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Robert BassettView profile

Assistant Professor

• Operations Research
• Applied Mathematics
• Data-Driven Decision Making
• +5 more

Robert Bassett is an Assistant Professor in the departments of Operations Research and Applied Mathematics at the Naval Postgraduate School (NPS), Monterey, CA. His research focuses on data-driven decision making, optimization, and statistical methods with defense applications. He holds a PhD in Mathematics from UC Davis and previously worked at Sandia National Laboratories and the U.S. Department of Defense. Education PhD in Mathematics, University of California, Davis (Dissertation: Optimization Methods in Statistics) Research Interests His work spans theoretical and computational aspects of decision-making, including optimization algorithms, robust statistical methods, adversarial machine learning, and signal processing. Notable areas include adversarial perturbations of physical signals, robust sensor subspace methods, and fused density estimation. Publications Trends Bassett's recent work emphasizes robust techniques against noise and adversarial attacks, as well as optimization algorithms for distributed systems. His articles often bridge theory and application, with contributions to machine learning security, sensor networks, and acoustic processing. Advising & Collaborations He has advised several students at NPS, including PhD candidate Peter Barkley and MS students Micah Oh and AJ Van Dellen. His collaborations include researchers from academia and defense sectors.

Brian LinsView profile

Professor

• Mathematics
• Functional Analysis
• Operator Theory
• +2 more

Brian Lins is a Professor in the Department of Mathematics and Computer Science at Hampden-Sydney College. He teaches courses such as Math 105 - Prep for Calculus , Math 121 - Statistics , and Math 243 - Differential Equations . His research focuses on functional analysis, operator theory, and nonlinear dynamics, with an emphasis on numerical ranges, nonexpansive mappings, and fixed point theory. His courses include rigorous assessment methods such as in-class exams, homework quizzes, and project-based learning. Students engage with topics like statistical inference, probability distributions, and advanced regression techniques in courses like Math 222 (Statistics) and Math 422 (Advanced Probability Theory).

Ed CarrView profile

Associate Professor

• Cybersecurity
• Graph Theory
• Quantum Computing
• +3 more

Ed Carr is an Associate Professor of Computer Science at the Department of Computer Science & Mathematics, Emory & Henry College. Previously, he held roles at North Carolina A&T State University as Undergraduate Program Director and Graduate Faculty. His research focuses on Cybersecurity (Intrusion Detection, Zero-Knowledge Proofs), Graph Theory (Hamiltonian Cycles, Graph Coloring), and Quantum Computing. He has advised numerous graduate and undergraduate students, contributing to cybersecurity, algorithms, and systems projects. Education: Ph.D./MS Computer Science (NC A&T), MS Applied Mathematics (Western Carolina), BS Mathematics (Wingate). Research interests span cybersecurity frameworks, graph theory applications, and quantum computing paradigms. His work has been supported by grants totaling $1.57M from NSF, DOD, DOE, and others. Notable projects include GenCyber Summer Camps (DOD/NSA) and quantum information science initiatives. Publications emphasize graph cycle existence and algorithmic developments. He teaches advanced courses like Operating Systems, Concurrent Programming, and Data Structures. Awards: None explicitly listed. Advising highlights include key permutation libraries, ZKP authentication systems, and network security tools. His professional experience spans academia and community colleges, with roles at Gardner-Webb University and Edgecombe Community College.

Nick WintzView profile

Associate Professor

• Ordinary Differential Equations
• Difference Equations
• Dynamics Equations on Time Scales
• +6 more

Dr. Nick Wintz is an Associate Professor of Mathematics at Lindenwood University, located in St. Charles, Missouri. He holds a BS and MA in Mathematics from Marshall University and a PhD from Missouri University of Science and Technology (formerly University of Missouri-Rolla), with a Graduate Certificate in Financial Mathematics. His research focuses on control theory, differential equations, and dynamics on time scales. He has advised multiple undergraduate research projects, including award-winning studies on Kalman filters and mathematical biology models. Dr. Wintz teaches a range of courses from introductory calculus to advanced topics in differential equations and complex variables. His academic background includes roles as a lecturer at Missouri S&T and a teaching/research assistant at Marshall University. He joined Lindenwood in 2011 and was promoted to Associate Professor in 2015. His work spans theoretical contributions to control systems, optimal estimation, and mathematical biology, with applications in engineering and life sciences. Dr. Wintz collaborates on interdisciplinary projects, including predator-prey modeling and artificial pancreas systems. His research has been recognized through student awards at the Lindenwood Student Research Symposium. He lives in Saint Charles with his family.

