جست‌وجوی استاد و پژوهشگر

Scott A. Craverمشاهده پروفایل

دانشیار

• Information Security
• Cryptology
• Steganography
• +۳ مورد دیگر

Scott A. Craver is an Associate Professor and Undergraduate Director in the Electrical and Computer Engineering Department at Binghamton University. His research focuses on information security, cryptology, steganography, watermarking, and security engineering. He holds a BS and MS from Northern Illinois University and a PhD from Princeton University. Craver is known for his work on ambiguity attacks in watermarking systems and contributed to the SDMI Challenge, leading to legal disputes with the RIAA. He also patented multilinearization data structures for image browsing with Intel Corporation. Education: PhD in Electrical Engineering, Princeton University BS and MS in Electrical Engineering, Northern Illinois University Research highlights include cryptographic protocols, steganographic channel design, and security analysis of public-key systems. His Erdős number is 3, connected through co-authorships in mathematical publications. Awards include the Chancellor's Award for Excellence in Faculty Service (2013-2014). Key contributions include patents on data structures for efficient image storage, and pioneering work in steganography, including the supraliminal channel concept for secure communication. His teaching focuses on cryptography and information security (e.g., EE 405 course), emphasizing hands-on assignments and programming projects.

Aida Khajaviradمشاهده پروفایل

استادیار

• Mixed Integer Nonlinear Optimization
• Nonconvex Optimization
• Algorithm Development
• +۳ مورد دیگر

Aida Khajavirad is an Assistant Professor in the Department of Industrial and Systems Engineering at Lehigh University. Her research focuses on advancing Mixed-Integer Nonlinear Optimization (MINLP) at theoretical, algorithmic, and software levels, integrating convex analysis, integer programming, and constraint programming. She has recently expanded her work to optimization algorithms for data science and machine learning applications. Education: Ph.D. in Mechanical Engineering from Carnegie Mellon University (2012). Research Interests : Mixed Integer Nonlinear Optimization Nonconvex Optimization Algorithm Development Convex Analysis Combinatorial Optimization Her work emphasizes bridging theoretical foundations with practical algorithm design for real-world challenges. Awards : 2023 INFORMS Computing Society Prize This prestigious award recognizes her contributions to optimization theory and applications. Grants & Funding : Air Force Office of Scientific Research ($1M award, 2023) This funding supports her research on advanced optimization algorithms. Labs and Affiliations: Based in the Harold S. Mohler Laboratory, she leads interdisciplinary efforts in optimization and data science.

• Partial Differential Equations
• Continuum Mechanics
• Mathematical Analysis
• +۳ مورد دیگر

Dr. Peter Lewintan is a researcher at the Faculty of Mathematics, Universität Duisburg-Essen. His work focuses on partial differential equations, Korn inequalities, elasticity theory, and mathematical analysis. He has contributed extensively to the study of continuum mechanics and applied mathematics, with a particular emphasis on foundational inequalities and their applications in material science. Research Interests: Partial Differential Equations Korn Inequalities and Functional Analysis Elasticity Theory and Nonlinear Mechanics Continuum Mechanics and Micromorphic Models Teaching and Academic Contributions: Lewintan has taught supplementary lectures for Analysis I and II courses, emphasizing rigorous mathematical foundations. His pedagogical approach includes detailed supplementary materials and live recordings for students. Key Publications: His recent work includes advancements in Korn-Maxwell-Sobolev inequalities, computational approaches to micromorphic models, and optimal inequality frameworks. These contributions highlight his expertise in both theoretical and applied mathematical research.

Longxiu Huangمشاهده پروفایل

استادیار

• Data/Signal Processing
• Applied Harmonic Analysis
• Machine Learning
• +۴ مورد دیگر

Longxiu Huang is an Assistant Professor at Michigan State University (MSU), holding dual appointments in the Department of Computational Mathematics, Science and Engineering (CMSE) and the Department of Mathematics. Prior to this, she was an Assistant Adjunct Professor at UCLA's Department of Mathematics. Her research focuses on Data/Signal Processing, Applied Harmonic Analysis, Machine Learning, Random Matrix/Tensor Analysis, Dynamical Sampling, and Optimization. Education : Ph.D. in Mathematics, Vanderbilt University (2014-2019) M.S. in Mathematics, Fudan University (2012-2014) B.S. in Mathematics, Sun Yat-Sen University (2009-2012) B.S. in Software Engineering, Sun Yat-Sen University (2008-2009) Research Interests : Huang's work bridges theoretical mathematics and applied computational methods. She explores signal reconstruction in dynamical systems, tensor decompositions for high-dimensional data, robust matrix/tensor completion, and optimization algorithms for ill-conditioned problems. Her contributions include CUR-based methods for low-rank approximations and sampling strategies for sparse signals on graphs. Professional Activities : She co-organizes the One World MINDS Seminar, a global initiative in mathematical data science. Her research has been published in top journals like SIAM Journal on Imaging Sciences and Applied and Computational Harmonic Analysis, with a focus on theoretical guarantees and practical applications in imaging and machine learning. Lab/Teams : Active collaborator in interdisciplinary projects at MSU, particularly in computational mathematics and machine learning applications.

