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.

Fatma Kılınç-KarzanView profile

Associate Professor

• Mathematical Optimization
• Convex Optimization
• Non-convex Optimization
• +7 more

Fatma Kılınç-Karzan is an Associate Professor of Operations Research at Carnegie Mellon University's Tepper School of Business, with a courtesy appointment as Associate Professor of Computer Science. She is also affiliated with the Algorithms Combinatorics and Optimization (ACO) PhD Program and was a Visiting Scientist at Berkeley's Simons Institute for the Theory of Computing during Fall 2017. Her educational background includes a PhD from Georgia Institute of Technology's H. Milton Stewart School of Industrial & Systems Engineering with a minor in Mathematics, supervised by Prof. Arkadi Nemirovski. She earned her B.S. and M.S. degrees from the Industrial Engineering Department of Middle East Technical University with a minor in Information Systems. Dr. Kılınç-Karzan's research spans mathematical optimization with emphasis on convex and non-convex optimization theory, algorithms, and applications. Her work bridges theoretical foundations with practical implementations in optimization under uncertainty (robust optimization, chance constraints, distributionally robust optimization), machine learning (preference learning from limited data), and business analytics. She develops foundational theory for large-scale optimization problems with applications in decision making under uncertainty and high-dimensional statistical inference. Analysis of her recent publications reveals a strong focus on convex hull characterizations, semidefinite programming relaxations, distributionally robust optimization, and online convex optimization frameworks. Her work demonstrates increasing integration of optimization theory with machine learning applications, particularly in developing data-driven approaches for decision making under uncertainty. NSF CAREER Award (2015) INFORMS Optimization Society Young Researcher Prize (2015) INFORMS Junior Faculty Interest Group (JFIG) Best Paper Award (2014) BP Junior Faculty Chair (2014-2015) Faculty Giving Chair (2012-2013) Wimmer Fellowship (2012-2013) Dr. Kılınç-Karzan has successfully mentored numerous PhD students who have received prestigious awards, including the 2021 INFORMS Optimization Society Best Student Paper (1st prize) and multiple honorable mentions. Her research has been supported by significant grants including an NSF CAREER Award, an ONR grant (with S. Küçükyavuz), and an AFOSR grant. She serves on editorial boards for Mathematical Programming, Operations Research, Mathematics of Operations Research, and other leading journals, and has held leadership positions in professional societies including the Mathematical Optimization Society and INFORMS Computing Society. Through her affiliations with CMU's Tepper School, Computer Science Department, and ACO Program, she collaborates across disciplines to advance optimization theory and its applications. Her professional service includes committee chair roles for major INFORMS competitions and program committee leadership for international optimization conferences.

Jelena GrbicView profile

Professor

• Topology
• Algebra
• Combinatorics
• +6 more

Professor Jelena Grbic is a distinguished mathematician serving as Professor of Mathematics within the School of Mathematical Sciences at the University of Southampton since 2012. Her academic journey began with a B.Sc. in Mathematics from the University of Belgrade, Serbia in 1997, followed by a Ph.D. in Algebraic Topology from the University of Aberdeen in 2004. Prior to her current position, she held academic appointments at the University of Manchester (2007-2012) as Lecturer and Senior Lecturer, and at the University of Aberdeen (2004-2006) as Lecturer. Professor Grbic's research spans multiple interconnected domains of pure mathematics, with a primary focus on modern homotopy theory, particularly unstable homotopy theory, and its applications across topology, algebra, and geometry. Her work centers on decompositions and exponent problems in homotopy theory, homotopy aspects of Toric Topology, Hopf algebras, and geometric problems related to cobordisms and string topology. This research bridges abstract mathematical theory with potential applications in data science and computational topology. Analysis of her recent publications (2020-2025) reveals a consistent research trajectory in algebraic topology with increasing interdisciplinary connections. Her work demonstrates sophisticated mathematical techniques applied to complex topological structures, particularly moment-angle complexes and polyhedral products. Notably, her 2022 paper 'Aspects of topological approaches for data science' indicates growing interest in applying topological methods to contemporary data analysis problems, suggesting an expanding research horizon beyond pure mathematics. Professor Grbic actively supervises PhD students, including current student Salvatore Elia in Mathematical Sciences, and teaches modules covering algebraic topology and homotopy theory. She serves as a reviewer for prestigious journals including Homology, Homotopy and Application (2019), Transactions of the London Mathematical Society (2021), and The LMS Newsletter (2017), contributing to the scholarly community through peer review and academic service.

