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Nilanjana DattaView profile

Professor

• Quantum Information Theory
• Mathematical Physics
• Quantum Channels
• +5 more

Nilanjana Datta is a Professor in Quantum Information Theory at the Department of Applied Mathematics and Theoretical Physics (DAMTP) within the University of Cambridge's Faculty of Mathematics. She transitioned to this role in 2017 after previously being part of the Statistical Laboratory. Her research focuses on foundational aspects of quantum information theory and mathematical physics, including quantum channel capacities, entropy inequalities, and the interplay between quantum information and thermodynamics. She has contributed significantly to understanding quantum entanglement, non-Markovian dynamics, and quantum hypothesis testing. Her academic career includes over 80 peer-reviewed publications in top journals such as Communications in Mathematical Physics and Physical Review Letters, alongside collaborations with leading institutions worldwide. Datta's work bridges theoretical insights with practical implications for quantum communication and cryptography. She holds a personal homepage at DAMTP and maintains active collaborations through arXiv preprints addressing cutting-edge topics like quantum Zeno effects and entropy continuity bounds. Research interests emphasize quantum resource theories, operational interpretations of quantum entropies, and the theoretical limits of information processing under quantum constraints. Her contributions to the mathematical framework of quantum information have advanced both fundamental understanding and technological applications in quantum computing and communication systems.

• Quantum Information Theory
• Quantum Many-Body Systems
• Quantum Dissipative Evolutions
• +3 more

Angela Capel Cuevas is an Assistant Professor of Quantum Information Theory/Theoretical Quantum Computation at the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge since April 2024. Previously, she held a Junior Professor (W1) position in Mathematical Methods of Quantum Theory at Universität Tübingen (2021–2024) and was a postdoctoral researcher at the Technische Universität München (2020–2021). She earned her PhD in Mathematics from Universidad Autónoma de Madrid and Instituto de Ciencias Matemáticas under a La Caixa-Severo Ochoa Fellowship. Research : Her work focuses on quantum many-body systems and quantum information theory, applying tools from analysis, geometry, and probability. Key areas include quantum dissipative evolutions, functional inequalities (e.g., logarithmic Sobolev inequalities), Gibbs states, and entropy decay. Notable contributions include studies on thermalization rates, correlation decay, and quantum Wielandt inequalities. Funding : Principal investigator in the Collaborative Research Center (CRC TRR 352) on Mathematics of Many-Body Quantum Systems (2023–2027) and the QuantERA project TouQan (2024–2027). Awards : Simons Emmy Noether Fellowship (2023), Forbes 30 Under 30 Spain (2023), Vicent Caselles RSME-FBBVA Award (2022). Advising : Supervises PhD students (e.g., Sebastian Stengele, Paul Gondolf) and postdoctoral researchers (e.g., Alberto Ruiz de Alarcón). Active in organizing workshops on quantum information and thermalization phenomena. Labs/Teams : Member of the Centre for Quantum Information and Foundations at DAMTP and the Munich Center for Quantum Science and Technology (MCQST).

Adam ShefferView profile

Associate Professor

• Computational Geometry
• Discrete Mathematics
• Incidence Geometry
• +3 more

Adam Sheffer is an Associate Professor of Mathematics at Baruch College and the Graduate Center of the City University of New York (CUNY). He is a member of Baruch's Discrete Math Group and serves as the Director of the NYC Discrete Math REU and the Baruch College Computer Science Program. His research focuses on computational geometry, discrete mathematics, and additive combinatorics, with notable contributions to incidence geometry and polynomial methods. He is the author of Polynomial Methods and Incidence Theory (Cambridge University Press) and an editor of the Journal of Computational Geometry . Sheffer's academic activities include organizing the Polymath Jr Program and the NYC Geometry Seminar. He has mentored numerous student research projects, several of which have led to published papers. Key research interests include geometric incidences, distinct distances problems, and combinatorial configurations. His work frequently bridges algebraic and geometric techniques to solve problems in discrete mathematics.

