جست‌وجوی استاد و پژوهشگر

Marc Moreno Mazaمشاهده پروفایل

استاد

• Computer Algebra
• Polynomial System Solving
• Parallel Algorithms
• +۳ مورد دیگر

Marc Moreno Maza is a Professor in the Computer Science and Applied Mathematics Departments at the University of Western Ontario, and a Principal Scientist at the Ontario Research Centre for Computer Algebra (ORCCA). His research focuses on applying computer science to mathematics, particularly polynomial system solving and algorithm design. Key areas include parallel computing, high-performance algebraic algorithms, and GPU acceleration. He leads projects funded by NSERC and industry partnerships, such as 'Hardware Acceleration Technologies for Polynomial Systems' and collaborative work with IBM and CAS Research. His research spans four directions: theoretical foundations of polynomial equations, efficient algorithm development, software implementation (e.g., RegularChains library in Maple), and applications to real-world challenges. He has delivered over 100 talks worldwide on topics like cylindrical algebraic decomposition, GPU-based polynomial arithmetic, and parametric system solving. His work emphasizes optimizing algorithms for modern architectures and leveraging parallelism. Notable contributions include the BPAS and CUMODP libraries for polynomial arithmetic, and the RegularChains library for semi-algebraic set computations. He collaborates internationally, with grants supporting both theoretical and applied research. His team addresses challenges in computational algebra, from theoretical breakthroughs to practical software tools.

• Quantum Foundations
• Quantum Entanglement
• Time-Symmetry
• +۳ مورد دیگر

Ken Wharton is a Professor of Physics & Astronomy at San José State University (SJSU). His research focuses on quantum foundations, particularly retrocausal models and time-symmetric interpretations of quantum phenomena. He advocates for frameworks that resolve quantum paradoxes by treating spacetime as a four-dimensional whole, emphasizing retrocausation. Wharton's work often addresses Bell's theorem, entanglement, and the compatibility of quantum mechanics with relativity. Education: PhD in Physics, University of California, Los Angeles (1998) BS in Physics, Stanford University (1992) Research Interests: Wharton explores how quantum phenomena can be explained through classical-like four-dimensional boundary value problems. His retrocausal models allow future constraints to influence past outcomes, bypassing traditional 'no-go' theorems. Key themes include entanglement mechanisms, time-symmetry in quantum systems, and the philosophical implications of retrocausality. Research Group: He leads a team at SJSU comprising graduate and undergraduate students, focusing on theoretical and conceptual challenges in quantum foundations. Recent work includes studies on entanglement swapping, spacetime path integrals, and the role of symmetry in retrocausal models. Awards: Award-winning essay: 'The Universe is Not a Computer' , challenging computational interpretations of quantum reality. Grants & Collaborations: His research has been supported by grants exploring retrocausal interpretations and quantum foundations. Collaborations include work with Nathan Argaman on time-symmetric boundary conditions and Rod Sutherland on localized quantum realities.

Travis Kowalskiمشاهده پروفایل

استاد

• Complex Analysis
• Mathematical Pedagogy
• Formal Power Series
• +۲ مورد دیگر

Travis Kowalski is Professor and Department Head of Mathematics at South Dakota Mines. Originally an art student, he transitioned to mathematics while maintaining artistic approaches to mathematical expression. His research spans complex analysis, formal power series, and mathematics pedagogy. Research interests include solving differential equations through infinite polynomials and developing abilities-based assessment methods. Received prestigious awards including the Mathematical Association of America's George Pólya Award and Chauvenet Prize. Teaching covers diverse courses from College Algebra to Game Theory, recognized with institutional and national teaching excellence awards. Mathematical artwork appears in daily 'constrained art' creations.

