جست‌وجوی استاد و پژوهشگر

Joan Lindمشاهده پروفایل

دانشیار

• Analysis
• Complex Analysis
• Probability

Joan Lind is an Associate Professor of Mathematics and serves as Associate Head for Math Majors and Minors and Director of the Math Honors Program at the University of Tennessee, Knoxville. She holds a Ph.D. in Mathematics from the University of Washington. Her research focuses on complex analysis, probability, and geometric function theory, particularly exploring Loewner theory, stochastic processes, and conformal mappings. Her academic roles include leading undergraduate and honors programs in mathematics. Lind's work bridges analysis and probability, addressing topics such as phase transitions in Loewner hulls, modulus convergence, and SLE trace regularity. She collaborates with researchers like Steffen Rohde and Nikolai Albin on projects involving geometric and probabilistic methods. Lind's research has been published in journals like Duke Math. J., Indiana Univ. Math. J., and Mathematische Annalen. She contributes to advancing understanding of Loewner equations, fractal geometry, and stochastic dynamics. Her teaching and mentorship roles reflect her commitment to both research and academic leadership.

Dmitry Belyaevمشاهده پروفایل

استاد

• Probability Theory
• Mathematical Physics
• Analysis
• +۵ مورد دیگر

Dmitry Belyaev is a Professor of Mathematics at the University of Oxford and a Tutorial Fellow at St. Anne's College. His research focuses on the intersection of analysis and probability, particularly Gaussian fields, critical phenomena, and Schramm-Loewner Evolution (SLE). He has made significant contributions to understanding the geometry of random functions, including work on zeros of random plane waves and Diffusion-Limited Aggregation models. His teaching includes advanced courses such as Metric Spaces, Complex Analysis, and Continuous Martingales. Research Interests: Geometry of Gaussian fields and critical points Stochastic processes in complex systems SLE and conformal maps Random fractals and percolation theory Harmonic measure and multifractal analysis Publications highlight studies on nodal domains, excursion sets, and critical point correlations in Gaussian fields. His work often bridges probability theory with geometric analysis, addressing questions about universality, continuity, and phase transitions. Supervised students include notable researchers in stochastic processes and mathematical physics.

Avelio Sepúlvedaمشاهده پروفایل

استادیار

• Probability Theory
• Statistical Physics
• Random Geometry
• +۵ مورد دیگر

Avelio Sepúlveda is an Assistant Professor in the Department of Mathematics at Universidad de Chile, where he has been affiliated since 2021. He previously held a Chair CMM–CNRS fellowship (2020–2021) and completed postdoctoral work at Université Lyon 1 (2017–2020). His education includes a PhD from ETH Zürich (supervised by Wendelin Werner), a Master's from Université d'Orsay, and an Engineering degree from Universidad de Chile. His research centers on probability theory and statistical physics , with emphases on Gaussian free fields, random planar maps, percolation theory, and topological phase transitions. Key investigations include the structure of 2D Gaussian free fields, scaling limits of decorated planar maps, and dynamic conditioning of Markov processes ( myopic conditioning ). His publications (2020–2025) predominantly explore probabilistic geometry, phase transitions, and field theory, with recurring themes in conformal invariance, scaling limits, and lattice models. Notable methodological contributions include novel algorithms for myopic processes and combinatorial characterizations of Markov properties in planar maps. Awards & Service: Chair CMM–CNRS of Excellence for Young Researchers (2020–2021) Associate Editor: Electronic Journal of Probability and Electronic Communications in Probability Advising & Collaborations: He mentors six PhD/Master's students (Pablo Araya, Paul Cahen, Damian Cid, Felipe Espinosa, Pablo Zúñiga, Tomás Laengle) and collaborates extensively with researchers globally, including Christophe Garban (ERC Vortex). He co-organizes the Seminario de Probabilidades de Chile and workshops (e.g., 2025 Topological Phase Transition workshop).