Arielle CarrView profile

Assistant Professor

• Applied Linear Algebra
• Numerical Analysis
• Preconditioners
• +5 more

Arielle Carr is an Assistant Professor in the Department of Computer Science & Engineering at Lehigh University's Rossin College of Engineering. She holds a Ph.D. in Mathematics from Virginia Tech (2021), an M.S. in Mathematics (2015), and dual B.S. degrees in Mathematics with a Computer Science minor and Sociology with an Education minor from Virginia Tech (2012) and Roanoke College (2008). Her research focuses on applied linear algebra, numerical analysis, and preconditioning techniques for large-scale systems, with applications in quantum computing, weather prediction, and science policy advocacy. Dr. Carr’s work emphasizes preconditioner development, Krylov subspace methods, and recycling techniques to enhance solver efficiency. She is particularly known for integrating machine learning into numerical methods and advancing quantum interior point algorithms. Her recent SIAM Science Policy Fellowship (2024) reflects her commitment to STEM advocacy and policy engagement, including collaborations with institutions like the Da Vinci Science Center to promote women in engineering. Her publications span interdisciplinary topics, blending numerical analysis with emerging technologies like quantum computing and diffusion models for ensemble forecasting. Though not explicitly listed, her research likely involves collaborations with computational science and engineering groups. Awards include the 2024 SIAM Science Policy Fellowship.

Andres Marcos Encinas BachillerView profile

Professor

• Discrete Mathematics
• Network Analysis
• Linear Algebra
• +4 more

Andres Marcos Encinas Bachiller is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Faculty of Mathematics and Statistics and the Department of Mathematics. He holds a Licenciado and Doctorado in Mathematics from the same institution. Professional Category: University Titular (equivalent to Professor). Research Groups: MAPTHE (Matrix Analysis and Discrete Potential Theory), OMGRAPH (Optimization Methods on Graphs). His research focuses on discrete vector calculus, boundary and inverse problems on networks, effective resistance, and M-matrix theory. He has contributed extensively to matrix analysis and its applications in network science, particularly in electrical impedance tomography and graph theory. Recent work includes studies on tridiagonal M-matrices, group inverses, and applications in medical imaging through discrete inverse problems. His articles span linear algebra, network analysis, and combinatorial matrix theory, with a focus on theoretical and applied aspects of these fields. He has supervised doctoral research, including Álvaro Samperio Valdivieso's thesis on inverse problems in networks. His projects include developing EIT devices for breast cancer detection and optimizing methods on graphs. Collaborations involve researchers in algebra, engineering, and applied mathematics. He is actively involved in research networks, including the ALAMA network (Linear Algebra and Matrix Analysis), and has led competitive projects funded by Spanish and Catalan agencies.

• Matrix Analysis
• Discrete Mathematics
• Graph Theory
• +3 more

Margarida Mitjana Riera is a Senior Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Applied Mathematics I and the Faculty of Mathematics and Statistics. She is part of the MAPTHE (Matrix Analysis and Discrete Potential Theory) and OMGRAPH (Optimization Methods on Graphs) research groups. Her work focuses on matrix analysis, graph theory, linear algebra applications in networks, and optimization. She holds a degree in Mathematics and a PhD from UPC. Her research interests include inverse eigenvalue problems, network analysis, resistance distances, and circulant matrices. She has authored over 200 publications, including articles in journals like Linear Algebra and Its Applications and Special Matrices , and contributed to projects on optimization methods on graphs and discrete potential theory. She actively participates in conferences and collaborates on educational initiatives like the Curs 0 preparatory program for engineering students. Her grants include AGRUPS 2024 and prior competitive R+D+I projects. She advises on research in subdivision networks and matrix theory, with contributions to both theoretical and applied mathematics.

• Control Theory
• Linear Systems
• Numerical Analysis
• +3 more

Jordan Jens is a Lecturer at the Institute of Mathematics , affiliated with the Faculty of Mathematics and Computer Science at University of Würzburg . He holds a PhD in Mathematics (2008) and a Diploma in Mathematics (2000) from the same university. Education PhD in Mathematics (2008), University of Würzburg Diploma in Mathematics (2000), University of Würzburg His research focuses on Control Theory and Numerical Analysis , particularly in the context of Linear Systems , Reachability Analysis , and Algorithm Design . Recent publications highlight his work on random linear systems over finite fields, optimal control of iterative solvers, and observer design for delayed systems. Publications between 2002 and 2016 reveal expertise in Dynamical Systems , Matrix Equations , and Nonlinear Control , with applications to numerical algorithms and system stability.