Martin Jurášمشاهده پروفایل

استاد

• Mathematics
• Cryptography
• Algebra
• +۳ مورد دیگر

Martin Juráš is Professor of Mathematics in the School of Liberal Arts at Savannah College of Art and Design (SCAD), Savannah, GA, holding this position since August 2015. He earned dual Ph.D. degrees in Mathematical Sciences from Utah State University and Mathematical Engineering from Brno University of Technology, along with an M.S. in Information Systems and Theoretical Computer Science from Univerzita J.E. Purkyně. His research spans algebra, cryptography, topological rings, and computational mathematics, with applications in encryption systems and invariant theory. Key domains include public-key cryptosystems, polynomial irreducibility, and differential equations. Recent scholarly work demonstrates a strong trend toward cryptographic mathematics, with 10+ publications on group invariants applied to security systems. Notable theoretical contributions include extensions of Eisenstein-Dumas irreducibility criteria. Qatar National Research Foundation Grants (2012-2016, 2013-2017)

• Interactive Theorem Proving
• Topological Combinatorics
• Algorithms
• +۲ مورد دیگر

Matt Superdock is an Assistant Professor in the Department of Computer Science at Rhodes College, Memphis, Tennessee. He holds a Ph.D. in Algorithms, Combinatorics, and Optimization from Carnegie Mellon University (2021), advised by Florian Frick. His research focuses on Interactive Theorem Proving (formal proofs, dependently typed data, metacircular languages) and Topological Combinatorics (Borsuk-Ulam extensions, simplicial complexes, finite projective planes). Recent work includes collaborations on Vietoris-Rips complexes, fundamental group constructions, and applications of topological methods in combinatorics. Publications appear in Discrete Mathematics , Journal of Topology and Analysis , and Journal of Combinatorial Theory . He teaches advanced algorithms, data structures, and programming fundamentals at Rhodes. Previously, he taught AP Calculus and Computer Science at Charles E. Jordan High School. Software contributions include vim-agda (asynchronous type-checking for Agda), agda-unused (code analysis tool), and vim-foldout (syntax-aware folding in Vim).

Robert van den Hoogenمشاهده پروفایل

استاد

• Mathematical Cosmology
• General Relativity
• Teleparallel Gravity
• +۳ مورد دیگر

Robert van den Hoogen is a Professor of Mathematics and Statistics at Saint Francis Xavier University (St. F.X.). He previously served as Dean of Science at St. F.X. from 2009 to 2015 before returning to the Department of Mathematics and Statistics in 2016 to focus on research and teaching. His education includes a Ph.D. in Mathematics and Statistics (1995) from Dalhousie University and an undergraduate degree from Saint Mary's University. His research focuses on mathematical cosmology and general relativity, with a particular emphasis on teleparallel gravity theories and the averaging problem in cosmology. He explores alternative explanations for Dark Energy, investigates symmetries in gravitational geometries, and examines how inhomogeneities in the universe affect its large-scale evolution. His work bridges differential geometry and cosmological modeling. Recent articles highlight advancements in teleparallel geometry, Bianchi cosmological models, and symmetry analyses in Riemann-Cartan spaces. These contributions reflect a sustained exploration of gravitational theories and their cosmological implications. No scientific awards are explicitly mentioned in the provided text. His academic career includes extensive teaching and administrative roles, with a strong focus on maintaining research output in theoretical physics. Collaborative efforts and grants are not detailed here, but his publications indicate active engagement with global research communities in cosmology and mathematical physics.