• Dynamical Systems
• Ergodic Theory
• Operator Theory
• +3 more

Demetris Hadjiloucas is an Associate Professor in the Department of Computer Science and Engineering at the European University of Cyprus (EUC). He holds a B.Sc. in Honours Mathematics (1997) and a Ph.D. in Mathematics (2001) from UMIST, U.K., with a doctoral thesis on invariant graphs in dynamical systems. His career includes postdoctoral research at UMIST, teaching roles at the University of Crete, and leadership roles at EUC, including Deputy Dean of the School of Sciences and Program Coordinator for the B.Sc. in Mathematics. Education: B.Sc. in Honours Mathematics, UMIST, U.K. (1997) Ph.D. in Mathematics, UMIST, U.K. (2001) Research Interests: Focuses on dynamical systems, ergodic theory, operator theory, and matrix dynamics. His work explores hypercyclicity, invariant graphs, and stochastic processes, with applications in functional analysis and nonlinear dynamics. Publications: His research spans over two decades, with contributions to hypercyclicity criteria, matrix dynamics, and ergodic properties. Notable themes include permutation equivalence classes, topological transitivity in operators, and non-homogeneous Markov chains. Awards: First Place Prize in the New York Mathematics League (1991) Overseas Research Scholarship (1997-2000) UMIST Graduate Research Scholarship (1998-2000) Advising & Leadership: Has coordinated academic programs, chaired selection committees, and advised on faculty hiring. His service includes roles in EUC’s Senate and departmental leadership. Research projects include studies on neural control of eye movements using dynamical systems analysis (BBSRC-funded).

• Group Theory
• Finite Group Theory
• Geometric Group Theory
• +3 more

Robert Heffernan is a Lecturer in the Department of Mathematics at Munster Technological University (MTU), located in Bishopstown, Cork, Ireland. His research focuses primarily on group theory, with early work centered on finite group theory, including commuting probability, p-groups, automorphisms, and character theory. More recently, his interests have expanded into geometric group theory. He has presented at several conferences, including the IMS September Meeting 2020 and the WIT Mathematics and Physics Seminar. His research often involves collaborative efforts with colleagues such as D. MacHale and B. McCann, exploring topics like minimal embeddings of finite groups and commutativity ratios in finite groups. Dr. Heffernan's publications span a range of journals including the Mathematical Gazette, Bulletin of the Irish Mathematical Society, and International Journal of Group Theory. His work frequently addresses theoretical problems in group structure, representation, and commutativity, with recent contributions to prime-producing polynomials and conjecture analysis in number theory. Despite his extensive publication record, no scientific awards are explicitly mentioned in the provided texts. His research trends emphasize both foundational group theory and its intersections with number theory and geometric approaches. Advising and grant activities are not detailed here, but his involvement in academic seminars and collaborative projects highlights active engagement in the mathematical community.

• Algebraic Geometry
• Mathematical Biology
• Phylogenetics
• +3 more

Jesús Fernández Sánchez is a Researcher at the Department of Mathematics, Polytechnic University of Catalonia (UPC), associated with the GEOMVAP (Geometry of Varieties and Applications) research group. He holds an affiliation with the Faculty of Mathematics and Statistics (FME) and the Institute of Mathematics of UPC-BarcelonaTech (IMTech). His work focuses on algebraic geometry, mathematical phylogenetics, and computational algebra, with applications to evolutionary biology and stochastic processes. Research Interests: Fernández Sánchez's research bridges algebraic geometry with biological applications, particularly in phylogenetics. He explores topics such as Markov matrix embeddability, phylogenetic invariants, equivariant models, and algebraic methods for evolutionary analysis. His work includes developing semi-algebraic methods for quartet reconstruction and analyzing rank conditions in phylogenetic networks. Grants & Projects: He has led or contributed to several competitive research projects, including 'GEOMETRIA DE VARIETATS I APLICACIONS' (GEOMVAP group), the María de Maeztu Excellence Program, and collaborations on phylogenetic model development. His projects emphasize multidisciplinary approaches in geometry, algebra, and topology. Advising: He has supervised doctoral students like Marina Garrote-López and Jordi Roca-Lacostena in topics such as phylogenetic reconstruction methods and Markov matrix analysis. His lab investigates geometric and algebraic tools for evolutionary biology, with a focus on model validation and computational techniques. Affiliations: Besides his primary role at UPC, he collaborates with international research networks in algebraic phylogenetics and stochastic processes. His work integrates pure mathematics with applied problems in biology and statistics.

• Operator Algebras
• Random Matrices
• Privacy-Preserving Data Synthesis
• +4 more

March Boedihardjo is an Assistant Professor in the Department of Mathematics at Michigan State University (MSU). His academic journey includes postdoctoral roles at ETH Zurich (2022-2023), the University of California, Irvine (2021-2022), and UCLA (2016-2021). He earned his Ph.D. in Mathematics from Texas A&M University (2012-2016) under advisors Bill Johnson and David Kerr, and holds a B.Sc./M.Phil. from Hong Kong Baptist University (2007-2011). Boedihardjo's research focuses on operator algebras, random matrices, and privacy-preserving data synthesis. His work bridges functional analysis and modern data science, with contributions to covariance loss minimization, max-sliced Wasserstein distances, and privacy-utility tradeoffs in synthetic data. He has presented at venues like Carnegie Mellon's Probability/Math Finance Seminar and the International Conference on Machine Learning (ICML). His teaching includes advanced courses like MTH 890: Readings in Mathematics. His research outputs span foundational mathematics (e.g., C*-algebra representations on ℓp spaces) and applied topics (e.g., differentially private synthetic data generation). While no specific awards are listed, his active conference participation reflects scholarly engagement in operator theory, probability, and data science intersections.

