جستجوی استاد راهنمای دانشگاهی

• Quantum Information Theory
• Quantum Many-Body Systems
• Quantum Dissipative Evolutions
• +۲ مورد دیگر

Angela Capel Cuevas is an Assistant Professor of Quantum Information Theory/Theoretical Quantum Computation at the University of Cambridge's Department of Applied Mathematics and Theoretical Physics (DAMTP). Previously, she held a Junior Professorship at Eberhard Karls Universität Tübingen (2021-2024) and was an MCQST Distinguished PostDoc at TU München (2020-2021). Her research focuses on the intersection of quantum information theory and quantum many-body systems, particularly studying thermalization dynamics via quantum functional inequalities. She is a recipient of the Simons Emmy Noether Fellowship and Forbes 30 Under 30 (Spain 2023). Education: PhD in Mathematics, Universidad Autónoma de Madrid/ICMAT (2015-2019) Master in Computational Engineering and Mathematics, URV/UOC (2016-2018) Bachelor in Mathematics, Universidad de Granada (2009-2014) Research: Angela's work applies analytic and geometric tools to quantum systems, emphasizing decay of correlations in Gibbs states and quantum dissipative evolutions. Key topics include entropy inequalities, modified logarithmic Sobolev inequalities, and thermalization rates in spin chains. Her recent work bridges quantum functional analysis with practical implications for quantum computing and thermalization phenomena. Grants & Roles: PI of CRC TRR 352 'Mathematics of Many-Body Quantum Systems' (7M€) Co-PI of QuantERA project TouQan (1.25M€) Organized workshops at BIRS and Tübingen (2023-2024) Awards: Simons Emmy Noether Fellowship (2023) Forbes 30 Under 30 (2023) Vicent Caselles RSME-FBBVA Award (2022) Labs/Teams: Leads a group studying quantum dissipative systems and thermalization at DAMTP. Collaborates with institutions globally on quantum functional inequalities and Gibbs state properties.

Andrew Childsمشاهده پروفایل

استاد

• Quantum Algorithms
• Quantum Information Processing
• Quantum Simulation
• +۲ مورد دیگر

Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.

• Algebraic Geometry
• Mathematical Physics
• Mirror Symmetry
• +۷ مورد دیگر

Maxim Kontsevich has been a permanent professor at the Institut des Hautes Études Scientifiques (IHÉS) since 1995, holding the AXA-IHES Chair for Mathematics . He is also Professor at Rutgers University (one month per year since 1997) and was Professor at University of California, Berkeley (1993–1995). Born 25 August 1964 in Khimki, former USSR, he became a French citizen in 1999. Education: Ph.D. in Mathematics, University of Bonn, March 1992. Research Interests: Prof. Kontsevich’s work lies at the intersection of algebraic geometry , mathematical physics , and quantum theory . He introduced revolutionary ideas in mirror symmetry , non-commutative geometry , and deformation quantization , creating new algebraic structures that have found applications far beyond their original contexts. His current ERC Synergy Grant “ReNew Quantum” (2019-2025) explores recursive and exact new quantum theory . Publications & Trends: Across more than 50 influential papers, Kontsevich has consistently pushed the boundaries of enumerative geometry , motivic integration , and topological field theory . His recent work delves into symplectic aspects of homological algebra , motivic Donaldson-Thomas invariants , non-archimedean geometry , and integrable systems , revealing deep connections between geometry, algebra, and physics. Scientific Awards & Honors: Fields Medal (1998) Crafoord Prize (2008) Shaw Prize in Mathematical Sciences (2012) Breakthrough Prize in Fundamental Physics (2012) Breakthrough Prize in Mathematics (2014) ERC Synergy Grant “ReNew Quantum” (2019) AMS Moore Prize (2025) Doctor Honoris Causa: Aarhus University (2014), Universität Wien (2015), Syddansk Universitet (2023) Member of Académie des Sciences, Institut de France, Academia Europaea, National Academy of Sciences (foreign), London Mathematical Society (honorary) Grants & Leadership: As Principal Investigator of the ERC Synergy Grant “ReNew Quantum” (€10 million, 2019-2025), Kontsevich coordinates an international team advancing exact methods and resurgence in quantum field and string theories. Editorial Service & Community Roles: He serves on the editorial boards of Compositio Mathematica , Publications Mathématiques IHÉS , Journal of Noncommutative Geometry , and several other leading journals, shaping the direction of contemporary mathematical research.