Dagomir Kaszlikowskiمشاهده پروفایل

دانشیار

• Quantum Entanglement
• Quantum Correlations
• Nonlocality
• +۶ مورد دیگر

Dagomir Kaszlikowski is an Associate Professor at the Department of Physics, Faculty of Science, National University of Singapore (NUS), and a Principal Investigator at the Centre for Quantum Technologies (CQT). His research focuses on foundational aspects of quantum theory, particularly correlations in quantum systems, which underpin quantum nonlocality, contextuality, and quantum information processing. He leads the Dagomir Kaszlikowski Group, exploring topics like quantum supremacy through alternative formulations of quantum mechanics and the social/economic impacts of quantum technologies. His recent work includes studies on electric-magnetic duality in lattice gauge theory, quantum geometric invariance, and spatiotemporal frameworks for quantum processes. He collaborates extensively with researchers such as Jia Zhian, Sheng Tan, and Pawel Kurzynski. His group investigates quantum correlations, quantum computing, and the intersection of quantum mechanics with thermodynamic properties. His research group's publications demonstrate a consistent focus on quantum information theory, nonlocality, and contextuality across multiple platforms including optical systems and lattice models. Key themes include entanglement, quantum algorithms, and fundamental tests of quantum theory. Contact: phykd@nus.edu.sg | Office: S15-06-09, NUS

Rita Teixeira da Costaمشاهده پروفایل

استادیار

• Mathematical General Relativity
• Black Holes
• Hyperbolic Partial Differential Equations
• +۳ مورد دیگر

Rita Teixeira da Costa is an Assistant Professor at the Department of Pure Mathematics and Mathematical Statistics (DPMMS) at the University of Cambridge, and Sheila Edmonds Lecturer at Newnham College. She holds a dual affiliation as an NSF and Princeton Gravity Initiative Fellow (2021–2024) and Junior Research Fellow at Trinity College. Her research focuses on Mathematical General Relativity, particularly black hole dynamics, hyperbolic PDEs, and geometric analysis. Her work explores foundational questions in gravitational physics, including stability properties of black holes, the behavior of gravitational waves, and the interplay between geometric structures and partial differential equations. Notable contributions include analyses of the Teukolsky equation on Kerr spacetimes and homogenization techniques applied to Einstein’s equations in symmetric configurations. Key awards include her NSF fellowship and Trinity College Junior Research Fellowship. While her profile does not explicitly list grants or advising roles, her publications reflect active engagement in collaborative research with institutions like Princeton University and international co-authors. Her personal homepage at DPMMS provides further details on her research outputs and academic activities.

• Machine Learning
• Spatial Statistics
• Bayesian Inference
• +۳ مورد دیگر

James Martin is an Honorary Research Fellow in the Statistics Section of the Department of Mathematics at Imperial College London, part of the Faculty of Natural Sciences. He previously served as a Senior Teaching Fellow, leading modules on the MSc in Machine Learning and Data Science. His research focuses on machine learning applications in engineering, spatial statistics for ecological systems, and Bayesian inference methods using likelihood-free approaches, particularly sequential Monte Carlo techniques. He is affiliated with the Artificial Intelligence Network, Mathematics research and teaching staff, and the Statistics group. His work bridges theoretical statistical methodologies with practical applications in environmental and engineering domains. Recent publications (2012–2025) emphasize advancements in Bayesian computational methods, spatial point processes, and network analysis, reflecting his interdisciplinary approach to solving complex data-driven problems. While no formal advising or grant details are provided, his academic contributions underscore a commitment to advancing computational and applied statistics. He collaborates within Imperial’s mathematics and AI communities, contributing to cutting-edge research initiatives in data science.

• Bayesian Computational Statistics
• Markov Chain Monte Carlo (MCMC)
• Approximate Bayesian Computation (ABC)
• +۴ مورد دیگر

