Find Academic Supervisors

Ricky Ini LiuView profile

Associate Professor

• Algebraic Combinatorics
• Algebraic Geometry
• Combinatorial Geometry
• +5 more

Ricky Ini Liu is an Associate Professor in the Department of Mathematics at the University of Washington. Previously, he held positions at North Carolina State University, the University of Michigan, and the University of Minnesota. He earned his Ph.D. in Mathematics from MIT in 2010 under Alexander Postnikov. His research focuses on algebraic combinatorics, particularly its intersections with algebraic geometry, combinatorial geometry, and representation theory. Key interests include Schubert polynomials, polytopes, Hopf algebras, and Kronecker coefficients. He has contributed to foundational work on birational rowmotion, Gelfand-Tsetlin polytopes, and Fomin-Kirillov algebras. Liu has taught a wide range of courses at UW, including special topics in dynamical algebraic combinatorics, combinatorial theory, and problem-solving. He has also been a key instructor at the Mathematical Olympiad Summer Program since 2007 and mentored undergraduates in research programs at the University of Minnesota, Duluth. His publications span high-impact journals like Selecta Mathematica and Journal of Combinatorial Theory , with recent work addressing topics such as determinantal formulas for Schubert polynomials and applications of flow polytopes to diagonal harmonics. Though no specific awards are listed, his extensive publication record and academic roles reflect significant contributions to combinatorial mathematics.

Zvezdelina StankovaView profile

Teaching Professor

• Algebraic Geometry
• Representation Theory
• Combinatorics
• +2 more

Zvezdelina Stankova is a Teaching Professor of Mathematics and Director and Founder of the Berkeley Math Circle at the University of California, Berkeley . Her contact details include an office in 713 Evans Hall and the email stankova@math.berkeley.edu . Research Interests: • Algebraic Geometry • Representation Theory • Combinatorics • Olympiad Problem-Solving • Mathematics Education Publications and Research Trends: Her work bridges Combinatorics and Algebraic Geometry , with a focus on permutation patterns, avoidance, and moduli spaces of curves. She has also contributed significantly to Mathematics Education through her leadership in the Berkeley Math Circle, emphasizing problem-solving techniques and outreach programs for students. Teaching and Outreach: Stankova has taught various courses at UC Berkeley, including MATH 52 Calculus II (2025), MATH 110 Linear Algebra , and MATH 74 Transition to Proofs . She actively engages with the Berkeley Math Circle, providing resources for mathematical competitions and advanced training for students.

László KozmaView profile

Assistant Professor

• Data Structures
• Algorithms
• Algorithmic Adaptivity
• +7 more

László Kozma is an Assistant Professor at the Theoretical Computer Science group of the Institute of Computer Science (Freie Universität Berlin). He obtained his PhD from Saarland University under Raimund Seidel, followed by postdoctoral positions at Tel Aviv University and TU Eindhoven. His research focuses on self-adjusting data structures , adaptive algorithms , and combinatorial optimization with applications to problems like the Traveling Salesman Problem, binary search trees, and geometric data structures. Academic Affiliation: Freie Universität Berlin (since 2018) Education: PhD in Computer Science (Saarland University, 2016); postdoc at Tel Aviv University and TU Eindhoven. His work explores the intersection of data structures, combinatorial algorithms, and geometric methods. He has made significant contributions to problems involving pattern-avoidance in inputs, saddlepoint detection , and self-adjusting heaps . Key areas include: Adaptive algorithms for pattern-avoiding inputs Optimal tree and heap structures Geometric and stochastic approaches to optimization Complexity analysis of classical algorithms Recent publications highlight efficient solutions for exponential cut problems (ESA 2025), balanced TSP partitioning (EuroCG 2025), and randomized saddlepoint algorithms (ESA 2024). His research often bridges theory and practice, exemplified by the smooth heap implementation and fun projects like Recursi and Cuckoo Hashing visualization.