Afonso S. Bandeiraمشاهده پروفایل

استاد

• High Dimensional Probability
• Random Matrices
• Mathematical Statistics
• +۳ مورد دیگر

Afonso S. Bandeira is a Professor in the Department of Mathematics (D-MATH) at ETH Zurich, where he conducts research at the intersection of mathematics, statistics, and computer science. He maintains strong affiliations with several interdisciplinary research centers including the Institute For Operations Research (IFOR), the Max Planck ETH Center for Learning Systems, the ETH Foundations of Data Science, and the ETH AI Center, with a courtesy appointment at D-ITET. Bandeira actively teaches courses including Mathematics of Signals, Networks, and Learning, and Mathematics of Data Science. His research focuses on High Dimensional Probability, Random Matrices, Mathematical Statistics, Theoretical Computer Science, Combinatorics, and Mathematical Optimization. Bandeira's work often explores the theoretical foundations of data science, examining phase transitions in statistical problems, computational barriers, and the geometry of high-dimensional spaces. He maintains a research group blog called Randomstrasse101 that emphasizes open problems in his field. Analysis of his recent publications reveals a strong focus on matrix and tensor concentration inequalities, synchronization problems, nonconvex optimization landscapes, and computational-statistical tradeoffs in high-dimensional inference. His work bridges theoretical mathematics with practical applications in machine learning and data analysis, particularly examining where computational limitations arise in statistical problems. Bandeira actively mentors students and researchers, currently supervising several doctoral candidates including Daniil Dmitriev, Konstantin Donhauser, Anastasia Kireeva, Kevin Lucca, Chiara Meroni, Gil Kur, Petar Nizic-Nikolac, and Almut Roedder. He emphasizes that students working with him should participate in the DACO seminar and group meetings, and encourages prospective students to have completed his Mathematics of Signals, Networks, and Learning or Mathematics of Data Science courses. He leads a research group focused on the mathematics of data science, with regular group meetings and seminars. Bandeira has developed comprehensive lecture notes including 'A Tour Through the Mathematics of Signals, Learning, and Networks' (2025) and 'Mathematics of Machine Learning' (2021), and previously authored 'Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science' (2015).

Valter Morettiمشاهده پروفایل

استاد

• Algebraic Quantum Field Theory
• Black Holes
• Functional Analysis
• +۱۰ مورد دیگر

Valter Moretti is a Full Professor in the Department of Mathematics at the University of Trento. His academic career spans roles from Research Fellow to Full Professor, focusing on Mathematical Physics and Quantum Field Theory (QFT) in curved spacetime. He earned an MSc in Physics from Genova University and a PhD in Theoretical Physics from Trento University. Research Interests : Algebraic QFT, General Relativity, Quantum Mechanics, Operator Algebras, and Spectral Theory. His work bridges mathematical rigor with physical applications, particularly in quantum localization, entanglement, and curved spacetime phenomena. Publications : Authored 15+ recent papers on topics like quantum particle localization, entanglement certification, and QFT on curved backgrounds. Collaborated on a 2022 patent for generating entangled photon states. Awards : Holds a patent for a quantum-certified random number generator (2022). Supervision : Advised 8 PhD students, including N. Pinamonti, L. Franceschini, and C. van de Ven. Coordinated national and international research projects (e.g., H2020-MSCA-COFUND-2015). Labs & Collaborations : Affiliated with INFN, TIFPA-INFN, and Q@TN (Quantum@Trento). Organized conferences like Quantum Physics and Geometry (2014) and Quantum Machine Learning (2023). Teaching : Lectures on Analytical Mechanics, Quantum Relativistic Theories, and Special Relativity. Authored textbooks on Spectral Theory and Quantum Mechanics.

Jan de Gierمشاهده پروفایل

استاد

• Mathematical Physics
• Statistical Mechanics
• Solvable Lattice Models
• +۳ مورد دیگر

