جست‌وجوی استاد و پژوهشگر

Eric A. Carlenمشاهده پروفایل

استاد

• Functional analysis
• Probability
• Mathematical physics
• +۳ مورد دیگر

Eric A. Carlen is a Distinguished Professor of Mathematics at Rutgers University, specializing in mathematical physics. His faculty position is within the Department of Mathematics where he conducts research at the intersection of functional analysis, probability theory, and mathematical physics. He maintains an active research program with numerous recent publications spanning quantum information theory, statistical mechanics, and partial differential equations. Professor Carlen's research focuses on functional analysis, probability, and mathematical physics, with particular emphasis on problems in non-equilibrium statistical mechanics and variational problems. His work explores geometric inequalities and their applications to physical systems. Recent research directions include: Quantum Markov semigroups and their spectral properties Functional inequalities and their stability Kinetic theory and approach to equilibrium phenomena Quantum information theory and entropy methods Non-equilibrium steady states in boundary-driven systems Analysis of Professor Carlen's recent publications (2023-2025) reveals a strong focus on quantum information theory, particularly quantum Markov processes and entropy inequalities. His work bridges abstract mathematical analysis with applications in statistical mechanics, showing particular interest in hypocoercivity, spectral gaps, and stability of functional inequalities. A significant portion of his recent work connects mathematical analysis with physical applications, especially in non-equilibrium statistical mechanics. Professor Carlen teaches courses in mathematics, including an introduction to the mathematical theory of probability. His office is located in Hill Center 632 at Rutgers University, and he can be contacted at carlen@math.rutgers.edu.

Christian de Rondeمشاهده پروفایل

استاد

• Foundations of Quantum Mechanics
• Philosophy of Physics
• Quantum Logic
• +۳ مورد دیگر

Christian de Ronde holds faculty positions at multiple institutions: Professor at the University of Buenos Aires, Argentina Professor at University Nacional Arturo Jauretche, Argentina Fellow Researcher at CONICET (National Scientific and Technical Research Council), Argentina Affiliated Researcher at Center Leo Apostel and Foundations of the Exact Sciences, Vrije Universiteit Brussel, Belgium His research centers on the philosophical and foundational aspects of quantum mechanics, with emphasis on developing the Logos categorical approach. This framework interprets the Born rule as representing intensive objective information about potential states of affairs through powers and definite potentia, challenging orthodox quantum interpretations while advocating for objective realism. Analysis of his 2023-2025 publications reveals consistent focus on the Logos approach. Key themes include critiques of standard quantum states, equivalence relations in quantum theory, tensorial formulations of entanglement, and the nature of quantum individuals. De Ronde persistently argues for realism in quantum mechanics through potentiality-based frameworks, engaging critically with Bohr's interpretations and proposing novel categorical structures to resolve foundational paradoxes. Scientific Awards: No scientific awards, prizes, or fellowships are mentioned in the provided text. Advising and Grants: The material contains no information about students, advisees, research grants, or funding sources. Labs and Teams: No specific laboratories, research groups, or collaborative teams are referenced in the given documentation.

Collin Capanoمشاهده پروفایل

عضو هیئت علمی

• Gravitational Wave Astronomy
• Black Hole Physics
• Neutron Star Dynamics
• +۳ مورد دیگر

Collin Capano is a Research Associate Professor in the Physics department at Syracuse University. He holds a Ph.D. and B.S. in Physics from Syracuse University (2011 and 2005 respectively). His research focuses on gravitational wave astronomy, black hole spectroscopy, and computational methods for analyzing astrophysical data. He has led projects involving black hole ringdown analysis, neutron star equation of state studies, and multimessenger astronomy. Dr. Capano has secured significant grants including a National Science Foundation award for developing black hole spectroscopy methods and desktop cluster infrastructure (2024-2026) and a Defense University Instrumentation Initiative grant (2022). He currently directs the Open Source Project Office at Syracuse University's Research Computing division. His work has been published in top journals like Physical Review D , Nature Astronomy , and The Astrophysical Journal . Notable contributions include testing general relativity with GW170817 observations and constraining neutron star radii through combined gravitational-wave and electromagnetic data analysis. Awarded the Max-Planck-Gesellschaft performance bonus (2020), he serves as a reviewer for leading journals including Physical Review Letters , Monthly Notices of the Royal Astronomical Society , and Classical and Quantum Gravity . He actively participates in international workshops and conferences, presenting on topics ranging from black hole spectroscopy to the future of gravitational wave astronomy.