Mona MerlingView profile

Associate Professor

• Algebraic K-Theory
• Equivariant Stable Homotopy Theory
• Manifold Theory
• +3 more

Mona Merling is an Associate Professor in the Department of Mathematics at the University of Pennsylvania, affiliated with the School of Arts and Sciences. She holds a Ph.D. from the University of Chicago (2014) under Peter May. Prior to Penn, she was a J.J. Sylvester Assistant Professor at Johns Hopkins University. Her research focuses on algebraic K-theory, its applications to number theory and manifold theory, and equivariant stable homotopy theory. She has held research positions at institutions like the Mathematical Sciences Research Institute (MSRI) and the Max Planck Institute for Mathematics. Merling teaches advanced courses in algebraic topology, homotopy theory, and calculus, including innovative programs like the Penn Directed Reading Program and collaborations with the Prison Teaching Initiative to provide education in incarcerated settings. She organizes conferences and workshops, such as the Algebraic Topology Bridge Summer Workshop, fostering accessibility in topology education. Her research explores cutting-edge topics like scissors congruence K-theory, equivariant infinite loop space theory, and parametrized cobordism categories. Recent work includes collaborations on derived scissors congruence and multiplicative equivariant K-theory, with applications to geometric and algebraic structures. Her grants include funding for social justice initiatives in education.

John MacLaren WalshView profile

Professor

• Information Theory
• Network Coding
• Distributed Computing
• +4 more

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.

David EppsteinView profile

Professor

• Graph Algorithms
• Computational Geometry
• Graph Theory
• +3 more

David Eppstein is a Distinguished Professor of Computer Science at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information & Computer Sciences. He holds academic leadership roles as director of the Center for Algorithms and Theory of Computation and associate director of the Center for Algorithms, Combinatorics, and Optimization. His research focuses on graph algorithms, computational geometry, discrete mathematics, and geometric graph theory. Eppstein earned a B.S. in Mathematics from Stanford University (1984) and a Ph.D. in Computer Science from Columbia University (1989). Research Interests: Graph drawing, information visualization, dynamic graph algorithms, mesh generation, optimal triangulation, K-shortest paths, subgraph isomorphism, data depth, exponential-time algorithms for NP-hard problems. Awards: ACM Fellow (2012), AAAS Fellow (2017), Distinguished Professor (2020), Best Paper Awards (2023, 2022), and SIAM recognition. Grants: Co-PI on a $1.2M NSF grant (2022) for geometric graph research, and previous NSF grants for algorithm studies (2016). His work bridges theoretical computer science and practical applications, including contributions to graph visualization, geometric algorithms, and combinatorial optimization. Notable recent achievements include resolving open questions in graph biplanarity and authoring the book Forbidden Configurations in Discrete Geometry (2018).

Jose Israel RodriguezView profile

Associate Professor

• Applied Algebraic Geometry
• Algebraic Statistics
• Nonlinear Algebra
• +7 more

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

Arkadi NemirovskiView profile

Professor

• Optimization Theory and Algorithms
• Convex Optimization
• Robust Optimization
• +4 more