Jan de Gier is a Professor at the School of Mathematics and Statistics, The University of Melbourne . He is also the Founding Director of MATRIX , Australia’s residential research institute in the mathematical sciences, and a former Deputy Director and Chief Investigator in the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) . Additionally, he co-founded the Australian and New Zealand Association for Mathematical Physics (ANZAMP) in 2011 and served as its inaugural Chair. His research focuses on solvable lattice models at the intersection of mathematical physics and statistical mechanics . Key areas include the application of quantum integrability , algebraic structures like the Yang-Baxter equation, Hecke algebras, and quantum groups, as well as analytical methods such as complex analysis and elliptic curves. His work bridges pure and applied mathematics through connections between enumerative combinatorics , representation theory , and real-world phenomena like traffic flow modeling via exclusion processes . The 15 most recent articles reflect his expertise in integrable systems , non-equilibrium statistical mechanics , and algebraic combinatorics . Topics span Macdonald polynomials , stochastic duality , quantum spin chains , and traffic modeling , with methodologies involving matrix product forms , exact solutions , and critical phenomena analysis. He has contributed to editorial efforts through the AustMS Gazette and MATRIX Annals, and has been involved in public science communication via opinion pieces on mathematics funding and applications. His work emphasizes the importance of fundamental research in driving technological innovation, as highlighted in media articles discussing pi calculation , zero-knowledge proofs , and mathematics education .

Hendrik Weberمشاهده پروفایل

استاد

• Stochastic Analysis
• Stochastic Partial Differential Equations (SPDEs)
• Regularity Structures
• +۴ مورد دیگر

Prof. Dr. Hendrik Weber is a Professor of Mathematics at the University of Münster, leading the Workgroup for Stochastic Analysis. He holds the Bridging the Gaps Professorship and is affiliated with the Faculty of Mathematics and Computer Science. His expertise lies in stochastic analysis, particularly stochastic partial differential equations (SPDEs) and their applications in mathematical physics and statistical mechanics. Weber's research focuses on regularity structures, singular SPDEs, and the interplay between stochastic processes and nonlinear dynamics. Education and Career: Weber earned his PhD from the University of Bonn (2010) and held positions at the University of Warwick (2010–2018) and the University of Bath (2018–2022) before joining Münster in 2022. He has been recognized with awards including the ERC Consolidator Grant (2022), Philip Leverhulme Prize (2017), and Rollo Davidson Prize (2016). Research Interests: Weber's work addresses theoretical challenges in SPDEs, including invariant measures, phase transitions, and scaling limits. His projects span topics like singularities in PDEs, field theory randomness, and deep learning surrogate methods. Recent studies include the dynamic Φ⁴ model, stochastic quantization in non-commutative spaces, and a priori bounds for quasilinear SPDEs. Publications: Over 60 peer-reviewed articles, including high-impact contributions to Annals of Probability , Communications in Mathematical Physics , and Archive for Rational Mechanics and Analysis . His work emphasizes rigorous mathematical analysis of stochastic systems and their physical implications. Awards and Grants: ERC Consolidator Grant (2022), Royal Society Fellowship (2016), and multiple collaborative projects funded by the EPSRC and DFG. His research also bridges theoretical developments with applications in machine learning and feature engineering using regularity structures. Labs/Teams: Leads a dynamic research group comprising PhD students (e.g., Sophie Mildenberger) and postdoctoral researchers. Collaborations with global institutions like the University of Warwick and the University of Bath drive interdisciplinary advancements in stochastic analysis.

• Functional Analysis
• Operator Theory
• Free Probability
• +۳ مورد دیگر

Michael Anshelevich is a Professor of Mathematics at Texas A&M University, affiliated with the College of Arts & Sciences. His research focuses on Functional Analysis, Operator Theory, and Free Probability, with contributions to non-commutative stochastic processes, orthogonal polynomials, and operator-valued distributions. He holds a Ph.D. from the University of California, Berkeley (2000) and a B.S. from the California Institute of Technology (1994). His work bridges combinatorial methods with advanced probability theory, addressing topics like free Lévy processes and free convolution powers. Research interests span non-commutative probability frameworks, including free stochastic measures, Fock space representations, and applications of combinatorial structures to stochastic calculus. Recent articles explore exponential products in operator algebras, Hermite polynomials in Brownian motion contexts, and depth-two actions in Fock spaces. His contributions to free probability include extending classical limit theorems to non-commutative settings and analyzing multiplicative free convolutions. Publications highlight interdisciplinary connections between functional analysis and stochastic processes, with a focus on operator-valued distributions and Jacobi parameters. While no specific awards are listed, his extensive bibliography reflects sustained impact in mathematical physics and operator theory. Advising and grants sections remain unspecified, though his research often involves collaborative projects in stochastic analysis and free probability.