• Theoretical High Energy Physics
• Gravitational Physics
• Astroparticle Physics
• +۳ مورد دیگر

Zhengwen Liu is an Assistant Professor at the Niels Bohr Institute, University of Copenhagen, specializing in Theoretical High Energy, Astroparticle and Gravitational Physics. He joined the Niels Bohr International Academy on October 1, 2022, and maintains his office at Blegdamsvej 17, 2100 Copenhagen Ø. His research focuses on the intersection of gravitational physics, high-energy theory, and astroparticle phenomena, with particular emphasis on binary black hole dynamics and gravitational wave physics. His work centers on post-Minkowskian theory for binary systems, employing scattering amplitudes, effective field theory, and computational techniques to model gravitational dynamics at high precision. Recent publications demonstrate expertise in conservative dynamics, radiation reaction, and soft emission theorems across quantum field theory and general relativity. He frequently collaborates with leading researchers including Dlapa, Kälin, and Porto, producing high-impact work in journals like Physical Review Letters and Journal of High Energy Physics . Analysis of his 2023-2025 publications reveals a dominant focus on fourth and fifth post-Minkowskian orders in binary dynamics, with significant contributions to gravitational self-force calculations and machine learning applications for gravitational integrals. His research bridges theoretical high-energy physics with gravitational wave astronomy, addressing both foundational aspects of general relativity and practical waveform modeling. No scientific awards were mentioned in the provided materials. No information regarding student advising or research grants was available in the source texts. Liu operates within the Theoretical High Energy, Astroparticle and Gravitational Physics research group at the Niels Bohr Institute, which forms part of the broader Cosmic Dawn Center (DAWN) collaboration. This group specializes in gravitational wave theory, high-energy scattering in curved spacetime, and connections between quantum field theory and gravity through amplitude techniques.

• Social Psychology
• Psychology of Persuasion
• Vocal Communication
• +۴ مورد دیگر

Dr Thomas Ian Vaughan-Johnston is Lecturer (Assistant Professor) in Social Psychology at Cardiff University’s School of Psychology. He studies persuasion—especially how vocal cues such as intonation, speed, and pitch influence attitude change—and explores how individual differences in personality, self-esteem beliefs, and attitude neutrality moderate these effects. He also investigates methodological issues that affect replication success in psychology. Education & Training PhD in Psychology (Queen’s University, Canada) SSHRC CGS-Doctoral Fellowship (2018-2021) Ontario Graduate Scholarship (2017-2018) SSHRC CGS-Masters Scholarship (2015-2016) Research Interests His work integrates three core domains: Vocal Communication & Persuasion: Examining how variations in vocal confidence, affect, speed, and pitch shape source credibility and message impact. Self & Attitude Processes: Investigating how lay beliefs about self-esteem and the desire to hold neutral attitudes guide self-regulation and receptivity to influence. Methodology & Replication: Studying how recruitment and sampling choices affect replicability in social-personality research. Scientific Awards & Grants BA/Leverhulme Small Research Grant (£10k, 2025) Durham University Research Accelerator Award (£10k, 2023-2025, twice awarded) SSHRC CGS-Doctoral Fellowship (£22k/yr, 2018-2021) Ontario Graduate Scholarship (£6k, 2017-2018) SSHRC CGS-Masters Scholarship (£6k, 2015-2016) Teaching & Supervision Dr Vaughan-Johnston coordinates and lectures on core undergraduate modules, achieving student satisfaction ratings of 4.5/5. He teaches social psychology topics (prejudice, emotion, conformity), supervises undergraduate, master’s, and doctoral research, and has led interdisciplinary initiatives on communication skills. He is currently supervising PhD student Benedict Holden. Laboratory & Team He leads an active research group within the Cardiff School of Psychology, collaborating with international scholars such as Professors Fabrigar, Guyer, Briñol, and Jacobson. The team employs experimental, cross-cultural, and meta-scientific methods to advance understanding of persuasion and self-regulation.

Kazi Lutful Kabirمشاهده پروفایل

استادیار

• Data Mining
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

Kazi Lutful Kabir is an Assistant Professor in the Department of Information Sciences and Technology at George Mason University (GMU). He previously served as an Assistant Professor at Stevens Institute of Technology and held a research fellowship at Los Alamos National Laboratory (LANL). His research focuses on applying data mining and machine learning techniques to address biological questions, particularly in protein structure prediction and molecular dynamics analysis. Kabir holds a PhD and MS in Computer Science from GMU and a BS in Computer Science and Engineering from the Military Institute of Science and Technology (MIST), Bangladesh. Education: PhD in Computer Science, George Mason University MS in Computer Science, George Mason University BS in Computer Science and Engineering, MIST, Bangladesh Research Interests: His work bridges computational methods and biological systems, emphasizing machine learning applications in bioinformatics. Key areas include protein structure quality estimation, molecular energy landscape analysis, and antibody dynamics modeling. He also explores quaternion-based methods in pedestrian path analysis and graph theory for structure prediction. Publications: His recent work highlights advancements in non-negative matrix factorization, tensor factorization, and unsupervised learning for molecular structure analysis. Notable themes include protein decoy selection, antibody-antigen interaction dynamics, and integrative approaches combining energy landscapes with Markov state models. Professional Experience: Assistant Professor, Stevens Institute of Technology (prior to GMU) Research Fellow, LANL Labs/Teams: While specific lab affiliations are not detailed, his research aligns with computational biology and data science initiatives at GMU’s College of Science.

