including Calculus, Linear Algebra, and Precalculus, employing pedagogical strategies enhanced by computational tools. His interdisciplinary interests intersect mathematics with digital media, music theory, and coding.

Charlotte AtenView profile

Research Fellow

• Combinatorics
• Universal Algebra
• Category Theory
• +3 more

Charlotte Aten is a Burnett Meyer Instructor at the University of Colorado Boulder's Department of Mathematics, part of the College of Arts and Sciences. Previously, she held a postdoctoral position at the University of Denver. Her research focuses on combinatorics, universal algebra, and category theory, with applications to machine learning and formal verification. A proponent of interdisciplinary work, she explores connections between algebraic structures and topological spaces, as well as categorical approaches to neural networks. Education: PhD in Mathematics (2022), University of Rochester, thesis: Finite Generation of Families of Structures Equipped with Compatible Group Actions Bachelor of Science in Mathematics (Honors, 2017), University of Rochester Associate of Science in Mathematics (Honors, 2014), Monroe Community College Research Interests: Functorial constructions of spaces from quasigroups, representation stability, categorified invariant theory, applied category theory in machine learning, and formal verification. Her work bridges abstract algebra with geometric and computational frameworks, emphasizing practical applications. Recognition: Provost’s Fellowship (2017), University of Rochester Doris Ermine Smith Award (2017), University of Rochester McNair Scholar (2015), University of Rochester Xerox STEM Scholarship (2014), Monroe Community College Teaching & Outreach: Taught courses at the University of Colorado Boulder and University of Denver, including Linear Algebra, Calculus, and specialized topics. Led undergraduate research programs (e.g., NSF REU/Grad for All), focusing on category theory and Python coding. Served as President of the University of Rochester’s AMS Graduate Student Chapter and Treasurer of outGRADS. Contributions: Authored textbooks, including Category Theory: A Concise Course (2019). Active on GitHub with repositories on algebraic structures and lattice theory. Maintains an educational YouTube channel on universal algebra and collaborates with Mastodon’s math-focused community (mathstodon.xyz).

Yuanlin LiView profile

Professor

• Algebra
• Number Theory
• Combinatorics
• +3 more

Yuanlin Li is a Professor of Mathematics at Brock University. He holds a PhD from Memorial University, an MSc from Nanjing University, and a BSc from Jiangsu University. His research focuses on group rings, combinatorial number theory, and algebraic structures, with applications in coding theory. Key interests include Zassenhaus conjectures, zero-sum problems, and homological properties of modules. Research Projects: Includes studies on unit groups of group rings, normalizer problems, and additive number theory. Interdisciplinary Work: Explores connections between rings and graphs (e.g., zero-divisor graphs) and combinatorial problems in group theory. He is affiliated with the Department of Mathematics and Statistics and maintains an active research program, though no specific grants or awards are listed in the provided text.

David JuedesView profile

Professor

• Algorithms
• Complexity Theory
• Approximation Algorithms
• +4 more

David Juedes is a Professor of Electrical Engineering and Computer Science and Associate Dean for Academics at Ohio University's Russ College of Engineering and Technology. He also directs the Avionics Engineering Center and is part of the Center for Scientific Computing and Immersive Technologies. Juedes holds a Ph.D. from Iowa State University (1994) and has taught courses ranging from introductory computer science to advanced graduate topics like computational complexity and formal languages. His research focuses on algorithms, complexity theory, approximation algorithms, and computational biology. Notable contributions include work on secure embedded systems (e.g., d-GUARD and DAGGER frameworks) and parameterized algorithm analysis. He has advised multiple graduate and undergraduate students in areas like parameterized algorithms and bioinformatics. Juedes has received awards including ACM Senior Membership (2010) and the Russ College Outstanding Research Paper Award (2004). His work spans 30+ years with over 80 publications in top journals/conferences. He actively promotes STEM education through initiatives like cybersecurity workshops for K-12 teachers and curriculum development for real-time systems and CORBA-based resource management. Labs/Teams: Director of Avionics Engineering Center, Core member of Center for Scientific Computing and Immersive Technologies.