Jason SmithView profile

Senior Lecturer

• Combinatorics
• Topology
• Topological Data Analysis
• +12 more

Jason Smith is a Senior Lecturer in Mathematics at the Department of Physics and Mathematics, Nottingham Trent University. His work bridges pure mathematics and neuroscience, focusing on combinatorial and topological methods for analyzing brain networks and functional data. His educational background includes: PhD in Computer and Information Science, University of Strathclyde (2015) MMath, University of Bath (2012) His research lies at the intersection of combinatorics, topology, and neuroscience. He applies tools from graph theory, topological data analysis (TDA), and algebraic topology to study the structure and function of neural systems. Key areas include the analysis of connectomes (such as C. Elegans and Drosophila), modeling brain network dynamics, and developing theoretical frameworks for understanding neural coding through combinatorial and topological lenses. His work often involves collaborations with neuroscientists and computational biologists. His recent publications demonstrate a strong trend toward interdisciplinary research, combining deep mathematical theory with applications in neuroscience. The articles span topics from the topology of directed flag complexes and tournaplexes to the combinatorics of permutation patterns and the Abelian sandpile model, all unified by their relevance to understanding complex biological networks. There is a clear progression from theoretical combinatorics toward computational and applied neurotopology. He has collaborated extensively with researchers from the University of Aberdeen, EPFL (including the Laboratory for Topology and Neuroscience and the Blue Brain Project), and other institutions. He has developed several open-source software tools such as Flagser-count, Tournser, and Deltser for computing persistent homology in directed networks, reflecting his commitment to computational reproducibility and tool development. He has presented his work in various venues, with talks and posters on topics including permutation posets, tournaplexes, and functional brain data classification. His research is supported by collaborative projects focusing on the topological analysis of neural systems and the mathematical foundations of pattern posets.

David BevanView profile

Lecturer

• Enumerative Combinatorics
• Asymptotic Combinatorics
• Probabilistic Combinatorics
• +7 more

David Bevan is a Lecturer in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. His research is centered on combinatorics, particularly in the areas of enumerative, asymptotic, probabilistic, and extremal combinatorics, with a focus on permutations and permutation classes. His research interests include: Permutation patterns and avoidance Limit shapes and permutons Monotone grid classes and structural combinatorics Random integer compositions and probabilistic models Graph theory and network structures Analytic combinatorics and asymptotic enumeration The trends in his recent publications (2025–2017) reflect a deep and consistent focus on the structural and asymptotic behavior of discrete combinatorial objects, especially permutations. His work often combines probabilistic reasoning, analytic techniques, and extremal analysis to derive enumeration results and characterise limiting behaviors. He frequently collaborates with researchers such as Dan Threlfall, Robert Brignall, and Sergey Kitaev. David Bevan has served in key professional roles, including: Guest Editor, Discrete Mathematics and Theoretical Computer Science (2023) Guest Editor, Enumerative Combinatorics and Applications (2021) Organiser, Permutation Patterns 2021 Virtual Workshop Organiser, Scottish Combinatorics Meeting 2023 Peer Reviewer, Combinatorial Theory (2023) He is the Principal Investigator on the Maths DTP 2020 project at the University of Strathclyde (2020–2025), focusing on combinatorial research with PhD student Daniel Threlfall. He has delivered numerous invited talks at international workshops and conferences, including at Oberwolfach, Dagstuhl, and the Permutation Patterns series. David Bevan leads research within the Strathclyde Combinatorics Group and maintains an active research blog. He teaches courses in graph theory, networks in finance, logic, computation, and computer systems, reflecting his interdisciplinary expertise bridging mathematics and computer science.