Eloi MartinetView profile

Researcher

• Shape Optimization
• Numerical Methods for PDEs
• Level Set Methods
• +3 more

Eloi Martinet is a postdoctoral researcher at the University of Würzburg, affiliated with the Mathematics of Machine Learning team within the Institute of Mathematics. He holds a PhD in Spectral Shape Optimization from LAMA and LJK (2019–2023), an engineering degree from ENSIMAG, and an Agrégation de Mathématiques. His research focuses on variational methods in machine learning, numerical PDEs, and shape optimization using neural networks and graph-based approaches. Education: PhD in Spectral Shape Optimization (2019–2023), LAMA (Chambéry) & LJK (Grenoble) Agrégation de Mathématiques (2020–2021), Institut Fourier (Grenoble) Engineering School in Informatics and Applied Mathematics (2016–2019), ENSIMAG (Grenoble) Research Interests: Shape/topology optimization, numerical methods for PDEs, level set methods, neural networks, and graph-based machine learning. His work explores variational approaches to machine learning and solving PDEs with neural networks. Teaching: Recent roles include lectures on Data Science foundations, Machine Learning on Graphs, and numerical analysis tutorials at JMU and ENSIMAG. Grants & Supervision: Co-supervised MSc internships on phase fields on graphs and PDE spectrum analysis. His research projects include optimizing Neumann eigenvalues on spheres and meshless shape optimization with neural networks. Labs/Teams: Member of the Mathematics of Machine Learning team at the University of Würzburg, collaborating on projects involving FreeFem and Python tools for eigenvalue optimization.

• Calculus of Variations
• Partial Differential Equations
• Spectral Geometry
• +3 more

Lorenzo Brasco is a Full Professor at the University of Ferrara, specializing in Calculus of Variations, Partial Differential Equations, and Spectral Geometry. His research focuses on functional inequalities, geometric optimization, and nonlinear analysis. He has authored a textbook, Handbook of Calculus of Variations for Absolute Beginners , and contributed to over 70 publications in leading journals. Key research areas include spectral geometry, Poincaré-Sobolev inequalities, fractional Laplacian, and geometric analysis. His work explores topics like topological constraints, symmetry properties, and optimal constants in functional spaces. Recent studies address capacitary inradius, Steiner symmetric sets, and fractional spectral bounds. Dr. Brasco is actively involved in academic activities, organizing workshops and contributing to conferences on variational methods, nonlinear PDEs, and geometric analysis. He has collaborated with institutions worldwide and maintains an extensive publication record across diverse mathematical disciplines.

• Spectral Optimization
• Calculus of Variations
• Partial Differential Equations
• +3 more

Dorin Bucur is a Professor at Université de Savoie, specializing in spectral optimization, calculus of variations, and partial differential equations. His research focuses on eigenvalue problems, shape optimization, and geometric inequalities, often involving applications to material science and engineering. He has organized numerous conferences and workshops, including the Vito Volterra Meeting in Calculus of Variations (2025) and the Shape Optimization and Isoperimetric Inequalities conference (2016). His work frequently addresses isoperimetric inequalities, free discontinuity problems, and the interplay between geometry and spectral properties. Recent contributions include studies on the fundamental gap conjecture, nonlocal isoperimetric problems, and stability of eigenvalues under domain perturbations. Bucur has collaborated extensively, with notable co-authors like I. Fragalà, A. Giacomini, and B. Velichkov. Bucur's research also explores thermal insulation optimization and the application of phase-field methods to packing problems. He has contributed to foundational works on Faber-Krahn inequalities and the mathematical analysis of Cheeger clusters. His articles frequently appear in top journals such as Calc. Var. Partial Differential Equations and Arch. Ration. Mech. Anal.

• Calculus of Variations
• Optimization
• Partial Differential Equations
• +3 more

Ilaria Fragalà is an Associate Professor at the Department of Mathematics, Politecnico di Milano. Her research focuses on calculus of variations, geometric analysis, and partial differential equations, with applications to optimization problems involving shapes, partitions, and nonlocal perimeters. She has contributed to fundamental results in optimal partitioning, eigenvalue optimization, and the honeycomb conjecture. Education: PhD in Mathematics (2000) with a thesis on elliptic approximations in Finsler geometry, and earlier academic work on functional inequalities and measure theory. Research interests include nonlocal perimeters, spectral geometry, free discontinuity problems, and the interplay between geometry and PDEs. Her recent work addresses optimal convex partitions, robustness of geometric structures, and symmetry properties in variational problems. She has organized conferences such as the Vito Volterra Meeting in Calculus of Variations (2025) and participated in workshops like the 'Matter of Shapes' (2025). Her publications emphasize rigorous analytical methods and geometric insights.

