جست‌وجوی استاد و پژوهشگر

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.

Otis Chodoshمشاهده پروفایل

دانشیار

• Geometric Analysis
• Partial Differential Equations (PDE)
• Differential Geometry
• +۴ مورد دیگر

Otis Chodosh is an Associate Professor of Mathematics at Stanford University, affiliated with the School of Humanities & Sciences. His research focuses on geometric analysis and partial differential equations, particularly in areas involving minimal surfaces, scalar curvature, and mean curvature flow. Chodosh earned his PhD from Stanford (2015), Master of Advanced Studies in Mathematics from the University of Cambridge (2011), and undergraduate degree in Mathematics and Physics from Stanford (2010). He previously held positions at Princeton University and the Institute for Advanced Study as a Veblen Research Instructor (2016–2019). His notable awards include the 3-year Terman Fellowship (2023) from Stanford’s Dean of Natural Sciences, the prestigious Walter J. Gores Award for Excellence in Teaching (2015), and the Gates Scholarship for studies at Cambridge (2010). Chodosh actively organizes the department’s Geometry Seminar and has advised students like Yujie Wu. Research interests span geometric analysis, PDEs, and applications to relativity. Key contributions include studies on minimal surfaces’ Morse index, scalar curvature obstructions, and mean curvature flow dynamics. Recent work explores scalar curvature’s role in manifold topology, geometric flows with singularities, and stability of hypersurfaces in high dimensions. Publications reflect a focus on geometric PDEs, including work on Minkowski inequalities, liquid drop models, and topological constraints from curvature conditions. His research frequently intersects with geometric measure theory and functional inequalities. Chodosh’s work bridges theoretical analysis with geometric intuition, addressing fundamental questions in differential geometry and mathematical physics through advanced analytical techniques.

Xiaoming Maoمشاهده پروفایل

استاد

• Soft Condensed Matter
• Materials Physics
• Statistical Mechanics
• +۳ مورد دیگر

Xiaoming Mao is a Professor in the Department of Physics at the University of Michigan . Her research focuses on soft condensed matter , materials physics , and statistical mechanics , particularly in the areas of topological mechanics and self-assembly . Education: PhD (2008), MS (2004) from University of Illinois at Urbana-Champaign; BS (2002) from Peking University, China. Her work explores soft elasticity through the lens of isostaticity —the balance between degrees of freedom and constraints in materials. This includes studying jammed solids, glasses, and biopolymer gels. She also investigates self-assembly mechanisms, focusing on entropic effects in colloidal open structures and nanoparticle systems. Recent research trends span topological mechanics (e.g., Maxwell lattices, floppy modes), nanoscale self-assembly , and mechanical metamaterials . Publications highlight topological edge modes , nonlinear elasticity , and stress-controlled fracturing . Professor Mao’s group engages in interdisciplinary collaborations , integrating biological physics (cell mechano-sensing, tissue dynamics) with materials engineering . Openings for postdoctoral researchers and graduate students emphasize projects in topological mechanics and active matter .

Zeev Dvirمشاهده پروفایل

استاد

• Theoretical Computer Science
• Discrete Mathematics
• Computational Complexity
• +۳ مورد دیگر

Zeev Dvir is a Professor jointly appointed in the Department of Computer Science and the Department of Mathematics at Princeton University. His research interests span theoretical computer science, discrete mathematics, and their intersections with algebra and combinatorics. He focuses on computational complexity, pseudo-randomness, coding theory, and combinatorial geometry. Notable contributions include work on the Kakeya conjecture in finite fields, incidence theorems, and applications to coding theory. He has published extensively in top venues such as computational complexity conferences and journals. His work has been highlighted in Quanta Magazine for its impact on geometric problems. Zeev Dvir holds grants from the National Science Foundation (NSF), including awards for research on dimension expanders and line-point incidence problems. His research also intersects with areas like matrix rigidity and data structure lower bounds. He maintains an active research program and collaborates on foundational questions in theoretical computer science and mathematics. His homepage hosts surveys on incidence theorems and their applications, reflecting his commitment to bridging algebraic methods with discrete geometry. He is a prominent figure in the Princeton academic community, contributing to both departments through teaching and interdisciplinary research.

Thomas Beckersمشاهده پروفایل

استادیار

• Control Systems
• Machine Learning
• Robotics
• +۶ مورد دیگر

Thomas Beckers is an Assistant Professor of Computer Science at Vanderbilt University's School of Engineering, joining in January 2023. He holds a Ph.D. in Electrical Engineering from the Technical University of Munich (2020), and B.Sc./M.Sc. degrees from Technical University of Braunschweig (2010/2013). His research bridges machine learning and control theory to develop safe, robust algorithms for complex systems like autonomous vehicles and soft robotics. He is a DAAD AInet Fellow and recipient of the Rhode & Schwarz Outstanding Dissertation Award. His work focuses on physics-enhanced learning and safe control strategies, leveraging Bayesian methods and port-Hamiltonian systems. Recent projects include developing uncertainty-aware control frameworks and Python tools like PyGpPHs for modeling physical systems. He advises students Peilun Li and Kaiyuan Tan, and has organized workshops at major conferences such as ACC and CDC. His lab explores topics ranging from PDE system identification to geometric control of aerial robots. Notable achievements include organizing large-scale workshops (e.g., 2023 CDC workshop with 80+ participants) and securing RAMP awards for data-driven control research. His publications emphasize safety, interpretability, and integration of physical priors into machine learning models.