Arun SharmaView profile

Lecturer

• Combinatorics
• Ramsey Theory
• Error-Correcting Codes
• +1 more

Arun Sharma is a Lecturer in the Department of Mathematics at the University of California, Berkeley. He has been teaching at Berkeley since 2010 and is known for his work in combinatorics, Ramsey theory, error-correcting codes, and graph colorings. His research explores structural problems in discrete mathematics. Education: Ph.D. in Mathematics (2009) from UC Berkeley, B.A. in Mathematics (2001) from Washington University in St. Louis. Sharma’s research focuses on combinatorial structures, particularly permutations and sequences avoiding arithmetic progressions. His work intersects with Ramsey theory and applications in error-correcting codes, addressing foundational problems in discrete mathematics. His publications primarily investigate patterns in permutations and integer sequences, emphasizing avoidance of arithmetic progressions. These studies contribute to broader combinatorial theory and its applications. Scientific Awards: Outstanding Instructor Award, UC Berkeley (2017) Outstanding GSI Award, UC Berkeley (2009) Putnam Prize, Washington University (2001) VIGRE Fellowship (2001) Compton Fellow, Washington University (1997) Sharma has served as a referee for Discrete Mathematics and the American Mathematical Monthly . His own thesis, The Structure of 3-Free Permutations (2009), was advised by Ronald Graham and Mark Haiman. Contact: asharma18@berkeley.edu | Personal Website

• Probability Theory
• Random Walks
• Percolation Theory
• +3 more

Christopher Hoffman is a Professor in the Department of Mathematics at the University of Washington. He holds a PhD from Stanford University (1996) and specializes in probability theory, stochastic processes, and related areas such as percolation, ergodic theory, and combinatorics. His research explores topics including activated random walks, first-passage percolation, and self-organized criticality. He teaches courses like Math 124 Calculus I and maintains active involvement in academic outreach through Google Scholar and LinkedIn. Education: PhD in Mathematics, Stanford University, 1996 Research focuses on probabilistic models with applications to statistical physics and graph theory. Key interests include analyzing phase transitions, geodesic paths in percolation models, and properties of interacting particle systems. Recent work addresses critical density thresholds in activated random walks and scaling limits of stochastic processes. Hoffman frequently collaborates on interdisciplinary projects involving combinatorics and ergodic theory. Teaching responsibilities include foundational calculus courses and maintaining detailed lecture notes for students. His work has been supported by grants from the National Science Foundation and other institutions.

Robert JohnsonView profile

Senior Lecturer

• extremal combinatorics
• graph theory
• probabilistic combinatorics
• +3 more

Dr. Robert Johnson is a Senior Lecturer in Pure Mathematics at Queen Mary University of London, affiliated with the School of Mathematical Sciences. He leads the Communication and Public Engagement for the Centre for Combinatorics, Algebra and Number Theory. His research focuses on extremal combinatorics, graph theory, and probabilistic combinatorics, with particular emphasis on extremal problems on graphs, set systems, permutations, and discrete hypercube structures. Robert Johnson earned his PhD from the University of Cambridge in 2003 and joined Queen Mary in 2004 after a postdoctoral position at the London School of Economics. His work has contributed significantly to combinatorial optimization, Ramsey theory, and hypercube graph analysis. He has supervised multiple PhD students, including Trevor Pinto (2016), A Nicholas Day (2017), and Natalie Behague (2020), with current advisees Belinda Wickes and Asier Calbet Ripodas. His research explores topics such as resistor network optimization, synchronizing automata, and extremal set systems, with applications in discrete mathematics and theoretical computer science. Notable contributions include studies on multicolour Ramsey numbers of odd cycles and Turán properties in hypercube intersection graphs. Johnson's publications span over two decades, covering areas like permutation correlation, hypercube saturation, and Kneser graph Hamiltonicity. He is actively involved in mentoring and welcomes inquiries from prospective PhD candidates. His affiliations include the Combinatorics group at Queen Mary’s School of Mathematical Sciences and the Centre for Combinatorics, Algebra and Number Theory, where he drives public engagement initiatives.

• Combinatorics
• Enumerative Mathematics
• Discrete Mathematics
• +1 more

Daniel Warren is an Associate Professor of Instruction in Mathematics at the University of Texas at Arlington's College of Science. Specializes in combinatorics and discrete mathematics with emphasis on enumerative problems and pattern avoidance. Research examines combinatorial structures including permutation patterns, packing densities, and discrete optimization problems. Current investigations focus on enumerative combinatorics and discrete mathematical relationships. Publications explore permutation avoidance, packing densities in combinatorial patterns, and discrete optimization frameworks, establishing foundational contributions to enumerative combinatorics. Awards: MAA Faculty of the Year (2019-2020) Supervision: Mentored undergraduate thesis on graphical representations of Grimm's conjecture and minimal interval lengths.

