Find Academic Supervisors

Stephen KirklandView profile

Professor

• Matrix Theory
• Combinatorial Mathematics
• Spectral Graph Theory
• +1 more

Stephen Kirkland is Professor of Mathematics and Associate Dean in the Faculty of Graduate Studies at the University of Manitoba. His research focuses on matrix theory, combinatorial mathematics, and spectral graph theory with applications to Markov chains and network science. Current investigations include Kemeny's constant analysis, quantum state transfer in graphs, and spectral properties of stochastic matrices. His work connects abstract matrix theory with practical applications in epidemiology, network analysis, and quantum computing. Kirkland serves as Editor-in-Chief of Linear and Multilinear Algebra and Senior Editor of Linear Algebra and its Applications. He previously served as President of the International Linear Algebra Society and on scientific advisory boards internationally. He currently supervises graduate students Hermie Monterde, Homer Franz De Vera, Aaron Rossi, and Max Wiebe. His research group investigates mathematical structures underlying complex systems and networks.

Murat SARDUVANView profile

Associate Professor

• Matrix Theory
• Linear Algebra
• Numerical Analysis
• +3 more

Murat SARDUVAN is an Associate Professor in the Department of Mathematics at Sakarya University . His research focuses on matrix theory, linear and multilinear algebra, numerical analysis, and applied mathematics, with particular interest in special matrix types (tripotent, idempotent, involutive) and their linear combinations. Research spans matrix equations, spectral theory, nonsingularity conditions, and nearness problems Published in journals like Journal of Numerical Mathematics , Linear & Multilinear Algebra , and Acta Universitatis Apulensis Supervised 6 graduate theses on matrix combinations and partial orders Awarded Teşekkür Belgesi and Takdir Belgesi for academic contributions

Ehrhard BehrendsView profile

Professor

• Functional Analysis
• Probability Theory
• Stochastic Processes
• +4 more

Prof. Ehrhard Behrends is a Professor of Mathematics at the Department of Mathematics and Computer Science, Freie Universität Berlin. His research focuses on functional analysis, probability theory, and stochastic processes. He is also deeply involved in mathematical education and public outreach, having authored numerous popular mathematics books and articles. Key roles include leading the European Mathematical Society's Raising Public Awareness committee (2009–2015) and developing the mathematics portal mathematics-in-europe.eu . Behrends has organized major exhibitions like 'Mathematics for all the Senses' and contributed to initiatives such as the Year of Mathematics 2008. His work bridges advanced research with accessible communication, reflected in his books on Markov chains, analysis textbooks, and the Five Minutes of Mathematics column.

• Discrete Optimization
• Non-Convex Optimization
• Operational Research
• +3 more

Akshay Gupte is a Professor in the School of Mathematics at the University of Edinburgh, specializing in Optimization and Operational Research. His research focuses on mathematical and algorithmic aspects of discrete and non-convex optimization, with applications in engineering, finance, and decision-making systems. He holds a PhD in Operational Research from Georgia Tech and teaches advanced courses such as Optimization Methods in Finance for MSc students. Education: BEng in Industrial Engineering from the University of Bombay MSc in Operational Research from the University of Arizona PhD in Operational Research from Georgia Tech Research Interests: Optimization problems involving discrete choices and non-convexity, with a focus on algorithm design and computational strategies. His work bridges applied mathematics, computer science, and engineering, addressing challenges in logistics, finance, and large-scale decision systems. Articles Trends: Recent publications emphasize algorithmic advancements in non-convex optimization (e.g., spatial branch-and-bound, semidefinite programming), multi-objective decision-making (e.g., biobjective programming), and stochastic frameworks for real-world problems like facility location and home service scheduling. Awards & Grants: No specific awards listed, but his research has been supported by collaborative grants in mixed-integer programming and optimization algorithms. He advises students through his teaching and research collaborations within the Optimization Group at the University of Edinburgh.

Seungly OhView profile

Associate Professor

• Partial Differential Equations
• Nonlinear dispersive partial differential equations
• Surface water waves
• +7 more

Seungly Oh is an Associate Professor of Mathematics in the Department of Mathematical Sciences at Western New England University. Their research focuses on nonlinear dispersive partial differential equations and harmonic analysis with applications in surface water waves, optics, and quantum physics. Education: Ph.D. in Mathematics, University of Kansas Research Interests: Nonlinear dispersive equations (Benjamin-Ono, Korteweg-de Vries, Boussinesq) Harmonic analysis and multilinear operators Functional spaces (Sobolev spaces, L^p embeddings) Applications in mathematical physics Recent Article Trends: Recent work addresses nonlinear smoothing properties, well-posedness in low regularity settings, and endpoint estimates for inequalities in harmonic analysis.