Brent NelsonView profile

Associate Professor

• Free Probability
• Operator Algebras
• Von Neumann Algebras
• +3 more

Brent Nelson is an Associate Professor in the Department of Mathematics at Michigan State University (MSU). He holds a PhD in Mathematics from the University of California, Los Angeles (UCLA), under the supervision of Dimitri Shlyakhtenko, and a BS in Mathematics from the University of Illinois at Urbana-Champaign (UIUC). His research focuses on free probability, non-tracial von Neumann algebras, free transport, subfactor planar algebras, and bi-free probability. He has held postdoctoral positions at Vanderbilt University and the University of California, Berkeley, and has been recognized with awards including the Pacific Journal of Mathematics Dissertation Prize (2015) and the Distinguished Teaching Award (2018). Key research interests include the structure of von Neumann algebras, free monotone transport, and applications to quantum graphs and operator algebras. He has authored numerous publications in top-tier journals and presented at international conferences such as the Canadian Operator Symposium and the Banff International Research Station workshops. His teaching includes advanced courses on functional analysis, operator algebras, and real/complex analysis at MSU and other institutions. Grants include NSF funding for projects on non-tracial derivations and distributions, and he has organized conferences like the Groundwork for Operator Algebras Lecture Series (2020). His work bridges abstract operator algebra theory with applications in quantum probability and ergodic theory.

• Functional Analysis
• Probability Theory
• Harmonic Analysis
• +4 more

Gilles Pisier is the A.G. and M.E. Owen Chair and Distinguished Professor in the Department of Mathematics at Texas A&M University, affiliated with the College of Arts & Sciences. His research focuses on functional analysis, probability theory, harmonic analysis, and operator theory, with significant contributions to C*-algebras and operator spaces. Education: Ph.D. in Mathematics, Université Paris VII (1977) DEA de Mathématiques Pures, Université Pierre et Marie Curie (Paris VI, 1972) École Polytechnique (1969–1972) Research Interests: Pisier’s work bridges functional analysis with probability and operator algebras. He has pioneered studies on operator spaces, non-commutative L p spaces, and the Grothendieck inequality. His research often intersects quantum probability and applications to quantum information theory. Recent work includes investigations into the lifting properties of C*-algebras and the weak expectation property (WEP). Publications: His articles explore topics such as von Neumann algebra injectivity, tensor products of operator spaces, and Sidon sets in harmonic analysis. These contributions highlight his expertise in abstract operator theory and its applications. Academic Service: He has served on editorial boards for prestigious journals and institutions, including the Académie des Sciences. His textbook Introduction to Operator Space Theory (2003) remains a foundational resource in the field. Future Work: Current projects include advancing the Connes-Kirchberg conjecture and exploring metric entropy in Banach-Mazur compacta.

• Operator Algebras
• Free Probability Theory
• Functional Analysis
• +3 more

Ken Dykema is a Professor of Mathematics at Texas A&M University's College of Arts & Sciences. He holds a Ph.D. from the University of California, Berkeley (1993), a B.A. from Oxford University (1987), and a B.S. from the University of Wisconsin, Eau Claire (1985). His research focuses on operator algebras, free probability theory, and their applications to non-commutative geometry and quantum information theory. Key research interests include von Neumann algebras, R-diagonal elements, spectral theory, and quantum correlations. Notable contributions involve the study of DT-operators, algebra-valued free probability, and the structure of free product algebras. His work frequently intersects with functional analysis, linear algebra, and graph theory. Publications span topics like operator decompositions, spectral properties, and Horn inequalities, reflecting his deep engagement with abstract algebraic structures and their analytical implications. While no specific awards are listed, his extensive publication record highlights sustained academic impact. Advising and grants are not explicitly detailed in the provided text, though his research activity suggests involvement in graduate mentorship and collaborative projects. No lab or team affiliations are mentioned.

Solesne BourguinView profile

Associate Professor

• Stochastic Analysis
• Fractional Brownian Motion
• Malliavin Calculus
• +6 more