Bertrand Lacroix-A-Chez-Toineمشاهده پروفایل

مدرس

• Statistical Mechanics
• Random Matrix Theory
• Extreme Value Statistics
• +۴ مورد دیگر

Dr. Bertrand Lacroix-A-Chez-Toine is a Lecturer in Statistical Mechanics of Disordered Systems at King’s College London’s Department of Mathematics, within the Faculty of Natural, Mathematical & Engineering Sciences. He holds a PhD in theoretical physics from Université Paris-Saclay (2019), focusing on extreme value statistics in correlated systems. Before joining King’s, he completed postdoctoral research at the Weizmann Institute of Science (2019–2021) and King’s College London (2021–2024). His research interests include random matrix theory, extreme value and counting statistics, disordered systems, and large deviations. He is part of the Disordered Systems research group, which focuses on statistical mechanics of complex systems. Recent work explores replica-symmetry breaking in spin glasses, landscape complexity in high-dimensional systems, and equilibrium counting in stochastic processes. Publications span peer-reviewed journals like Journal of Statistical Physics , Physical Review Letters , and Journal of Physics A . His work addresses topics such as spin glass transitions, nonlinear dynamics in disordered systems, and universality in random landscapes.

Yan Fyodorovمشاهده پروفایل

استاد

• Mathematical Physics
• Random Matrix Theory
• Statistical Mechanics of Disordered Systems
• +۴ مورد دیگر

Yan Fyodorov is a Professor of Mathematics and Co-chair in Disordered Systems at King's College London's Department of Mathematics within the Faculty of Natural, Mathematical & Engineering Sciences. He holds a PhD from the Petersburg Nuclear Physics Institute (1988) and has held positions at institutions including Brunel University, University of Nottingham, Queen Mary University, and visiting roles at Cologne University, Isaac Newton Institute, and École normale supérieure. Research Interests: Focuses on random matrix theory, statistical mechanics of disordered systems, quantum chaotic scattering, Anderson localization, and statistical topology of random landscapes. His work bridges pure mathematics and applications in physics, particularly in complex systems and high-dimensional landscapes. Publications: Active in high-impact journals like Physical Review Letters , Annales Henri Poincaré , and Journal of Statistical Physics . Recent work explores eigenvalue statistics, non-orthogonal eigenvectors, and replica symmetry breaking in spin-glass models. Awards: Recognized as a Bessel Research Awardee (2006/7) and Leverhulme Research Fellow (2008). His research has been supported by grants from EPSRC and Alexander von Humboldt Foundation. Labs/Teams: Leads the Disordered Systems group at King's, part of the Centre for Non-Equilibrium Science (CNES), and collaborates with the Probability group in Mathematics.

• Dynamical Systems
• Ergodic Theory
• Stochastic Processes
• +۹ مورد دیگر

Marco Lenci is a Full Professor at the Department of Physics and Astronomy 'Augusto Righi' of the University of Bologna. His academic discipline is Mathematical Physics. Lenci's research focuses on dynamical systems, ergodic theory, and stochastic processes, with applications to physical systems, climate sciences, and biological systems. His work investigates infinite-measure dynamics, billiards (e.g., Lorentz gases), random walks in heterogeneous environments, and quantum large deviations. Key themes include anomalous diffusion, transport phenomena, and large deviations in quantum lattice systems. Recent studies explore limit theorems for human mobility models and applications of dynamics to epidemiology. His publications span topics like ergodic properties of quenched random systems, quantum computing, and post-quantum cryptography. No scientific awards are explicitly mentioned in the provided texts. Lenci's advising and grants activities are not detailed here, but his role as a professor suggests active mentorship. His interdisciplinary research bridges mathematics, physics, and applied sciences, contributing to both theoretical and applied domains.

• Stochastic Partial Differential Equations
• Mathematical Physics
• Nonlinear Analysis
• +۲ مورد دیگر

Guopeng Li is a Research Fellow at the Department of Mathematics within the School of Mathematical & Computer Sciences at Heriot-Watt University, United Kingdom (postcode EH14 4AS). His academic work focuses on advanced mathematical research in stochastic dynamics and nonlinear systems. His primary research areas include Stochastic Partial Differential Equations, Nonlinear Analysis, and Probability Theory. He investigates energy-critical stochastic nonlinear Schrödinger equations with emphasis on global well-posedness, boundary conditions, and conservation laws. His theoretical work bridges mathematical physics and stochastic processes, contributing to fundamental understanding of quantum systems under random perturbations. Recent publications (2021-2022) demonstrate consistent focus on stochastic nonlinear Schrödinger equations, exploring dimensional challenges (4-D systems), boundary value problems, and almost conservation laws. This research trajectory reveals deep specialization in stochastic PDE theory with applications to quantum mechanics and wave propagation phenomena.