Arkadi Nemirovski is the John P. Hunter, Jr. Chair and Professor at the H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech. He holds a Ph.D. in Mathematics (1974) from Moscow State University, a Doctor of Sciences in Mathematics (1990) from the USSR Supreme Attestation Board, and an honorary Doctor of Mathematics from the University of Waterloo (2009). Ph.D. in Mathematics, Moscow State University (1974) Doctor of Sciences in Mathematics, USSR Supreme Attestation Board (1990) Doctor of Mathematics (Honoris Causa), University of Waterloo (2009) His research focuses on Optimization Theory and Algorithms , with emphasis on complexity analysis, efficient methods for nonlinear convex programs, robust optimization, optimization under uncertainty, and applications in engineering and nonparametric statistics. He has pioneered advancements in interior-point methods, semidefinite programming, and stochastic approximation, shaping modern convex optimization. His article trends highlight a trajectory from foundational interior-point algorithms (1990s) to robust optimization (2000s) and recent works on first-order methods, polyhedral estimates, and applications in machine learning, signal processing, and tomography. Key subfields include matrix norms , large-scale optimization , and stochastic uncertainty handling . Scientific awards include: 1982 Fulkerson Prize (joint with L. Khachiyan and D. Yudin) 1991 Dantzig Prize (joint with M. Grotschel) 2003 John von Neumann Theory Prize (joint with M. Todd) 2017 Member, National Academy of Engineering 2018 Fellow, American Academy of Arts and Sciences 2020 Norbert Wiener Prize (joint with M. Berger) He has supervised students like Dmitry Gabelev (polynomial-time cutting plane algorithms), Daureen Steinberg (matrix norms in robust optimization), and Eitan Rubinstein (SVMs via advanced optimization), with their works later formalized in academic journals.

Antonio De RosaView profile

Associate Professor

• Geometric Analysis
• Partial Differential Equations
• Geometric Measure Theory
• +3 more

Antonio De Rosa is an Associate Professor in the Department of Decision Sciences at Bocconi University, Italy. Previously, he held positions at the University of Maryland, College Park (2020–2024), and the Courant Institute of Mathematical Sciences, New York University (2017–2020). He earned his Ph.D. in Mathematics from the University of Zurich in 2017 under Camillo De Lellis and Guido De Philippis. Education: Ph.D. in Mathematics, University of Zurich (2017). His research spans Geometric Analysis , Partial Differential Equations , Calculus of Variations , Geometric Measure Theory , Optimal Transport , and Non-convex Optimization . Recent work focuses on anisotropic geometric variational problems, including existence, regularity, and uniqueness of anisotropic minimal surfaces and CMC (constant mean curvature) surfaces. He has also contributed to interdisciplinary applications in Explainable Risk Assessment and Data Analysis . The 15 most recent articles highlight advancements in anisotropic surfaces , min-max theory , optimal transport , and mathematical programming (e.g., K-means clustering, linear programming). Key trends include the intersection of geometric measure theory with nonlinear PDEs and applications in machine learning and transportation networks . Scientific Awards and Grants: 2023 Maryland Research Excellence Carlo Ciliberto Prize (2019) ERC Starting Grant ANGEVA (101076411, 2023–2028) Air Force Office of Scientific Research (AFOSR) grant (FA9550-23-1-0123) NSF CAREER Award (DMS-2143124) NSF DMS Awards (DMS-1906451, DMS-2112311) AMS Simons Travel Grant Antonio actively supervises research and teaches courses such as Optimization and Introduction to Partial Differential Equations . His work is supported by significant funding totaling approximately €3 million.

• Computational Mechanics
• Scaled Boundary Finite-Element Method
• Dynamic Soil-Structure Interaction
• +5 more