Joakim ArnlindView profile

Professor

• Non-commutative Geometry
• Algebraic Geometry
• Riemannian Geometry
• +5 more

Joakim Arnlind is a Professor and Head of the Department of Mathematics at Linköping University, Faculty of Science and Engineering. He is affiliated with the division of Algebra, Geometry and Discrete Mathematics (ALGD), where he leads research in non-commutative and algebraic geometry. Research Interests: His work centers on algebraic aspects of geometry, particularly non-commutative Riemannian geometry, Poisson algebras, and the geometric interpretation of operator-valued functions. He investigates how classical geometric concepts can be generalized to noncommutative algebras, with applications in mathematical physics and quantum geometry. Publication Trends: His recent publications (2020–2024) focus on Levi-Civita connections in noncommutative settings, quantum spheres, Kronecker algebras, and fuzzy spaces. The research emphasizes derivation-based calculi, metric compatibility, and the construction of geometric structures on noncommutative manifolds, reflecting a deep engagement with both algebraic and differential frameworks. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: Joakim Arnlind is the main supervisor for PhD students Axel Tiger Norkvist and Kwalombota Ilwale. He leads the Noncommutative Riemannian Geometry research group and is involved in organizing academic workshops, such as the Workshop in Algebra and Noncommutative Geometry. While specific grants are not listed, his sustained publication output and leadership roles indicate active research funding and mentorship. Labs and Teams: He leads the research group focused on Noncommutative Riemannian Geometry, exploring metric aspects such as connections and curvature using twisted derivation-based calculi. He is also part of the broader ALGD division, which includes researchers in algebra, geometry, combinatorics, and topology.

• Functional Analysis
• Operator Theory
• Several Complex Variables
• +7 more

Francisco Javier Falco Benavent is an Associate Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, University of Valencia, Spain. His research is centered on functional analysis, operator theory, and several complex variables. He is a member of the research group ESALDI (Spaces and Algebras of Differentiable Functions), focusing on holomorphic functions and norm-attaining operators. His research interests include: Functional Analysis and Operator Theory Norm-attaining operators and multilinear maps Several complex variables and holomorphic functions Polynomial convexity and invariant polynomials Hypercyclicity and linear dynamics Approximation theory in complex analysis The trends in his recent publications reflect a deep engagement with the interplay between algebraic structures and analytic properties in infinite-dimensional spaces. His work often explores separation theorems, Bishop-Phelps-type properties, and algebrability in function spaces, with a strong emphasis on group-invariant structures and boundary behavior in complex domains. He has collaborated extensively with leading mathematicians such as Manuel Maestre, Domingo García, Richard Aron, and Paul Gauthier. While no scientific awards are explicitly mentioned, his consistent publication record in high-quality journals like Advances in Mathematics , Journal of Mathematical Analysis and Applications , and Studia Mathematica underscores his active and impactful research presence. He completed his PhD in 2014 at the University of Valencia under the supervision of Dr. Domingo García Rodríguez, Dr. Manuel Maestre Vera, and Dr. Pilar Rueda. There is no indication of part-time status, retirement, or former staff status—he appears to be an active, full-time faculty member.

• Operator Theory
• Functional Analysis
• Mathematical Analysis
• +4 more

Dr. Josep Martinez Centelles is an Associate Professor at the Faculty of Mathematics , University of Valencia , specializing in Mathematical Analysis . His research spans operator theory, differential equations, and their applications to physics and engineering. PhD in Mathematics (1992) from University of Valencia Key research collaborations with experts in relativity, optimization, and harmonic analysis Research focuses on: Operator theory and semigroups in Banach spaces Harmonic analysis for time-frequency localization Relativistic thermodynamics and gravitational collapse modeling Computational methods in fluid dynamics and multi-objective optimization Recent work explores generalized ε-quasi solutions in set optimization (2022), enhanced LES discretization techniques (2015), and uncertainty principles in spherical mean transforms (2014). His publications appear in journals like zbMATH, Journal of Mathematical Analysis and Applications, and Computational Optimization and Applications.

• Game Theory
• Operational Research
• Cooperative Games
• +7 more

Dr. Balbina Casas Mendez is a Professor in the Department of Statistics, Mathematical Analysis and Optimization at the University of Santiago de Compostela (USC) , affiliated with the Galician Mathematical Research and Technology Center (CITMAga) and the MODESTYA research group focused on optimization, decision-making, and statistical models. She holds a doctorate from USC (1996) for her thesis on cooperative games with graph-restricted communication, advised by Dr. José Manuel Prada Sánchez. Her research lies at the intersection of Game Theory , Operational Research , and Mathematical Economics , with emphasis on cooperative games, power indices, bankruptcy rules, and multi-issue allocation problems. Her work applies these concepts to real-world scenarios like food distribution logistics, European Union decision-making, and healthcare data analysis. Recent publications highlight her expertise in: Algorithmic methods for power indices in coalition-structured games Heuristic solutions for logistics and agricultural planning Statistical approaches to feature influence in classification problems Axiomatic characterizations of game theory solutions She has co-authored over 31 works since 2000, with significant contributions to journals like the European Journal of Operational Research and International Journal of Game Theory .