Xiumin Duمشاهده پروفایل

استادیار

• Harmonic Analysis
• Geometric Measure Theory
• Partial Differential Equations (PDEs)
• +۳ مورد دیگر

Xiumin Du is an Assistant Professor of Mathematics at Northwestern University. His research focuses on harmonic analysis, geometric measure theory, and partial differential equations (PDEs), with a particular emphasis on Fourier restriction/extension problems, decoupling theory, and applications to geometric measure theory such as the Falconer distance set problem. He has contributed to improving bounds for fractal measures and Schrödinger maximal functions across dimensions. His work often intersects with geometric analysis, combining techniques from harmonic analysis and PDEs to address problems in fractal geometry. Notable contributions include advancements in weighted Fourier restriction estimates, refined decoupling inequalities, and solutions to multiparameter distance set problems. His research has been published in top-tier journals like the Annals of Mathematics and the Transactions of the American Mathematical Society. No specific awards or grants are explicitly mentioned in the provided text, though his extensive publication record indicates active research involvement. He advises no listed graduate students but collaborates frequently with researchers such as Yumeng Ou, Hong Wang, and Ruixiang Zhang. His office is located in Lunt Hall 220 at Northwestern University.

Süha Tunaمشاهده پروفایل

استادیار

• Machine Learning
• Bioinformatics
• Hyperspectral Imaging
• +۲ مورد دیگر

Assistant Professor Süha Tuna is affiliated with Istanbul Technical University at the Institute of Informatics in the Computational Science and Engineering department. She holds a postdoctoral degree from the University of Strathclyde and has been actively involved in academic roles since 2010.

• Quantum Computing
• Complexity Theory
• Quantum Algorithms
• +۵ مورد دیگر

Ronald de Wolf is a Senior Researcher at CWI (Dutch Centre for Mathematics and Computer Science) and a part-time Full Professor at the University of Amsterdam's Institute for Logic, Language and Computation (ILLC). He leads the Algorithms and Complexity group at CWI and is a core member of QuSoft and the Amsterdam TCS ecosystem. His academic journey includes studying computer science and philosophy at Erasmus University Rotterdam, followed by a PhD in quantum computation and communication complexity from the University of Amsterdam and CWI (2001), advised by Harry Buhrman and Paul Vitányi, and a postdoctoral fellowship at UC Berkeley. Research Focus: De Wolf's primary expertise lies in quantum computing and complexity theory, with significant contributions to quantum algorithms, communication complexity, and quantum machine learning. His work bridges theoretical computer science with practical quantum applications, exploring areas like quantum speedups for optimization problems, graph algorithms, and linear algebra. He maintains active interests in error-correcting codes, data structures, and theoretical machine learning foundations. Publication Trends: His recent research focuses on quantum advantage in optimization (graph sparsification, matrix problems), quantum communication complexity bounds, and quantum machine learning techniques. Work frequently establishes fundamental limits through lower bounds while developing novel quantum algorithms for practical computational challenges. Awards and Honors: Gödel Prize (2023) ACM STOC 10-year Test of Time Award (2022) STOC'12 Best Paper Award (2012) Cor Baayen Award (2003) ERC Consolidator Grant (2013) NWO TOP-grant (2013) Vidi Innovational Research Grant (2008) Veni Innovational Research Grant (2005) Academic Leadership: De Wolf has supervised 10+ PhD students (e.g., Yanlin Chen, András Gilyén, Srinivasan Arunachalam) and coordinates the NWO Gravitation program 'Quantum Software Consortium'. He secured significant funding including ERC and multiple NWO grants. As coordinating editor of Quantum and former editor for SIAM Journal on Computing, he shapes research dissemination. He regularly organizes major conferences (QIP, STOC, FOCS) and leads EU projects (QALGO, QAIP). Labs and Teams: He directs the Algorithms and Complexity group at CWI, collaborating extensively within QuSoft – the Dutch research center for quantum software. His team explores quantum algorithms, complexity theory, and their intersection with machine learning and optimization.