Robin Ryder is a Senior Lecturer in Statistics at the Department of Mathematics, Imperial College London, within the Faculty of Natural Sciences. He previously held positions as Associate Professor (maître de conférences HDR) at Université Paris-Dauphine and an associate member at École Normale Supérieure, Paris. His research focuses on Bayesian computational statistics (MCMC and ABC methods) and stochastic modeling in the Humanities, particularly Linguistics and Social Sciences. Education: DPhil in Statistics , University of Oxford Habilitation à Diriger les Recherches , Paris Dauphine University Research Interests: Dr. Ryder specializes in advancing computational methods for statistical inference, including Markov Chain Monte Carlo (MCMC) and Approximate Bayesian Computation (ABC). His applied work bridges statistics with the Humanities, addressing questions in linguistic phylogenetics, cultural evolution, and social sciences. Notable areas include modeling language evolution, analyzing sign language histories, and investigating functional load dynamics in linguistic systems. Recent Contributions: His work spans theoretical advancements (e.g., saddlepoint Monte Carlo for ecological inference) and applied studies (e.g., phylogenetic models for Kra-Dai languages and weaving technologies). He frequently collaborates on interdisciplinary projects, such as computational analyses of sign language histories and formal assessments of primate communication systems. Awards & Recognition: While no explicit awards are listed, his contributions have been featured in prominent outlets like Science and French popular science magazine Pour la Science . Grants & Advising: Details on grants or advisees are not explicitly mentioned, though his involvement in editorial boards (e.g., Bayesian Analysis ) underscores his leadership in statistical methodology. He actively participates in conferences and workshops, emphasizing sustainability by advocating for reduced academic travel.

Jun Zhangمشاهده پروفایل

استاد

• Information Geometry
• Optimal Transport
• Statistical Learning Theory
• +۷ مورد دیگر

Jun Zhang is a Professor of Psychology and holds a courtesy appointment in the Department of Statistics at the University of Michigan. He earned his Ph.D. in Statistics from the University of California, Berkeley. His research spans interdisciplinary areas, including information geometry, optimal transport theory, machine learning, and cognitive neuroscience. Notably, he explores applications of geometric structures to statistical models and neural systems. Key research themes include the development of reproducing kernel Banach spaces, entropy deformation theory, and the integration of differential geometry with statistical methodologies. His work often bridges abstract mathematical frameworks with empirical studies in neuroscience, such as modeling neuronal firing rates and analyzing fMRI data in social decision-making contexts. Zhang’s contributions to Bayesian inference, topological data analysis, and neurocomputational modeling reflect his expertise in both theoretical and applied domains. His recent articles highlight advancements in Kähler geometry for optimal transport, statistical mirror symmetry, and the neural basis of strategic reasoning. While no specific grants or awards are listed in the provided text, his prolific publication record underscores his influence in these fields. Collaborative projects involve interdisciplinary teams addressing complex problems at the intersection of mathematics, psychology, and statistics.

Ralf Spatzierمشاهده پروفایل

استاد

• Differential Geometry
• Dynamical Systems
• Ergodic Theory
• +۱۰ مورد دیگر

Ralf Spatzier is the Gopal Prasad Collegiate Professor of Mathematics at the University of Michigan, Department of Mathematics (College of Literature, Science, and the Arts). He holds a Ph.D. in Mathematics from the University of Warwick (1983). His research focuses on differential geometry, dynamical systems, ergodic theory, and rigidity phenomena in geometric and algebraic structures. Key interests include higher rank rigidity, Anosov actions, symmetric spaces, and Zimmer’s program. Education: Ph.D., Mathematics, University of Warwick (1983). Research emphasizes rigidity of geometric and dynamical systems under symmetry or curvature conditions. Recent work explores smooth actions of higher rank groups, Carnot metrics, and local rigidity of lattice actions. Notable contributions include classification of Cartan actions and rigidity of symmetric spaces. Scientific Awards: Gopal Prasad Collegiate Professor (2024), AMS Fellow (2013), Sloan Foundation Fellow (1988). He serves as editor for Michigan Math Journal , Geometriae Dedicata , and Journal of Modern Dynamics . Advising: Over 20 doctoral students since 1995, including notable researchers in geometry and dynamics. Active in training through NSF RTG grants and inquiry-based learning initiatives. Labs/Teams: Collaborates widely in geometric group theory, dynamical systems, and rigidity theory. Leads editorial roles and organizes seminars in his research areas.