Solesne Bourguin is an Associate Professor in the Department of Mathematics and Statistics at Boston University. She is a member of the Probability and Statistics research group. Her research focuses on advanced topics in stochastic analysis, including stochastic dynamical systems, fractional Brownian motion, Malliavin calculus, Stein's method, and free probability theory. She teaches graduate and undergraduate courses such as Probability Theory II and Linear Algebra. Her research interests emphasize the theoretical foundations of stochastic processes, with applications to nonlinear statistics and random matrices. Recent work explores quantitative analysis of stochastic iterative algorithms and Gaussian approximations in high-dimensional settings. She has contributed to understanding fluctuation dynamics in multiscale systems driven by fractional Brownian motion and has published in leading journals like the Electronic Journal of Probability and Stochastic Processes and their Applications. Bourguin's recent publications highlight her expertise in topics like functional Gaussian approximations, moderate deviation principles, and spherical Poisson waves. These studies often combine techniques from Malliavin calculus and Stein's method to derive precise probabilistic estimates. She also investigates the limiting behavior of correlated Wishart matrices in high-dimensional regimes, contributing to random matrix theory. Scientific awards and grants are not explicitly listed in the provided information. She actively participates in academic activities, including organizing Boston University's Statistics and Probability Seminar Series. Her teaching reflects her commitment to both foundational and advanced mathematical education, spanning topics from linear algebra to stochastic processes.

• Functional Analysis
• Operator Theory
• Banach Space Geometry
• +2 more

Otte Heinävaara is a Scott Russell Johnson Postdoctoral Scholar Teaching Fellow in Mathematics at the California Institute of Technology (Caltech). He is affiliated with the Division of Physics, Mathematics and Astronomy, specializing in functional analysis and operator theory. His research focuses on matrix inequalities, Banach space geometry, and tracial spectral measures. He holds an M.Sc. in Mathematics from the University of Helsinki (2018), where his thesis under Eero Saksman explored matrix monotone functions. His current work investigates tracial joint spectral measures, a theory he discovered, with applications in non-commutative geometry. Research interests include exploring how matrix inequalities reveal geometric properties of Banach spaces. Recent work involves Schatten-3 class analysis, probabilistic geometry on spheres, and operator algebra techniques. Collaborations include studies with D. Bilyk, A. Chang, R. W. Matzke, and S. Steinerberger. No academic awards are listed, but his preprints and publications reflect active engagement in high-dimensional analysis and spectral theory.

• Theoretical Computer Science
• Complexity Theory
• Operator Scaling
• +2 more

Leonid Gurvits is a Professor in the Computer Science department at City College of New York. His research spans theoretical computer science, complexity theory, operator scaling, and quantum computing. Gurvits develops mathematical frameworks and algorithms addressing fundamental problems in combinatorics, optimization, and quantum information. Recent publications demonstrate Gurvits' focus on: Advanced operator scaling techniques and applications Quantum particle statistics and entanglement complexity Combinatorial optimization through matrix analysis Efficient algorithms for permanents and partition functions

Vladimir ShpilrainView profile

Professor

• Post-Quantum Cryptography
• Computational Complexity
• Group Theory
• +4 more

Vladimir Shpilrain is a Professor in the Department of Mathematics at The City College of New York (CUNY). His primary research focuses on post-quantum cryptography, computational complexity, and algorithmic problems in group theory. He is a leading figure in applying algebraic methods to cryptographic protocols and has contributed to foundational work in non-commutative cryptography. His academic affiliations include the Algebraic Cryptography Center and collaborative projects at the intersection of mathematics and computer science. Shpilrain has authored over 100 publications, including two influential books on combinatorial and computational group theory. His work bridges pure mathematics (e.g., combinatorial group theory, affine algebraic geometry) with applied areas like secure communication and blockchain technology. He holds patents for cryptographic systems and has advised numerous students in interdisciplinary research areas. Shpilrain teaches advanced courses in linear algebra, probability theory, and cryptography. His research is supported by grants exploring post-quantum security, Cayley hash functions, and delegation protocols. Collaborations span global institutions, emphasizing both theoretical rigor and practical applications in information security.

Abraham WesterbaanView profile

Lecturer

• Category Theory
• Von Neumann Algebras
• Operator Algebras
• +4 more

Dr. Abraham Westerbaan is a Lecturer at Radboud University's ICIS (Digital Security Department) and a Scientific Programmer at Radboud's iHub. He earned his Ph.D. in 2019 under the supervision of Bart Jacobs, defending a thesis titled *The Category of Von Neumann Algebras*, which explores foundational aspects of operator algebras and category theory. His research spans quantum computing, mathematical logic, and cryptographic systems, with notable contributions to quantum programming languages and mathematical structures in theoretical physics. Westerbaan's work integrates advanced algebraic concepts with computational security, reflecting his dual role in academic research and applied scientific programming. His publications emphasize categorical frameworks for quantum mechanics, operational quantum logic, and cryptographic protocols for network privacy. He maintains an active GitHub repository documenting his thesis and related projects, showcasing collaborations in operator algebra theory and computational mathematics. While no specific grants or awards are explicitly listed, his extensive publication record and academic roles indicate sustained engagement with cutting-edge research in theoretical computer science and mathematical physics. His affiliations with ICIS and the iHub highlight a commitment to both foundational inquiry and applied technological development.