Professor Chongmin Song is a faculty member at the University of New South Wales (UNSW), affiliated with the School of Civil and Environmental Engineering. His academic rank is Professor, and he specializes in computational mechanics with a focus on innovative numerical methods. He holds a BE and ME from Tsinghua University and a DEng from the University of Tokyo. His research explores computational mechanics, fracture analysis, wave propagation, and soil-structure interactions. Key methodologies include the Scaled Boundary Finite Element Method (SBFEM), image-based modeling, and dynamic simulations of infrastructure systems. He leads significant ARC-funded projects like 'A scaled boundary framework for nonlinear dynamic analysis of structures' (DP250100955) and 'Developing sustainable graded porous cementitious structures' (LP240100123), totaling over $1M in recent grants. Recent publications emphasize adaptive modeling techniques, multiphysics simulations, and high-performance computing applications. Trends include topology optimization for structural dynamics, phase-field fracture modeling for brittle materials, and GPU-accelerated elastodynamics. His work integrates computational efficiency with real-world engineering challenges, particularly in geomechanics and material failure analysis. Professor Song collaborates extensively on projects involving computational fracture mechanics and maintains laboratories focused on numerical simulation advancements. Future work targets scalable algorithms for 3D crack propagation and multiphysics coupling in infrastructure systems.

Ioannis EmirisView profile

Professor

• Computational Geometry
• Algebraic Algorithms
• Robotics
• +4 more

Ioannis Z. Emiris is a Professor in the Department of Informatics & Telecoms at the National & Kapodistrian University of Athens and concurrently serves as President and General Director of the ATHENA Research Center in Greece. He holds a BSc in Computer Science from Princeton University (1989) and a PhD in Computer Science from UC Berkeley (1994). His research spans computational geometry, algebraic algorithms, robotics, structural bioinformatics, and optimization. He is a leading expert in sparse elimination theory, geometric modeling, and algorithmic algebra. Affiliations: ATHENA Research Center, National & Kapodistrian University of Athens, INRIA Sophia Antipolis (France via joint AROMATH team). Education: BSc (Princeton), PhD (UC Berkeley). Research Interests Emiris's work focuses on geometric algorithms, algebraic systems, and their applications. His contributions include advancements in sparse elimination theory, computational geometry for high-dimensional data, and robotics. He has developed algorithms for polynomial system solving, Voronoi diagrams, and geometric predicates for ellipses. Articles Overview His recent work bridges theoretical advances with practical applications, such as deep learning for protein structure prediction (HydraProt) and geometric algorithms for high-dimensional data analysis. He explores intersections between algebraic geometry and computational methods, with applications ranging from robotics to bioinformatics. Scientific Awards Best Paper Award at ISSAC 2003 and 2010 MSCA Network GRAPES (2019-2023) Advising & Grants Emiris has supervised numerous students and researchers, contributing to interdisciplinary projects. He has secured grants for initiatives like the GRAPES network and has led teams in algorithm design and geometric software development. His work on MARS (Maple/Matlab/C Resultant-Based Solver) exemplifies his focus on practical algorithm implementation. Labs & Teams He directs the Lab of Geometric & Algebraic Algorithms and collaborates with the AROMATH team at INRIA. His research group develops open-source tools for computational geometry and algebraic computations.

Ilaria PerugiaView profile

Professor

• Numerical methods for PDEs
• Finite element methods
• Discontinuous Galerkin methods
• +6 more

Ilaria Perugia is a University Professor (Univ.-Prof.) and Chair of Numerics of PDEs at the Department of Mathematics, Faculty of Mathematics, University of Vienna. She also serves as Deputy Head of the Research Platform Erwin Schrödinger International Institute for Mathematics and Physics. Her research focuses on numerical methods for partial differential equations with applications in computational physics and engineering. Professor Perugia's primary research interests include: Numerical methods for PDEs Finite element methods Discontinuous Galerkin methods Trefftz methods Virtual element methods Space-time methods Computational electromagnetics Wave propagation problems Nonlinear reaction-diffusion problems Her work spans theoretical analysis, algorithm development, and practical implementation of numerical methods for solving complex physical phenomena. Her recent publications demonstrate a strong focus on space-time methods, virtual element methods, and structure-preserving discretizations for wave equations, heat equations, and other PDEs. She has made significant contributions to the development of stable and efficient numerical schemes that preserve important physical properties of the underlying continuous problems, particularly in the context of wave propagation and computational electromagnetics. Professor Perugia leads a research group comprising several researchers and students including Mattia Corti, Matteo Ferrari, Monica Nonino, Andrea Scaglioni, Paul Stocker, Enrico Zampa, and Marco Zank. Her group actively collaborates on projects related to numerical analysis and scientific computing, with particular emphasis on developing novel discretization techniques for challenging PDE problems.