Xiangwen Zhangمشاهده پروفایل

استاد

• Geometric Analysis
• Partial Differential Equations
• Differential Geometry
• +۳ مورد دیگر

Xiangwen Zhang is a Professor in the Department of Mathematics at the University of California, Irvine. His research focuses on geometric analysis and partial differential equations, particularly exploring geometric flows, complex geometry, and mathematical physics. He has contributed to the study of Hessian equations, Strominger systems, and string theory-related geometric structures. Dr. Zhang’s work bridges differential geometry and nonlinear PDEs, with significant contributions to the understanding of curvature flows, conformally balanced metrics, and geometric inequalities. His research often involves advanced techniques from complex geometry and geometric analysis, addressing questions in both pure and applied mathematical contexts. His academic activities include teaching courses like Math 2D (Multivariable Calculus) and maintaining active participation in seminars such as the Analysis Seminar and Differential Geometry Seminar. He collaborates widely, evidenced by co-authorships with researchers like T. Fei, D.H. Phong, and S. Picard. His research has been published in leading journals such as the Journal of Differential Geometry and Inventiones Mathematicae. Zhang’s expertise also extends to geometric inequalities and spacetime geometry, as seen in his work on Minkowski formulae and Alexandrov theorems. His research program reflects a deep engagement with the interplay between geometry, analysis, and theoretical physics.

Hongkai Zhaoمشاهده پروفایل

استاد

• Applied and Computational Mathematics
• Inverse Problems
• Imaging
• +۴ مورد دیگر

Professor Hongkai Zhao is a Chancellor’s Professor and Chair of the Mathematics Department at the University of California, Irvine (UCI), with a joint appointment in Computer Science. He holds a B.S. from Peking University, M.S. from USC, and Ph.D. from UCLA, all in Mathematics. His research focuses on computational and applied mathematics, including moving interface problems, inverse problems, imaging, and Hamilton-Jacobi equations. He is renowned for developing the Fast Sweeping Method (FSM) for solving hyperbolic PDEs efficiently. Education: B.S. (Peking University, 1990), M.S. (USC, 1992), Ph.D. (UCLA, 1996). Employment: UCI faculty since 1999, Szego Assistant Professor at Stanford (1996–1999). Research interests span computational fluid dynamics (moving interfaces), inverse problems (tomography, wave propagation), and imaging (medical imaging, computer vision). Key contributions include numerical methods for surfactant-laden drops, fast algorithms for Hamilton-Jacobi equations, and 4D cone-beam CT reconstruction. Awards include the Feng Kang Prize (2007), Sloan Fellowship (2002–2004), and Chancellor’s Professorship (2016–present). He has authored over 100 publications on numerical methods, inverse problems, and PDEs. Lab affiliations: Active in interdisciplinary research at UCI, leading projects in computational mathematics and imaging science. Current work includes high-frequency wave propagation, multi-scale modeling, and geometric data analysis.

Arash Yazdanbakhshمشاهده پروفایل

عضو هیئت علمی

• Computational Neuroscience
• Visual Perception
• Human Electrophysiology
• +۳ مورد دیگر

Arash Yazdanbakhsh is a Research Assistant Professor and Director of the Computational Neuroscience & Vision Lab in Boston University's Department of Psychological & Brain Sciences. He earned an M.D. from Tehran Medical University, a Ph.D. from Boston University, and completed postdoctoral research in Neurobiology at Harvard Medical School. Research focuses on human vision modeling, electrophysiology, and psychophysics, with specific projects examining cortical mechanisms of figure-ground segregation, motion integration via multiscale sampling, and spatio-temporal dynamics of neural receptive fields. Work bridges computational neuroscience with clinical applications in schizophrenia and autism research. Recent publications (2020-2024) demonstrate strong emphasis on neural modeling of visual and cognitive processes, with methodological innovations in machine learning applications to neuropathology. Dominant themes include: schizophrenia neural circuitry (33%), autism perception studies (27%), sleep neurophysiology (13%), and fundamental vision mechanisms (27%). Article keywords frequently involve computational psychiatry, thalamocortical circuits, and deep learning approaches.