Guillaume Rabusseauمشاهده پروفایل

دانشیار

• Machine Learning
• Multilinear Algebra
• Tensor Networks
• +۴ مورد دیگر

Guillaume Rabusseau is an Associate Professor at Mila and the Department of Computer Science and Operations Research (DIRO) at Université de Montréal , holding a Canada CIFAR AI Chair since 2019. His research spans machine learning, theoretical computer science, and multilinear algebra. Education : PhD in Computer Science (2016) from Aix-Marseille Université , MSc in Fundamental Computer Science from AMU, BSc in Computer Science (distance learning) from AMU. Research Interests : Tensor methods for machine learning, spectral learning algorithms, connections between weighted automata, tensor networks, and RNNs, low-rank regression, and nonlinear computational models on structured data. Publication Trends : Recent work focuses on tensor train decomposition, temporal graph benchmarks, quantum-inspired ML, spectral regularization, and formal methods for sequence modeling. Collaborative papers address dynamic graphs, foundational models for molecular learning, and high-order pooling in GNNs. Scientific Awards : Canada CIFAR AI Chair (2019–present, renewed) Advising : Supervises PhD students like Maude Lizaire and Pascal Tikeng Notsawo, and MSc students such as Soroush Omranpour. Past advisees include Andy Huang (now at Oxford) and Tianyu Li (Samsung).

• Functional Analysis
• Geometry of Banach spaces
• Tensor products of Banach spaces
• +۳ مورد دیگر

Dr. Qingying Bu is a Professor of Mathematics at the University of Mississippi's Department of Mathematics, housed within the College of Liberal Arts. He holds a PhD from Kent State University (2002) and has been affiliated with the University of Mississippi since completing his studies. His research focuses on Functional Analysis, particularly exploring topics like Geometry of Banach spaces, Tensor products of Banach spaces, Positive tensor products of Banach lattices, and Regular multilinear operators. He has published over 84 papers cited in 312 mathematical works, with contributions to prestigious journals such as the Journal of Functional Analysis and Proceedings of the American Mathematical Society. Teaching responsibilities include courses ranging from calculus and differential equations to advanced topics in topology and algebra. His work bridges foundational mathematical theory with applications in operator theory and tensor product structures. Dr. Bu's academic journey began with a B.S. and M.S. in Mathematics from Harbin Institute of Technology (1983, 1989), followed by his doctoral studies at Kent State University. His research has consistently addressed structural properties of Banach spaces and their operators, contributing to the advancement of functional analysis methodologies.

Andrzej Okolewskiمشاهده پروفایل

دانشیار

• Financial Mathematics
• Actuarial Science
• Risk Management
• +۳ مورد دیگر

Dr. Andrzej Okolewski is an Associate Professor in the Division of Insurance and Capital Markets at Lodz University of Technology's Faculty of Technical Physics, Information Technology and Applied Mathematics. His research bridges pure mathematics and financial applications. Mathematical investigations focus on: Fractal geometry and iterated function systems Topological properties of function spaces Fixed point theorems and metric space theory Lineability and spaceability in functional analysis Applied work addresses mathematical foundations of insurance, risk assessment, and capital market modeling. Recent publications examine attractor topologies in generalized iterated function systems and structural properties of Orlicz spaces.

Kasso Okoudjouمشاهده پروفایل

استاد

• Time-frequency analysis
• Pure harmonic analysis
• Applied harmonic analysis
• +۷ مورد دیگر

Kasso Okoudjou is a Professor and Chair of the Department of Mathematics at Tufts University. His academic career spans both pure and applied mathematics with a focus on harmonic analysis and its applications. Education: PhD, Mathematics, Georgia Institute of Technology, 2003 MS, Electrical Engineering, Georgia Institute of Technology, 2003 Maîtrise es Sciences Mathematiques, National University of Benin, 1996 Professor Okoudjou's research interests lie in pure, applied and computational harmonic analysis, especially wavelet analysis, frame theory, and time-frequency analysis of pseudo-differential equations. He is also deeply interested in spectral analysis on fractals and graphs and their applications to data sciences. More recently, he has developed growing interests in mathematics education, particularly in active learning methods for lower-level math courses and broadening participation of underrepresented minorities in undergraduate research in mathematical sciences. His recent publications demonstrate a strong focus on frame theory on graphs, spectral decimation techniques, quantum walks, and time-frequency analysis. The research trends show an increasing integration of fractal analysis with graph theory and quantum information science, while maintaining strong foundations in classical harmonic analysis. Scientific Recognition: Principal Investigator for National Science Foundation grants DMS-2205771 and DMS-2309652 Co-organizer of the 2020 Gene Golub SIAM Summer School (held in 2021 at AIMS South Africa) Author of the book "Modulation Spaces: With Applications to Pseudodifferential Operators and Nonlinear Schrodinger Equations" (2020) Professor Okoudjou has advised numerous PhD students including Martin Buck, Shuang Guan, Matthew Hirn, Clare Wickman, Matt Begué, Chae Clark, Ganiou Atindéou, and Shujie Kang. He has also mentored postdocs such as Jens Christensen, Xuemei Chen, Divyang Bhimani, Gamal Mograby, and Christopher Dock. His teaching portfolio includes advanced courses like Real Analysis, Functional Analysis, and Point Set Topology. He leads two main research groups: one focused on frame theory in finite-dimensional Euclidean spaces, and another developing calculus on fractals such as the Sierpinski triangle.