• Real Algebraic Geometry
• Combinatorics
• Convex Optimization
• +۳ مورد دیگر

Cynthia Vinzant is an Associate Professor in the Department of Mathematics at the University of Washington. Her research focuses on real algebraic geometry, combinatorics, and convex optimization, with applications to hyperbolic polynomials, determinantal representations, and convex algebraic geometry. She collaborates extensively on projects involving numerical ranges, quasicrystals, and geometric optimization problems. Research Interests: Real algebraic geometry and its connections to combinatorics and optimization Hyperbolic and log-concave polynomials Convex geometry and spectrahedra Applications in matrix analysis and statistical mechanics Her work spans theoretical advances in algebraic geometry and computational methods, including contributions to the study of principal minors, tropical geometry, and phase retrieval problems. Recent publications highlight her focus on Fourier quasicrystals, higher-rank numerical ranges, and combinatorial structures in matroids. Publications: Over 30 peer-reviewed articles, including influential works on quartic curves, determinantal representations, and log-concave polynomials. Grants & Collaborations: Active in interdisciplinary research, with projects supported by NSF and collaborations in algebraic combinatorics and geometric optimization.

• Control Systems
• Optimization
• Market Design
• +۴ مورد دیگر

Junjie Qin is an Assistant Professor of Electrical and Computer Engineering at Purdue University’s Elmore Family School of Electrical and Computer Engineering. His research focuses on control systems, optimization, market design, and data analytics applied to power systems and the energy-transportation nexus. He explores challenges in distributed energy resource management, smart grid technologies, and the integration of renewable energy sources. His work addresses issues such as scheduling under limited observability, neural risk-limiting dispatch, and joint optimization of transportation-energy systems through electric vehicle charging strategies. Key research areas include power system stability, inverter-dominated grid dynamics, and machine learning applications in energy systems. He investigates topics like real-time charging control for electric roadways, loss function selection in learning-based optimal power flow, and pricing mechanisms for workplace EV charging. His contributions span theoretical frameworks and practical algorithms, emphasizing data-driven solutions and system-level optimization. While no awards or grants are explicitly listed, his publications reflect a strong focus on advancing smart grid technologies and sustainable energy systems. His advising activities are not detailed here, but his research group likely engages in cutting-edge projects at the intersection of control theory and energy infrastructure.

• Free Probability Theory
• Random Matrix Theory
• Operator Algebras
• +۳ مورد دیگر

Ping Zhong is an Associate Professor in the Department of Mathematics at the University of Houston. He previously served as an Assistant Professor at the University of Wyoming (2018-2024). He earned his Ph.D. in Mathematics from Indiana University Bloomington under the supervision of Hari Bercovici. His research focuses on free probability theory, random matrix theory, operator algebras, and their applications to high-dimensional statistics and machine learning. He actively mentors graduate and undergraduate students interested in these areas. Dr. Zhong's work bridges pure mathematics and applied domains, with contributions to spectral analysis, quantum information, and stochastic processes. His recent research explores outlier eigenvalues, Brown measure analysis, and superconvergence phenomena in free probability. He organizes the Analysis Seminar at UH and has been involved in conferences like the RMMC Summer School 2022 on free probability and applications. While no specific awards are mentioned, his extensive publication record indicates sustained academic contribution. He seeks motivated students for collaborative research projects in his areas of expertise.

• Infinite dimensional geometry
• Mathematical physics
• Decision science

Jean-Pierre Magnot serves as an Associate Researcher at LAREMA (Laboratoire Angevin de Recherche en Mathématiques), University of Angers, France, while concurrently holding a High-School Teacher position at Lycée Jeanne d'Arc, Clermont-Ferrand, France. He maintains additional affiliation with the Lepage Research Institute in Slovakia. His research integrates three core domains: Infinite dimensional geometry (focusing on diffeological structures, vector pseudobundles, and Grassmannians), Mathematical physics (specializing in Kadomtsev-Petviashvili hierarchies and pseudo-differential operators), and Decision science (developing geometric frameworks for pairwise comparison matrices and inconsistency reduction). This interdisciplinary approach frequently bridges gauge theory concepts with decision-making algorithms, exemplified by Yang-Mills formulations applied to ranking problems. Recent publications (2024-2025) reveal a cohesive trajectory where diffeological methods unify mathematical physics and decision theory. Key trends include the geometrization of pairwise comparisons through quantum gravity analogies, well-posedness analysis of generalized KP systems, and optimization frameworks for infinite-dimensional spaces. His work demonstrates consistent application of abstract geometric constructs to both theoretical physics and practical decision systems. No scientific awards were documented in the provided sources. Information regarding students advised, doctoral supervision, or research grant acquisitions was not present in the source material. Magnot actively collaborates with international institutions including the Union of Czech Mathematicians and Physicists, University of Prešov (Slovakia), Eötvös Loránd University (Hungary), Italian Society for General Relativity and Gravitation, Transilvania University of Brasov (Romania), VŠB-TU Ostrava (Czech Republic), and Lodz University of Technology (Poland). These partnerships span mathematical physics, differential geometry, and decision science applications.