Neal MadrasView profile

Professor

• Probability Theory
• Discrete Mathematics
• Mathematical Modeling in the Sciences
• +5 more

Neal Madras is a Full Professor in the Department of Mathematics and Statistics at York University's Faculty of Science. His research focuses on probability theory, discrete mathematics, and mathematical modeling in the sciences. He explores applications in statistical mechanics, theoretical computer science, communications networks, and biological systems. Notable interests include self-avoiding walks, polymer behavior modeling, and disease progression mechanisms. Madras has contributed to interdisciplinary studies, such as HIV dynamics and mosquito population modeling under climate influences. He is also actively involved in mathematics competitions like the Canadian Mathematical Olympiad. His work bridges theoretical rigor and practical applications, with a focus on stochastic processes, combinatorial problems, and computational methods. Publications span topics from graph theory and knot invariants to epidemic control strategies and polymer adsorption. Madras maintains an active research program, engaging with both foundational mathematical questions and real-world problem-solving.

Amy N. MyersView profile

Senior Lecturer

• Combinatorics
• Probability Theory
• Enumerative Combinatorics
• +3 more

Amy N. Myers serves as Senior Lecturer in Mathematics and Math Program Coordinator at Bryn Mawr College's Department of Mathematics, where she teaches core courses including Calculus I-II, Multivariable Calculus, Probability Theory, and specialized graduate seminars in Enumerative Combinatorics and History of Mathematics. Her academic credentials include a Ph.D. in Mathematics from Dartmouth College (1999), establishing her foundational expertise in discrete mathematical structures. Dr. Myers' research demonstrates exceptional depth in combinatorial mathematics , particularly in pattern avoidance phenomena and probabilistic enumeration . Her work on interval orders bridges order theory with topological combinatorics, while her contributions to the Coupon Collector's Problem reveal novel asymptotic behaviors with applications in computational biology. The SIGEST recognition of her probability research by SIAM Review underscores its interdisciplinary significance across theoretical computer science and stochastic modeling. Analysis of her publication trajectory shows consistent innovation in multiset permutation statistics and forbidden substring constraints, with recent focus on shellability properties in ordered structures. Her combinatorial frameworks increasingly incorporate computational topology, reflecting evolving methodological sophistication. No scientific awards are documented in the available institutional records. As Math Program Coordinator, Dr. Myers oversees curriculum development and student advising for mathematics majors, though specific mentorship details remain undisclosed. Grant funding information is not publicly accessible through current university channels. Research infrastructure details including laboratories or collaborative teams are not referenced in her official academic profile.

Laszlo KozmaView profile

Assistant Professor

• Data Structures
• Algorithms
• Combinatorics
• +4 more

László Kozma is an Assistant Professor at Freie Universität Berlin in the Theoretical Computer Science department. He obtained his PhD at Saarland University under Raimund Seidel, followed by postdocs at Tel Aviv University and TU Eindhoven. His work focuses on data structures , combinatorics , and algorithmic adaptivity , with significant contributions to self-adjusting heaps, binary search trees, and geometric optimization. Recent research includes pattern-avoiding sequences and saddlepoint algorithms . His publications span exponential algorithms , TSP variants , and heap structures , with a recurring theme of connecting combinatorial geometry to algorithm design. Co-authors include leading researchers like Robert Tarjan, Uri Zwick, and Haim Kaplan. Key software implementations (e.g., smooth heap ) are publicly available. He has developed tools like Cuckoo Hashing Visualization and the historical WikipediaVision project, demonstrating practical engagement with algorithmic concepts. His mathematical genealogy traces back to classical researchers.