Leonel Robertمشاهده پروفایل

دانشیار

• C*-algebras
• Operator Algebras
• Functional Analysis
• +۳ مورد دیگر

Leonel Robert is an Associate Professor in the Department of Mathematics at the University of Louisiana at Lafayette. His research focuses on the structure and classification of C*-algebras, the Cuntz semigroup, Hilbert C*-modules, and K-theory. He has organized conferences such as the Mini-workshop on the Cuntz semigroup (2018) and contributed to significant collaborations in operator algebras. His work integrates model theory, functional analysis, and algebraic topology to advance the understanding of noncommutative structures. Key research areas include C*-algebra classification, trace theory, and the interplay between algebraic and topological properties. His recent articles explore topics such as selfless C*-algebras, unitary groups' distinguishing properties, and nuclear dimension analysis. Dr. Robert has published extensively in top-tier journals like Duke Math. J., Advances in Mathematics, and Journal of Functional Analysis. His research bridges pure mathematics with applications in operator theory and noncommutative geometry. Office hours are held Tuesdays and Thursdays in MDD406.

Bruno Carpentieriمشاهده پروفایل

دانشیار

• Numerical Linear Algebra
• High-Performance Computing
• Computational Electromagnetics
• +۵ مورد دیگر

Bruno Carpentieri is an Associate Professor in Applied Mathematics at the Faculty of Computer Science , Free University of Bozen-Bolzano , Italy. His work focuses on Numerical Linear Algebra , High-Performance Computing , and Preconditioning Techniques for large-scale scientific problems. Education : Laurea in Applied Mathematics (1997, University of Bari Aldo Moro); PhD in Computer Science (National Polytechnic Institute Toulouse). Research Interests : Sparse linear systems, Krylov subspace methods, computational electromagnetics, PageRank problems, and fractional calculus applications in nonlinear engineering. His publications (1998–2025) emphasize efficient solvers for multi-shifted systems, parallel computing, and preconditioning strategies. Recent works (2025) explore fractional-order methods and multilayer network centrality . He has collaborated on ITER tokamak simulations (F4E/MIUR grants) and biomedical finite element models . Grants : F4E-2008-OPE-06-06-11 (ITER analysis); MIUR PRIN 2010SPS9B3. Key Contributions : VBARMS preconditioner (2014), hybrid block GMRES variants (2018), and chaos-enhanced fractional solvers (2025).

Henri Martikainenمشاهده پروفایل

دانشیار

• Harmonic Analysis
• Geometric Measure Theory
• Partial Differential Equations
• +۲ مورد دیگر

Henri Martikainen serves as Associate Professor of Mathematics at Washington University in St. Louis, specializing in harmonic analysis and geometric measure theory with significant applications to partial differential equations. His research bridges abstract operator theory with concrete geometric problems through advanced singular integral techniques. Education: PhD in Mathematics, University of Helsinki, Finland His research program investigates the deep structural connections between harmonic analysis and geometric measure theory, with particular emphasis on singular integral operators, commutators, and multi-parameter analysis. Current work explores exotic Calderón-Zygmund operators, bilinear and multilinear phenomena, and the role of dyadic-probabilistic methods in resolving long-standing problems in operator boundedness. His approach frequently employs geometric measure theory to address questions in partial differential equations through singular integral representations. Analysis of his 15 most recent publications (2020-2025) reveals consistent focus on commutator theory across multiple frameworks—bi-parameter spaces, product domains, and Banach-valued settings—with recurring themes of kernel regularity, weighted inequalities, and the interplay between analytic and geometric structures. Key contributions include foundational work on Zygmund dilations, entangled commutators, and compactness properties in multi-linear operator theory. Scientific awards: Five-year Academy of Finland Research Fellowship Dr. Martikainen's research program has been substantially supported by competitive grants, most notably his Academy of Finland fellowship which enabled extended research periods at Washington University following his tenure at the University of Helsinki. His collaborative work frequently involves international research groups focused on advancing singular integral theory and its geometric applications, though specific grant details beyond the fellowship are not disclosed in available sources.

Heinz Junekمشاهده پروفایل

استاد

• Functional Analysis
• Locally Convex Spaces
• Operator Ideals
• +۶ مورد دیگر

Heinz Junek is a Professor at the University of Potsdam , affiliated with the Institute of Mathematics . His research focuses on advanced mathematical structures in functional analysis and operator theory. Research areas include Locally Convex Spaces , Operator Ideals , and Tensor Products . He investigates topics like Multilinear Operators and Ideals , Infinite Holomorphy , and PDE with Infinitely Many Variables . His work also extends to Algebras of Unbounded Operators , with a focus on theoretical frameworks.