Dmitri PanovView profile

Professor

• Complex Geometry
• Symplectic Geometry
• Hyperbolic Geometry
• +3 more

Professor Dmitri Panov is a Professor of Geometry at King's College London, part of the Faculty of Natural, Mathematical & Engineering Sciences. He holds a PhD from École Polytechnique (2005) and has held academic positions including Royal Society Research Fellow (2010–2012), Senior Research Fellow (2012–2015), and Reader (2015–2020) at King’s College. His research focuses on complex, symplectic, and hyperbolic geometry, with a particular emphasis on polyhedral Kahler structures and definite connections. Education: Bachelor’s degree from Moscow State University (1998) PhD from École Polytechnique, France (2005) Research Interests: Panov studies geometric structures such as polyhedral Kahler manifolds and definite connections. His work bridges algebraic, differential, and symplectic geometry, with applications to moduli spaces, spherical metrics, and geometric analysis. Grants & Projects: EPSRC Grant: Kaehler manifolds of constant curvature with conical singularities (2019–2023) Royal Society Grant: Polyhedral Kahler Geometry (2017–2018) Geometric structures on manifolds (2015–2018) Events: Panov has participated in events like the Mathematics Inaugural Lecture (2023) and PhD program introductions, emphasizing his role in academic leadership and outreach.

Anton PetruninView profile

Professor

• Geometry
• Alexandrov Geometry
• Metric Geometry
• +6 more

Anton Petrunin is a Professor in the Department of Mathematics at The Pennsylvania State University, affiliated with the Eberly College of Science. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (1995). His research focuses on Geometry, particularly Alexandrov geometry, metric geometry, differential geometry, and their applications. He is known for contributions to curvature bounds, isometric embeddings, and geometric analysis. Teaching: Petrunin instructs courses such as MATH 471 (Geometry for Teachers) and actively engages in mathematical outreach, including organizing the Tournament of Towns, an international mathematics competition for school students. He emphasizes problem-solving and rigorous foundations in his pedagogy. Publications: Petrunin has authored influential books, including Alexandrov Geometry: Foundations , Pure Metric Geometry , and Euclidean Plane and Its Relatives . His work bridges theoretical advancements with accessible educational materials. Contributions: Beyond academia, he advocates for open-access research and self-publishing in mathematics. His GitHub repository reflects his commitment to sharing educational resources and collaborative projects in metric geometry and topology.

Jack SnoeyinkView profile

Professor

• Computational geometry
• Algorithms for geographical information systems (GIS)
• Structural biology
• +3 more

Jack Snoeyink is a Professor at the University of North Carolina at Chapel Hill, holding joint appointments in the Department of Computer Science (College of Arts & Sciences) and the School of Data Science and Society. His research focuses on computational geometry, with applications in molecular biology, geographic information systems (GIS), and geometric modeling. His work in computational geometry explores algorithmic design and analysis for problems in solid modeling, computer graphics, and robotics. Key application areas include terrain modeling in GIS, molecular structure validation in biochemistry, and computational topology. He has contributed to output-sensitive algorithms for convex hulls and Voronoi diagrams, and geometric search problems. Articles highlight his expertise in computational geometry, with trends spanning 1999-2000. Topics include contour tree algorithms (SODA'00), watershed extraction (ASPRS'99), and skeleton generation (Crust.pdf). His work bridges theoretical advancements with practical implementations in GIS and structural biology. Jack Snoeyink has collaborated with researchers like Marc van Kreveld, Christopher Gold, and Bettina Speckmann on projects related to Delaunay triangulation, regression depth computation, and geometric assembly problems. He previously served as a program director at the National Science Foundation's CISE division (2015-2018) and co-founded the TRIPODS program for data science foundations.