• Geometry
• Topology
• Low Dimensional Topology
• +۴ مورد دیگر

Feng Luo is a Professor of Mathematics at Rutgers, The State University of New Jersey, affiliated with the Department of Mathematics within the School of Arts and Sciences. His research focuses on geometry, topology, and their computational applications, including low-dimensional topology, geometric structures on manifolds, and discrete conformal geometry. His academic contributions span theoretical work on hyperbolic 3-manifolds, Ricci flow applications in network analysis, and geometric modeling. He has developed computational methods for conformal geometry with applications in vision and data science. His work integrates mathematical rigor with interdisciplinary challenges in neuroscience and engineering. Key research areas include discrete conformal geometry, optimal transportation maps, and geometric variational principles. His studies on neural mechanisms in Parkinson’s disease and auditory processing highlight interdisciplinary collaborations.

Lionel Bombrunمشاهده پروفایل

دانشیار

• Signal Processing
• Image Processing
• Remote Sensing
• +۵ مورد دیگر

Lionel Bombrun is an Associate Professor at the University of Bordeaux, specializing in Signal and Image Processing within the MOTIVE team at IMS Bordeaux. His research focuses on the application of Riemannian geometry to texture analysis, remote sensing, and machine learning problems. His educational background includes advanced studies in signal processing and mathematics, though specific degrees aren't detailed in the provided text. His research interests span multiple domains including: Statistical modeling on Riemannian manifolds Covariance matrix analysis for texture classification Wavelet-based feature extraction Remote sensing applications for environmental monitoring Machine learning approaches for hyperspectral and radar data Bombrun's publication record shows consistent contributions to high-impact journals, particularly in IEEE Transactions. His recent work demonstrates growing interest in applying conformal prediction and deep learning techniques to aviation safety and precision agriculture. The publications reveal a strong pattern of interdisciplinary collaboration across mathematics, engineering, and environmental science domains. Among his notable scientific contributions is the development of Riemannian statistical models for covariance matrix descriptors, which has become influential in texture analysis and remote sensing classification tasks. Professor Bombrun actively collaborates with researchers across multiple institutions and industries, particularly in applications related to vineyard monitoring, forest management, and aircraft navigation systems. His work demonstrates both theoretical depth in mathematical statistics and practical applications in real-world problems.

Pascal Weisenburgerمشاهده پروفایل

پژوهشگر

• Programming Languages
• Multitier Programming
• Tierless Programming
• +۱۲ مورد دیگر

Pascal Weisenburger is a researcher at the School of Computer Science , University of St. Gallen. His work focuses on programming languages for distributed systems , emphasizing multitier programming, reactive paradigms, and type-driven placement reasoning. Research Themes : Multitier programming languages, CRDTs, dynamic placement type systems, reactive microservices, compiler correctness, and domain-specific scheduling. Recent Articles : Explored E-graphs for disequality reasoning (POPL 2025), array type duality in functional languages (ECOOP 2024), and formal verification of CRDTs (PLDI 2023). Committee Roles : Participated in program/steering committees for ECOOP, SPLASH, APLAS, and IEEE BigData conferences. Key Contributions : Developed the ScalaLoci language for multitier systems, proposed Propel for algebraic property verification, and introduced Dyno for static reasoning in dynamic placement scenarios.