• Game Theory
• Operational Research
• Cooperative Games
• +3 more

Jose Maria Alonso Meijide is a Professor at the Department of Statistics, Mathematical Analysis and Optimization within the Faculty of Veterinary Medicine at the University of Santiago de Compostela. He is affiliated with the Galician Mathematical Research and Technology Center (CITMAga) and leads the MODESTYA research group focused on Optimization, Decision, and Statistical Models. PhD in Cooperative Games (2002) from University of Santiago de Compostela Research areas: Game Theory, Operational Research, Cooperative Game Theory Key collaborators: Gloria Fiestras Janeiro, Ignacio Garcia Jurado, Balbina Casas-Mendez Research Focus spans cooperative games with exogenous conditions, power indices (Banzhaf, Shapley), and coalition structures. His work appears in journals like Annals of Operations Research and European Journal of Operational Research , emphasizing axiomatic characterizations and computational methods. Publications show expertise in power measurement (Banzhaf-Coleman, Shapley-Shubik), egalitarian values, and applications to the IMF and European Union. His 2025 article Necessary players and values extends axiomatic frameworks for cooperative scenarios.

• Theoretical Computer Science
• Algorithms
• Computational Complexity
• +4 more

Nutan Limaye is a Professor at the Department of Theoretical Computer Science , IT University of Copenhagen , specializing in Algorithms , Computational Complexity , and Algebraic Circuits . She actively contributes to research on polynomial complexity, quantum computation, and lower bound techniques. Key Research Areas : Algebraic Circuit Complexity, Polynomial Computation, Graph Isomorphism, Boolean Satisfiability Current Projects : FLows : Formula complexity and lower bounds (2024-2026) DIREC: OnlineAlgo : Digital research initiatives (2022-2025) BARC2 : Basic Algorithms Research Copenhagen (2024-2029) Scientific Recognition includes the FOCS Best Paper Award (2022) . Her work frequently appears in top conferences like CCC , FSTTCS , and SIGACT News , with recent collaborations in Denmark and international institutions. She contributes to public understanding through media appearances on topics like basic computer science research and BARC's initiatives .

• Mathematics
• Differential Equ
• Linear and Multilinear Algebra: Matrix Theory
• +6 more

Assoc. Prof. Serap Kemali is an Assistant Professor at Akdeniz University's Technical Sciences Vocational School, Department of Architecture and City Planning. Her research focuses on mathematical analysis, particularly in convex functions, differential equations, and optimization. Her primary research areas include Mathematics Differential Equations Convex and Discrete Geometry Optimization Kemali has published extensively on convexity-related inequalities, including works on s-convex functions, Hermite-Hadamard type inequalities, and fractional calculus applications. Her research explores abstract convexity, B-convexity, and its generalizations, contributing to theoretical and applied mathematical analysis. Recent publications demonstrate expertise in Caputo fractional derivatives Integral inequalities Convexity refinements Curriculum development in mathematics education Kemali has advised 1 thesis and participated in funded projects like "B-Convexity and B^(-1) Convexity Comparisons" (2015-2018) "Mathematics in Our Life: Agriculture" (2015-2017)

• Machine Learning
• Deep Learning
• Robustness in Neural Networks
• +2 more

Dr. Grigorios Chrysos is a faculty member in the Department of Electrical & Computer Engineering at the University of Wisconsin-Madison. His research focuses on reliable machine learning, emphasizing robustness to noise, out-of-distribution generalization, and theoretical understanding of neural/polynomial networks. Education: PhD in Machine Learning, Imperial College London (2020) M.Eng. in Electrical Engineering, National Technical University of Athens (2014) Key research interests include robustness in deep networks , inductive bias analysis , and polynomial network design for high-order input interactions. His work explores adversarial robustness, fair model generalization, and extrapolation properties in generative frameworks. Recent awards include the prestigious DAAD AInet Fellowship (2023), Best Reviewer Awards at NeurIPS (2022), ICLR (2022), and IMCL (2021), alongside Amazon Cloud Credits and Nvidia GPU donations (2019). Scientific Contributions: Advancing tensor methods in machine learning Developing polynomial networks for robustness Designing efficient EEG seizure analysis algorithms