• Finite Free Probability
• Non-commutative Probability
• Random Matrices
• +۶ مورد دیگر

Dr. Daniel Perales Anaya is a Visiting Assistant Professor in the Department of Mathematics at Texas A&M University, affiliated with the College of Arts & Sciences. He completed his Ph.D. in 2022 at the University of Waterloo under the supervision of Alexandru Nica. His research focuses on Finite Free Probability, a field at the intersection of free probability, random matrices, combinatorics, and non-commutative probability. He also investigates infinitesimal freeness, hypergeometric polynomials, and cumulant theory. He organizes the Free Probability and Operators Seminar at Texas A&M University and maintains an active research profile with contributions to journals like Transactions of the American Mathematical Society and Constructive Approximation . His work bridges classical analysis, operator algebras, and combinatorial structures, often leveraging finite free convolutions and non-crossing partitions. Publications span topics including infinitesimal distributions, hypergeometric polynomial zeros, and S-transforms in finite free probability. His research has been supported by institutions such as the Simons Foundation and Birkhäuser.

• Quantum Information Science
• Quantum Communication Theory
• Theoretical Quantum Cryptography
• +۳ مورد دیگر

Mario Berta is a Professor of Physics at RWTH Aachen University’s Institute for Quantum Information, with an honorary Visiting Reader position at Imperial College London’s Department of Computing. His research focuses on mathematical aspects of quantum information science, including quantum communication theory, cryptography, and algorithms. He leads a group funded by the ERC Starting Grant QEntropy, exploring entropy’s role in quantum information. He actively recruits PhD/postdoc researchers and organizes workshops like the Mathematics of Quantum Information conference at RWTH Aachen and Beyond IID 13 in Munich. Education: PhD in Theoretical Physics from ETH Zurich. Prior roles include Senior Research Scientist at Amazon Web Services’ quantum computing division and Postdoctoral Researcher at Caltech’s IQIM. He has pioneered quantum Gibbs sampling algorithms for the Fermi-Hubbard model and contributed to quantum error correction and complexity theory. His work bridges theoretical foundations with practical implementations, emphasizing resource analysis and algorithm optimization. Research interests span quantum algorithms’ computational complexity, entanglement theory, and information-theoretic security. He explores topics like quantum channel coding, hypothesis testing, and distributed quantum protocols under communication constraints. His group’s activities include organizing international workshops and collaborations with institutions like ML4Q and EPSRC. Funding sources include the European Research Council, RWTH’s Exploratory Research Space, and the EPSRC. He advocates for open-access science, as seen in his German-language article Algorithmen für neue Hardware . His work aims to advance quantum technologies through rigorous mathematical frameworks and experimental feasibility analysis.

Alice Guionnetمشاهده پروفایل

پژوهشگر

• Random Matrix Theory
• Probability Theory
• Statistical Mechanics
• +۳ مورد دیگر

Alice Guionnet is a French mathematician and Research Director at the CNRS, affiliated with the Unité de Mathématiques Pures et Appliquées (UMPA) at École Normale Supérieure de Lyon since 2005. Her research focuses on random matrix theory, probability theory, and their applications in statistical mechanics and large deviations principles. She completed her doctorate in 1995 with a thesis on spin glass dynamics, supervised by Gérard Ben Arous. Her work includes groundbreaking contributions such as the Single Ring Theorem (2009) and studies on large deviations for eigenvalues of Wigner and heavy-tailed matrices. She has been honored with the Oberwolfach Prize (1998), Loève Prize (2009), and Blaise Pascal Medal (2018), and was elected to the French Academy of Sciences in 2017. Key research interests include non-linear Wigner spiked models, spectral phase transitions, and free probability. She has authored over 80 publications, including influential papers on matrix models, eigenvector delocalization, and stochastic processes in disordered systems. Her ERC Project LDRAM (Large Deviations in Random Matrices) explores asymptotic behaviors of random matrix ensembles. Education: PhD from École Normale Supérieure (1995), MSc in Mathematics (ENS Paris, 1989). Labs/Teams: UMPA Lyon, collaborations with CNRS and international institutions. Grants/Awards: Simons Investigator (2012–2015), CNRS Silver Medal (2010).