Boris HasselblattView profile

Professor

• Dynamical Systems
• Hyperbolic Dynamics
• Chaos Theory
• +11 more

Boris Hasselblatt is a Professor in the Department of Mathematics at Tufts University's School of Arts and Sciences. He has been affiliated with Tufts since 1989, holding roles including Department Chair and Associate Provost (2014-2016). His research focuses on geometrically motivated hyperbolic dynamics chaos theory ergodic theory topological dynamics centralizers of dynamical systems and has produced over 5000 published pages, including the seminal textbook on dynamical systems. He has held visiting appointments at ETH Zurich, University of Tokyo, and IHES Paris. Hasselblatt's research spans the regularity of Anosov splittings ergodic theory for hyperbolic systems exotic Anosov flows degree-growth of monomial maps pointwise vs. uniform hyperbolicity differentiability of Hartman-Grobman linearizations His work connects dynamical systems with differential geometry, number theory, and coding theory. He has received NSF grants for Award #2020: VISION FOR DYNAMICS (2019-2020) School on Geometry and Dynamics (2014-2015) Tufts Math Circle (2012-2013) and held leadership roles across mathematical societies including Secretary of the American Mathematical Society (2021-present) Founding Editor of Journal of Modern Dynamics Founding Editor-in-Chief of Mathematics Research Reports AMS Council and Committees membership Teaching activities include advanced courses in Differential Equations Graduate and PhD thesis advising Master's thesis instruction Honors thesis supervision at Tufts University.

Xiang-dong HouView profile

Professor

• Finite Fields
• Permutation Polynomials
• Coding Theory
• +2 more

Xiang-dong Hou is Professor in the Department of Mathematics and Statistics at the University of South Florida. His research spans algebra, number theory, coding theory, cryptography, and combinatorics, with particular expertise in finite fields and permutation polynomials. Research develops novel approaches to polynomial factorization over finite fields and equivalence classification of rational functions. Applications include cryptographic Boolean function design and efficient coding theory implementations. Publications demonstrate innovative connections between abstract algebra and information security, particularly in developing new permutation polynomial families for cryptographic applications. Recent work advances theoretical frameworks for normal polynomial identification. Scientific Awards: No awards listed Supervises doctoral students in finite field applications and serves as editorial board member for Finite Fields and Their Applications journal.

Giacomo MicheliView profile

Associate Professor

• Applied Algebra
• Finite Fields
• Cryptography
• +2 more

Giacomo Micheli is Associate Professor in the Department of Mathematics & Statistics at University of South Florida's College of Arts and Sciences, and Co-Director of the Center for Cryptographic Research. Education includes a PhD in Mathematics from University of Zurich (2015) and MA/BA degrees from University of Rome (2012/2010). Research spans applied algebra and number theory with focus areas: Algebraic foundations of cryptography (finite fields, code equivalence) Locally recoverable codes for distributed storage Differential cryptanalysis of symmetric ciphers Current projects supported by NSF CAREER and RTG grants develop cryptographic primitives and analyze number-theoretic structures. Advises PhD students in algebraic coding and cryptanalysis. Serves as associate editor for Advances in Mathematics of Communications and Journal of Number Theory.

Betty Fyn-SydneyView profile

Lecturer

• Group Theory
• Representation Theory
• Coding Theory
• +2 more

Dr. Betty Fyn-Sydney is an Associate Lecturer in the Department of Computing at Goldsmiths, University of London, and holds concurrent roles as a Teaching Fellow at the University of Birmingham and a Lecturer at the University of Greenwich. She specializes in pure mathematics with a focus on group theory, representation theory, and coding theory. Her teaching spans foundational mathematics courses for computing students, including Mathematical Modelling and Problem Solving, and she oversees undergraduate research projects at the University of Birmingham. Education: PhD in Pure Mathematics, University of Birmingham (2013) MSci in Mathematical Sciences, University of Birmingham (2007) BSc in Statistics, Obafemi Awolowo University, Nigeria (2004) Research & Teaching: Dr. Fyn-Sydney’s research bridges abstract algebra (group theory) and applied mathematics (coding theory). She actively contributes to teaching across multiple institutions, leading tutorials in mathematical modelling for first-year undergraduates at Greenwich and supervising advanced projects at Birmingham. Her expertise also extends to linear algebra, number theory, and calculus instruction. Awards: No scientific awards explicitly mentioned in the provided materials. Advising & Grants: Supervises undergraduate mathematics projects at Birmingham but no specific grants or funding details are noted. Her academic service includes curriculum development in symbolic and numerical mathematics. Labs/Teams: No dedicated lab or research team described in the text.