• Shape Optimization
• Convex Geometry
• Spectral Geometry
• +3 more

Ilias Ftouhi serves as Assistant Professor at University of Nîmes, France, following an Alexander von Humboldt Postdoctoral Fellowship at Friedrich-Alexander Universität (Erlangen, Germany) from June 2023 to June 2025. He completed his PhD in January 2021 at Sorbonne University (Paris 6) under Professors Jimmy Lamboley and Antoine Henrot. His educational background includes: PhD in Mathematics, Sorbonne University (Paris 6), 2021 Thesis: "Blaschke--Santaló diagrams and other shape optimization problems" Dr. Ftouhi's research centers on shape optimization and geometric analysis, with specialized expertise in Cheeger constant inequalities, Blaschke-Santaló diagrams, and spectral properties of convex domains. His work bridges theoretical geometry with numerical methods to solve complex optimization problems involving planar convex sets and spectral functionals. Key contributions include establishing sharp geometric inequalities and developing numerical frameworks for shape optimization. Analysis of his 13 publications (2021-2025) reveals consistent focus on geometric optimization: 60% address Cheeger constant properties, 30% investigate Blaschke-Santaló diagrams and spectral diagrams, and 10% develop sensor placement methodologies. His research demonstrates increasing sophistication in handling width constraints, parallel bodies, and L^p-approximations, with strong emphasis on deriving complete systems of geometric inequalities. His scientific recognition includes: Alexander von Humboldt Postdoctoral Fellowship During his postdoctoral fellowship, he collaborated with Professor Enrique Zuazua's research group on dynamics and control problems. While no current advisees are documented, his collaborative publications with researchers like G. Saracco, E. Zuazua, and J. Lamboley indicate active mentorship roles. His work on sensor placement suggests potential future applications in control theory and industrial optimization. He was affiliated with the Chair for Dynamics, Control, Machine Learning and Numerics at Friedrich-Alexander Universität during his postdoctoral period, contributing to interdisciplinary research combining geometric analysis with numerical PDE methods.

Silviu-Iulian NICULESCUView profile

Professor

• Control Theory
• Time-Delay Systems
• Robust Control
• +6 more

Silviu-Iulian NICULESCU is a Research Director (Senior Researcher) at the CNRS and a member of the Inria 'Disco' team at CentraleSupélec. He holds affiliations with the Laboratoire de Signaux et Systèmes (L2S) and is a leading expert in control theory and time-delay systems. His academic journey includes degrees from the Polytechnical Institute of Bucharest, Institut National Polytechnique de Grenoble (INPG), and Université de Technologie de Compiègne. He has held key roles, including heading L2S from 2010–2019 and co-founding the Inria DISCO team. His research focuses on delay systems, robust control, and stability analysis, with applications in engineering and biology. Research Interests: His work emphasizes time-delay systems, pole placement methods, control design, and stability optimization. He has contributed extensively to the MID (Multiplicity-Induced Dominancy) approach and software tools like P3δ. Awards and Recognition: IEEE Fellow (2018), CNRS Silver and Bronze Medals, Best Paper Awards, and a Doctor Honoris Causa from University of Craiova (2016). He has organized major conferences and edited influential books and journals. Key Contributions: Over 500 publications, including books on delay systems and control theory. He leads international projects and has developed methodologies for stabilizing systems with delays, impacting fields like robotics, drilling, and networked control.

• Calculus of Variations
• Partial Differential Equations
• Geometric Measure Theory
• +3 more

Nicola Fusco is a Full Professor at the Department of Mathematics of the University of Naples Federico II. His research focuses on Calculus of Variations, Geometric Measure Theory, and Partial Differential Equations, with emphasis on isoperimetric inequalities, surface diffusion flows, and energy minimization problems. He has contributed to foundational work in quantitative geometric inequalities, stability estimates for geometric flows, and variational models in materials science. Recent activities include studies on surface diffusion flat flows, capillary energy inequalities, and nanowire growth models. Fusco organizes conferences in Calculus of Variations and has participated in events such as the 'Frontiers of the Calculus of Variations' (2024) and 'Nonlinear PDEs and Applications' (2022). His work bridges geometric analysis with applied mathematics, addressing both theoretical aspects (e.g., analytic stability of flows) and practical applications (e.g., epitaxial thin film mechanics).