Yinon Spinkaمشاهده پروفایل

مدرس ارشد

• Probability Theory
• Statistical Mechanics
• Ergodic Theory
• +۳ مورد دیگر

Dr. Yinon Spinka is a Senior Lecturer in the Department of Theoretical Mathematics at Tel Aviv University's School of Mathematics Sciences, where he has been employed since 2021. His research focuses on probability theory and its connections to statistical mechanics, ergodic theory, and combinatorics. Dr. Spinka completed all his academic training at Tel Aviv University: B.Sc. in Mathematics and Physics (2010), M.Sc. in Mathematics (2013), and Ph.D. in Mathematics (2018). His research explores phase transitions in discrete systems, finitary codings for Markov random fields, and the behavior of loop models at criticality. Spinka has developed novel techniques for analyzing stochastic domination, finitary factors, and spatial mixing properties across various probabilistic models. His work often bridges combinatorics, probability theory, and mathematical physics, with particular emphasis on lattice models and their phase transitions. A significant portion of his research investigates the relationship between different probabilistic notions and graph properties, especially amenability. Dr. Spinka's publication record shows consistent output in top journals including Inventiones Mathematicae, Annals of Probability, and Journal of the European Mathematical Society. His work demonstrates increasing sophistication in connecting different areas of probability theory, with recent papers showing strong integration of techniques from statistical mechanics, combinatorics, and ergodic theory. His research on finitary codings has established important connections between spatial mixing conditions and factor properties of random fields. Alix De Rothschild Scholarship in Science and Technology (2015) Israel Academy of Sciences and Humanities Adams Fellowship (2015) Israeli Mathematical Union Haim Nessyahu Prize (2020) Bernoulli Society Wolfgang Doeblin Prize (2022) Dr. Spinka has established a robust collaborative network with leading researchers including Ron Peled, Gourab Ray, Omer Angel, and Hugo Duminil-Copin. His research has been supported through prestigious fellowships including the Adams Fellowship. While specific grant details aren't provided in the source material, his publication record in top journals suggests sustained research funding. His work contributes significantly to Tel Aviv University's strong reputation in probability theory and mathematical physics. Dr. Spinka's research contributes to several active areas within the Department of Theoretical Mathematics, particularly in probability theory and its applications to statistical mechanics. His work connects with broader research efforts in mathematical physics and combinatorics, advancing fundamental understanding of phase transitions and critical phenomena in discrete systems.

Dapeng Zhanمشاهده پروفایل

استاد

• Probability Theory
• Schramm-Loewner evolution (SLE)
• Statistical Lattice Models
• +۳ مورد دیگر

Dapeng Zhan is a Professor in the Department of Mathematics at Michigan State University (MSU), where he has held this position since 2017. He earned his Ph.D. in Mathematics from the California Institute of Technology in 2004. His research focuses on Schramm-Loewner evolution (SLE), a stochastic process describing random fractal curves in two-dimensional spaces, with applications to critical phenomena in statistical physics models like percolation and the Ising model. Zhan has held prior academic positions, including Gibbs Assistant Professor at Yale University (2007–2009) and Morrey Assistant Professor at UC Berkeley (2004–2007). His research interests include Probability Theory, SLE, and statistical lattice models. He has received prestigious awards such as the Salem Prize (2012), Sloan Research Fellowship (2011–2015), and Simons Fellowship (2016). His work frequently appears in top journals like *Annals of Probability* and *Inventiones Mathematicae*. Zhan teaches advanced courses in probability and analysis, including *Brownian Motion and Stochastic Analysis* and *Analysis I*. He has advised numerous research projects and holds grants from the NSF, including a CAREER award (2011–2018). His contributions span theoretical developments in SLE's reversibility, duality, and boundary behavior, with recent work exploring multi-force-point SLE and boundary Green’s functions.

Malcolm Perryمشاهده پروفایل

استاد

• Black Hole Physics
• Quantum Gravity
• String Theory
• +۴ مورد دیگر

Malcolm Perry is a Professor of Theoretical Physics at Queen Mary University of London, previously holding a professorship at the University of Cambridge's Department of Applied Mathematics and Theoretical Physics. He is a Fellow of Trinity College, Cambridge, and a member of the Centre for Fundamental Physics and the Relativity and Gravitation research group. His research focuses on black hole physics, quantum gravity, string theory, and cosmology. Perry's work includes the Myers-Perry metric (with Robert Myers) and significant contributions to resolving the black hole information paradox with Stephen Hawking and Andrew Strominger. He has received awards from the Gravity Research Foundation and the Sloan Research Fellowship. Education: King Edward’s School, Birmingham Bachelor's in Physics, St John’s College, Oxford PhD in Theoretical Physics (supervised by Stephen Hawking), King’s College, Cambridge Research Interests: Perry advances understanding of black hole thermodynamics, gravitational waves, and the interplay between quantum mechanics and general relativity. His work spans Euclidean quantum gravity, soft hair conjectures, and higher-dimensional spacetime models in string theory. Grants & Collaborations: Perry co-leads the Amplitudes, Strings and Duality grants (STFC-funded), collaborating with experts like Andreas Brandhuber and David Berman. These projects explore string theory and gauge/gravity dualities. Awards: Gravity Research Foundation Award Sloan Research Fellowship Labs/Teams: Perry contributes to Queen Mary's Centre for Fundamental Physics and the Relativity and Gravitation group, advancing interdisciplinary research in theoretical physics.