Stefan Lukitsمشاهده پروفایل

مدرس

• Formal Epistemology
• Nietzsche Studies
• Legal Positivism
• +۳ مورد دیگر

Stefan Lukits is a Sessional Lecturer in the Department of Philosophy at the University of British Columbia and holds a faculty position in the Mathematics Department at the British Columbia Institute of Technology. He holds an M.Sc. in Mathematics from the University of Graz and a Ph.D. in Philosophy from UBC. His research focuses on formal epistemology, particularly quantitative partial belief representation, alongside interests in Nietzsche studies and legal positivism. He teaches courses such as Philosophy and Literature (PHIL 375) exploring hermeneutics and Central European writers, and Philosophy of Law (PHIL 338) examining legal positivism and Marxist legal theory. His publications address topics ranging from Nietzsche’s anti-humanism to probabilistic reasoning frameworks in epistemology. Office hours are Tuesdays & Thursdays 4–5pm (by appointment), with additional availability upon request. Research highlights include formal analyses of belief geometry and trust in textual interpretation, alongside contributions to debates on Carnap’s conventionalism and entropy-based reasoning models.

• String Theory
• Quantum Gravity
• General Relativity
• +۴ مورد دیگر

Professor Daniel Waldram is a leading academic in theoretical physics at Imperial College London's Department of Physics, part of the Faculty of Natural Sciences. He serves as Head of the Physics of the Universe Community. His research focuses on string theory, quantum field theory, and gravity, with emphasis on geometric structures in string theory. His work explores connections between geometry and string theory, including flux compactifications, moduli stabilization, and dualities. Notable contributions include exceptional generalised geometry frameworks, M-theory compactifications, and AdS/CFT correspondence applications. He has pioneered methods for consistent truncations in supergravity and explored supersymmetric vacua in diverse dimensions. Recent publications (2021–2024) emphasize advanced topics like Y-algebroids, exceptional complex structures, and wrapped M5-branes. His theoretical work bridges abstract geometry with physical realizations, influencing modern approaches to quantum gravity and string vacua. Research affiliations include the Theoretical Physics Group, Physics of the Universe, and the Imperial College Artificial Intelligence Network. His contributions have advanced understanding of non-geometric backgrounds, dualities, and holographic principles.

Eric Mazumdarمشاهده پروفایل

استادیار

• Machine Learning
• Algorithmic Game Theory
• Economics
• +۵ مورد دیگر

Eric Mazumdar is an Assistant Professor of Computing and Mathematical Sciences and Economics at the California Institute of Technology (Caltech), holding dual appointments in the Division of Engineering and Applied Science and the Humanities and Social Sciences division. His research bridges machine learning and economics with applications in societal-scale systems. His educational background includes a B.S. in Electrical Engineering and Computer Science from MIT (2015) and a Ph.D. in Electrical Engineering and Computer Science from UC Berkeley (2021), where he was co-advised by Michael Jordan and Shankar Sastry. Mazumdar's research focuses on theoretical foundations of learning algorithms in uncertain, dynamic environments interacting with strategic agents . Key areas include algorithmic game theory, reinforcement learning in strategic settings, risk-aware decision-making, and behavioral economics. His work addresses challenges in intelligent infrastructure, online markets, e-commerce, and healthcare delivery through rigorous mathematical frameworks. His publication trends reveal a strong focus on zero-sum stochastic games , distributionally robust reinforcement learning , and strategic classification , with increasing integration of optimization theory and game-theoretic principles. Recent work emphasizes sample efficiency, risk aversion, and equilibrium computation in multi-agent systems. NSF Career Award for studying strategic interactions in Societal-Scale Systems Research Fellowship for Learning in Games from the Simons Institute Mazumdar advises multiple postdocs (Zaiwei Chen, Laixi Shi, Kishan Panaganti) and graduate students (Lauren Conger, Tinashe Handina, Yizhou Zhang), with research funded by NSF, DARPA, and Amazon. His group explores applications in intelligent infrastructure and healthcare systems through collaborations with Caltech's Linde Institute and Center for Social Information Sciences (CSIS).