Oana Pocovnicuمشاهده پروفایل

دانشیار

• Nonlinear Partial Differential Equations
• Probabilistic Methods in PDEs
• Mathematical Analysis
• +۲ مورد دیگر

Oana Pocovnicu is an Associate Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University, United Kingdom. Her research focuses on nonlinear partial differential equations, probabilistic methods in PDEs, and stochastic processes, particularly in the context of dispersive equations and wave dynamics. Research Trends: Recent publications highlight her work on probabilistic well-posedness for nonlinear wave equations, stochastic nonlinear Schrödinger equations with nonsmooth noise, and higher-order expansions for PDEs in negative Sobolev spaces. Collaborations span international institutions, with key contributions to stochastic analysis in mathematical physics.

Yi Shenمشاهده پروفایل

دانشیار

• Applied Probability
• Stochastic Processes
• Extreme Value Theory
• +۳ مورد دیگر

Yi Shen is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, Canada. He holds affiliations with the Institute of Quantum Computing. His research focuses on applied probability, stochastic processes, and their symmetries, including stationarity, self-similarity, and exchangeability. He explores applications in extreme value theory, financial mathematics, quantum information, and statistical physics. Education: PhD in Operations Research (Cornell University, 2013) under Gennady Samorodnitsky; Ingenieur in Quantitative Economics and Finance (École Polytechnique, 2008); BS in Mathematics and Physics (Tsinghua University, 2005). Research emphasizes random locations of stochastic processes (e.g., supremum locations) and their connections to probabilistic symmetries. Recent work bridges probability with quantum mechanics, econometrics, and machine learning. His publications address topics like regression discontinuity designs, operator-scaling Gaussian fields, and quantum system Hamiltonian inference. Key contributions include analyzing self-similar processes, ergodic theory applications, and separability-entanglement classification in quantum systems. His work spans theoretical probability to applied domains like finance and quantum computing.

Neil Watlingمشاهده پروفایل

دانشیار

• Functional Analysis
• Mathematical Physics
• Non-Commutative Geometry
• +۳ مورد دیگر

Neil Watling is an Associate Professor in the Department of Mathematics at Widener University. His research focuses on C*-algebras, mathematical physics, and non-commutative geometry, with recent work exploring intersections of probability, linear algebra, and number theory. He holds a PhD in Functional Analysis from the University of Warwick (UK, 1989). Education: PhD, Functional Analysis, C*-algebras (1989), University of Warwick (UK) Research Interests: Explores automorphic group actions on C*-algebras, fixed point sub-algebras, and rotation algebras. Recently investigates independence and roundness concepts in probability/number theory. His work bridges abstract algebra with geometric and physical applications. Publications: Focused on operator algebras and discrete mathematics. Key themes include divisibility theory, discretized algebraic structures, and dynamical systems on tori. Professional Affiliations: Member of the American Mathematical Society (AMS) and Mathematical Association of America (MAA).

Alexander Mollمشاهده پروفایل

استادیار

• Probability Theory
• Mathematical Analysis
• Integrable Probability
• +۳ مورد دیگر

Alexander Moll is an Assistant Professor of Mathematics at Reed College, specializing in probability theory and mathematical analysis. His research encompasses integrable probability, non-linear dispersive waves, soliton quantization, and semi-classical analysis. He earned a B.A. from Columbia University and a Ph.D. from M.I.T. Before joining Reed in 2022, he held postdoctoral positions at the Institut des Hautes Études Scientifiques, Hausdorff Center for Mathematics, Northeastern University, and served as the inaugural Robert T. Seeley Visiting Assistant Professor at the University of Massachusetts Boston. His recent publications focus on asymptotic analysis in probability, spectral theory of integrable systems, and combinatorial aspects of mathematical physics. The research demonstrates a consistent exploration of boundary phenomena and symmetry structures across different mathematical domains.

Rebecca Conleyمشاهده پروفایل

استادیار

• Numerical Analysis
• Finite Element Method
• Quantum Computing
• +۲ مورد دیگر

Dr. Rebecca Conley is an Assistant Professor of Mathematics at Saint Peter's University, where she has taught since 2016 while serving as Associate Director of Faculty Research & Development. Her contact information includes rconley@saintpeters.edu and Loyola Hall, Room 25. Her academic credentials include: Ph.D. from Stony Brook University M.A. from Hunter College B.A. from Pace University Dr. Conley's research centers on numerical analysis with specialization in finite element methods, where she pioneered the Adaptive Extended Stencil Finite Element Method (AES-FEM) to overcome element quality limitations. She has expanded into quantum computing for solving boundary value problems and developed innovative statistics education activities emphasizing active learning through technology integration. Her publication record from 2010-2024 reveals three distinct research thrusts: foundational AES-FEM work (2013-2016), quantum computing applications (2020-2023), and statistics pedagogy (2021). The 2016 cluster shows concentrated innovation in numerical methods, while recent work demonstrates strategic expansion into quantum algorithms and educational design. Her professional recognition includes: Varrichio Teaching Award (2018) Dr. Conley maintains an active teaching schedule across algebra, probability, and statistics courses but has not publicly disclosed research grants or formal student advising relationships. Her collaborative work with computational scientists like X. Jiao and J. Glimm suggests interdisciplinary engagement without dedicated laboratory facilities.