Tarek Anousمشاهده پروفایل

مدرس ارشد

• Quantum Field Theory
• Theoretical Physics
• Holographic Dualities
• +۴ مورد دیگر

Tarek Anous is a Senior Lecturer in Mathematical Sciences at Queen Mary University of London (UKRI Future Leaders Fellow). He holds a position within the School of Mathematical Sciences, focusing on theoretical physics research with strong ties to quantum gravity and holography. His work explores de Sitter space cosmology, black hole physics, and string theory applications. Anous' research group investigates topics such as quantum field theory in expanding spacetimes, holographic dualities (e.g., AdS/CFT), and the interplay between quantum mechanics and gravitational systems. Education details are not explicitly stated in the provided texts, but his academic trajectory is evident through his publications and research focus. His research interests include exact solvable models in de Sitter backgrounds, low-dimensional gravity models, and disordered systems mimicking black hole behavior. Notable collaborations include work with Dionysios Anninos on topics like discrete series representations and rotating black hole horizons. His advising includes PhD student Johnny Brendan Gleeson. Anous' work has been supported through fellowships and grants, though specific funding bodies are not listed. He maintains an active research group with current and past members engaged in cutting-edge theoretical physics projects. His webpage tarek-ano.us provides further details on ongoing research and collaboration opportunities. Key research trends from his articles include advancements in de Sitter quantum field theory (e.g., Schwinger model analysis), exploration of black hole phase transitions (rotating horizons), and development of holographic models for glassy systems. He frequently employs techniques from conformal field theory, string theory, and quantum mechanics to address foundational questions in gravitational physics.

Jim Halversonمشاهده پروفایل

دانشیار

• String Theory
• Particle Physics
• Cosmology
• +۲ مورد دیگر

Jim Halverson is an Associate Professor of Physics at Northeastern University in Boston, Massachusetts. His research bridges string theory , particle physics , cosmology , mathematical geometry , and deep learning . He serves as a co-PI and Board Member of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) and co-organizes Physics ∩ ML . Halverson holds a PhD in Physics from the University of Pennsylvania (2012) and completed postdoctoral work at the Kavli Institute for Theoretical Physics (2012-2015). His research focuses on the string landscape and its implications for physics beyond the Standard Model, particularly through the lens of extra-dimensional geometries . He has pioneered the integration of deep learning into theoretical physics, applying it to problems in quantum field theory , knot theory , and cosmological model inference . Halverson has organized numerous workshops, including String Phenomenology and IAIFI Summer Schools , and serves on the editorial board of Machine Learning: Science and Technology . Halverson’s recent publications highlight neural network applications to conformal symmetry , Kolmogorov-Arnold networks , and geometric problems in string theory . His work intersects physics , mathematics , and machine learning to explore fundamental questions in cosmology and quantum gravity. He has received the NSF CAREER Grant and DOE Graduate Fellowship , underscoring his contributions to both research and education. Halverson teaches graduate courses in quantum mechanics and quantum field theory at Northeastern University.

Geoffrey Grimmettمشاهده پروفایل

استاد

• Probability Theory
• Combinatorial Theory
• Stochastic Models in Statistical Physics
• +۳ مورد دیگر

Geoffrey Grimmett is Professor of Mathematical Statistics at the University of Cambridge, affiliated with the Faculty of Mathematics and the Statistical Laboratory. His research focuses on probability theory, combinatorial theory, stochastic models in statistical physics, and probabilistic number theory. He has contributed extensively to percolation theory, self-avoiding walks, and lattice models, with notable collaborations on hyperbolic site percolation and critical probabilities of lattice-pairs. His work bridges theoretical mathematics with applications in statistical physics and combinatorics. Education and Background: No explicit educational details provided in the text, but his role as a professor implies advanced degrees in mathematical statistics or related fields. Research Interests: His primary areas include probability theory, with a focus on percolation, stochastic processes, and applications in statistical physics. Recent work involves hyperbolic percolation models, connective constants of graphs, and alignment percolation. He also explores intersections with combinatorics and quantum systems, such as entanglement entropy in the quantum Ising model. Publications Trends: Over 20 articles listed, emphasizing percolation theory (e.g., hyperbolic site percolation, critical probabilities), combinatorial problems (self-avoiding walks, cubic graphs), and applications in physics (quantum spin systems, epidemic models). His work often combines rigorous mathematical analysis with interdisciplinary applications. Awards: None explicitly listed in the provided text, though his contributions to probability theory are widely recognized in academic circles. Grants and Labs: No specific grants or lab affiliations mentioned, but his position suggests involvement in Cambridge’s research initiatives. Collaborators include Z Li (frequent co-author) and researchers in statistical mechanics.