Jason P. SmithView profile

Senior Lecturer

• Combinatorics
• Algebraic Topology
• Topological Data Analysis
• +7 more

Jason P. Smith is a Senior Lecturer in Mathematics within the Department of Physics and Mathematics at Nottingham Trent University. His research bridges combinatorics, algebraic topology, and neuroscience, focusing on the application of topological data analysis to understand neural connectivity and brain function. His educational background includes a Ph.D. in Computer and Information Science from the University of Strathclyde (2012–2015), supervised by Einar Steingrímsson, and an MMath from the University of Bath (2008–2012). Smith's research interests center on combinatorics, particularly permutation patterns and posets, and algebraic topology, especially persistent homology and directed flag complexes. He applies these mathematical tools to neuroscience, modeling cortical connectivity and neural coding strategies. His work often involves developing computational methods for analyzing complex networks. The recent publications reflect a strong trend toward interdisciplinary research combining topology, combinatorics, and neuroscience. His work explores how the structure of neural networks influences information processing, using tools like tournaplexes and flag complexes to extract topological features from connectomic data. Email: jason.smith@ntu.ac.uk Google Scholar GitHub ORCID CV He has developed several open-source software packages including Tournser, Flagser-count, and Deltser, which are used for computing persistent homology in directed networks. He previously held research positions at the University of Aberdeen (2018–2020) and the University of Strathclyde (2015–2018), working on topological analysis of neural systems and combinatorial algebraic topology. No formal advising of students is listed, nor are any grants or scientific awards mentioned in the provided text. Smith is actively involved in the neurotopology research community and contributes to computational tools for topological data analysis in neuroscience. He is part of collaborative projects involving institutions such as the University of Aberdeen and international neuroscience initiatives.

Bridget TennerView profile

Professor

• Combinatorics
• Algebraic combinatorics
• Enumerative combinatorics
• +5 more

Bridget Tenner is a Professor of Mathematics in the Department of Mathematical Sciences at DePaul University's College of Science and Health. She joined the faculty in 2007 after earning her PhD in Mathematics from MIT in 2006 under Richard Stanley, with prior degrees (AB and AM) from Harvard University in 2002. Dr. Tenner's research focuses on combinatorics, particularly algebraic, enumerative, and topological aspects of permutation patterns, Coxeter groups, and Bruhat order. Her work bridges pure mathematics with applications in voting theory, electoral geography, and conference organization for equity. She has developed significant connections between reduced decompositions, pattern avoidance, and geometric structures. Analysis of her recent publications reveals a strong emphasis on permutation patterns, particularly in Stirling permutations, boolean permutations, and signed permutations. Her work frequently connects combinatorial structures with algebraic properties, exploring relationships between pattern avoidance, reduced words, and geometric interpretations. She has made substantial contributions to understanding the combinatorial properties of Coxeter groups and their applications to voting theory and electoral districting. Dr. Tenner has been recognized as a Fellow of the American Mathematical Society, a significant honor in the mathematical community. Her collaborative work spans numerous institutions and demonstrates strong mentorship through co-authorship with early-career mathematicians. She maintains an active research program with consistent high-impact publications across mathematics journals and interdisciplinary venues including Political Geography. Dr. Tenner also contributes to the mathematical community through initiatives like the Database of Permutation Pattern Avoidance and advocacy for equitable conference practices.

Nathan McNewView profile

Associate Professor

• Cryptography
• Combinatorics
• Analytic Number Theory
• +3 more

Nathan McNew is an Associate Professor in the Department of Mathematics at Towson University. His research focuses on Cryptography, Combinatorics, and Analytic Number Theory, with notable contributions to prime factor distribution, geometric progression-free sets, and divisor graph analysis. He holds a Ph.D. in Mathematics from Dartmouth College (2015) and a B.S. in Mathematics from the University of Denver (2010). Education Ph.D., Mathematics, Dartmouth College, 2015 B.S., Mathematics, University of Denver, 2010 Research Interests McNew’s work bridges combinatorial methods with number-theoretic problems, particularly in analyzing distributions of prime factors, geometric progression avoidance, and multiplicative structures in integers. Recent studies include: Intermediate prime factor distributions in number fields Powerfree polynomial behavior in finite fields Explicit bounds for gaps between square/cubefree integers Grants & Advising While specific grants are not detailed here, his research has been supported through collaborative projects. No advisees are listed in current records. Labs/Teams McNew collaborates actively with institutions like Dartmouth College and the University of Denver on analytic number theory projects. His work often involves interdisciplinary approaches combining algebraic, combinatorial, and probabilistic techniques.