• High-dimensional Statistics
• Machine Learning
• Signal Processing
• +۵ مورد دیگر

Karim Lounici is a Professor at the Centre de Mathématiques Appliquées (CMAP) of Ecole Polytechnique. His research focuses on high-dimensional statistics, machine learning, signal/image processing, probability theory, and optimization. He explores theoretical foundations and practical applications in areas like stochastic processes, quantum tomography, and dynamical systems. His work bridges mathematical rigor with computational methods, addressing challenges in data analysis, uncertainty quantification, and algorithmic efficiency. Recent contributions include equivariant representation learning, robust covariance estimation, and learning Koopman operators for dynamical systems. Publications span topics like neural conditional probability, spatio-temporal Monge alignment, and domain adaptation, reflecting expertise in both statistical theory and applied machine learning. No scientific awards explicitly mentioned. No advising or grant details provided in text. Affiliated with CMAP, a leading applied mathematics research center at Ecole Polytechnique.

Frédéric Patrasمشاهده پروفایل

پژوهشگر

• Algebra
• Combinatorics
• Probability Theory
• +۴ مورد دیگر

Frédéric Patras is a Researcher (Directeur de Recherche CNRS) at Université Côte d'Azur, based at the Laboratoire J.A. Dieudonné (UMR CNRS-UNS N°7351). He holds editorial roles at journals including Annals of Mathematics and Philosophy , Annales de l’Institut Henri Poincaré D , and EpiDEMES . He co-leads the PhilMathMED network and participates in research projects like ANR CARPLO and ANR PAGCAP. His research spans algebra, combinatorics, probability theory, and the philosophy of mathematics, with a focus on algebraic structures in quantum theory and stochastic processes. Education: PhD in Mathematics (1992, Université Paris 7) with a thesis on homotopy and simplicial homology. Leadership roles: Membre du Comité de direction de l'IFR en Epistémologie, organizer of international conferences (e.g., PhilMathMED 2023, Algebraic Combinatorics of the Symmetric Groups). His work bridges pure mathematics and interdisciplinary applications, including credit risk modeling, quantum independence structures, and the interplay between algebraic combinatorics and phenomenology. Recent research emphasizes free probability theory, renormalization group actions, and Hopf algebraic methods. Key contributions include studies on shuffle algebras, cumulant-cumulant relations, and the application of group-theoretical approaches to non-commutative probability. He has edited volumes on credit risk and mathematical thinking, and his articles span journals in mathematics, physics, and philosophy.

• Medical Imaging
• Artificial Intelligence
• Deep Learning
• +۳ مورد دیگر

Mena Shenouda is a Researcher in the Department of Radiology & Biomedical Imaging at Yale School of Medicine (Yale University). Their work focuses on advancing AI-driven medical imaging technologies to improve clinical outcomes, particularly in disease detection and diagnostic accuracy. Shenouda holds a Ph.D. in Medical Physics from the University of Chicago (2024) and a B.S. in Physics and Biophysics (Honors) from the University of Michigan (2019). They are also completing a Medical Physics Diagnostic Imaging Residency at Yale, set to conclude in 2026. Education: B.S. Physics, Biophysics (Honors), University of Michigan (2019) Ph.D. Medical Physics, University of Chicago (2024) Medical Physics Diagnostic Imaging Resident, Yale University (2026) Research Interests: Shenouda specializes in applying artificial intelligence and deep learning to medical imaging challenges. Their work includes developing algorithms for detecting diseases such as COVID-19 and pleural mesothelioma , optimizing radiomics features for clinical decision-making, and improving image reconstruction techniques. They emphasize the generalizability and ethical implementation of AI models in healthcare. Publications: Shenouda has authored peer-reviewed studies in high-impact journals like Journal of Medical Imaging and JCI Insight , focusing on deep learning applications in radiology and oncology. Their research bridges computational methods with clinical practice, addressing real-world challenges in imaging technology. Professional Contributions: As part of the Radiology & Biomedical Imaging team, Shenouda collaborates on translational research initiatives. Their projects align with Yale’s broader goals in precision medicine and healthcare innovation.