Adrian Ioanaمشاهده پروفایل

استاد

• Operator Algebras
• Functional Analysis
• Ergodic Theory
• +۴ مورد دیگر

Adrian Ioana is a Professor in the Department of Mathematics at the University of California, San Diego (UCSD). He holds a Ph.D. from UCLA (2007) under Sorin Popa and has held prestigious fellowships including the Clay Research Fellowship (2008–2011) and Alfred P. Sloan Research Fellowship (2014). His research focuses on operator algebras, ergodic theory, and group theory, with expertise in von Neumann algebras and their classification. He has organized major conferences such as the 2024 Banff Workshop on Group Operator Algebras and co-edits journals like Journal of Operator Theory and Journal of Group Theory . Research interests include von Neumann algebras, ergodic theory (orbit equivalence), group stability, and logic (descriptive set theory). Notable achievements include rigidity results for group von Neumann algebras and contributions to the classification of II₁ factors. Awards include the European Math Society Prize and being an invited speaker at the 2018 International Congress of Mathematicians. Recent work explores wreath-like group products, non-isomorphism in von Neumann algebras, and asymptotic freeness in ultraproducts. He actively teaches graduate courses and mentors students in functional analysis and related fields.

Marta Lewickaمشاهده پروفایل

استاد

• Nonlinear Analysis
• Partial Differential Equations
• Calculus of Variations
• +۴ مورد دیگر

Marta Lewicka is a Professor of Mathematics at the University of Pittsburgh, affiliated with the Dietrich School of Arts and Sciences. Her research focuses on nonlinear analysis, partial differential equations (PDEs), and calculus of variations, with applications to elasticity, geometric analysis, and game theory. She holds a PhD from SISSA, Italy, and has authored influential works such as A Course on Tug-of-War Games with Random Noise and Calculus of Variations on Thin Prestressed Films . Key awards include the 2021 AMS Fellowship and NSF award DMS-2006439. Her work bridges theoretical mathematics and applied fields, addressing geometric problems in elasticity, dimension reduction of thin films, and convex integration techniques for PDEs. She has organized international workshops and serves on editorial boards of journals like SIAM Journal of Mathematical Analysis. Teaching includes advanced courses on calculus of variations, real analysis, and partial differential equations. Her research also explores connections between stochastic processes (e.g., tug-of-war games) and PDEs, contributing to both pure and applied mathematical frameworks.

Nicholas Edelenمشاهده پروفایل

استادیار

• Differential Geometry
• Geometric Analysis
• Geometric Measure Theory
• +۲ مورد دیگر

Nicholas Edelen is an Assistant Professor in the Department of Mathematics at the University of Notre Dame, College of Science. His research specializes in geometric analysis and geometric measure theory, focusing on minimal surfaces, mean curvature flow, and singularity analysis. He is affiliated with the Analysis and Partial Differential Equations and Differential Geometry research groups. Education: Ph.D., Stanford University, 2016 BSc, University of Edinburgh, 2012 Research Interests: Dr. Edelen studies problems related to the regularity of minimal surfaces (mathematical models of soap films) and their behavior near singularities. His work connects differential geometry, PDEs, and geometric measure theory to analyze structural properties of singular sets in high-dimensional spaces. Publications: His recent articles predominantly explore minimal surfaces, capillary boundary conditions, and regularity theory, with frequent collaborations addressing both theoretical foundations and applied geometric analysis. Common themes include singularity formation, free boundary problems, and geometric evolution equations. Awards: NSF Fellowship He currently leads the Graduate Differential Geometry course and co-organizes the Geometry and Analysis seminar. His research is supported by NSF grant DMS-2204301. Past teaching includes undergraduate real analysis, calculus, and geometric measure theory. Dr. Edelen collaborates with international researchers and contributes to interdisciplinary teams focusing on PDE-driven geometric phenomena.

• Noncommutative Geometry
• Operator Algebras
• Index Theory
• +۳ مورد دیگر

Guoliang Yu holds the Powell Chair in Mathematics and the rank of Professor at Texas A&M University's Department of Mathematics within the College of Arts & Sciences. His research focuses on noncommutative geometry, operator algebras, and geometric topology with applications to index theory, coarse geometry, and K-theory. He has contributed extensively to the Novikov conjecture and coarse Baum-Connes conjecture through studies of scalar curvature, geometric invariants, and operator K-theory. Key research themes include quantitative K-theory, geometric analysis on manifolds, and the interplay between algebraic topology and geometric group theory. His work explores scalar curvature rigidity, coarse embeddability of groups, and applications to topological rigidity problems. Yu's recent studies address FCE-by-FCE structures, Milnor exact sequences in KK-theory, and dynamic complexity in operator algebras. Publications from 2023-2025 highlight advancements in controlled operator K-theory, geometric inequalities, and universal coefficient theorems for C*-algebras. These contributions bridge functional analysis with geometric problems, particularly in contexts involving large-scale geometry and metric spaces.

John Keyserمشاهده پروفایل

استاد

• Computer Science
• Graphics and visualization
• Physically-based simulation
• +۵ مورد دیگر

John Keyser is a Professor in the Department of Computer Science & Engineering at Texas A&M University, serving as Graduate Advisor. He holds a Ph.D. from the University of North Carolina at Chapel Hill and multiple B.S. degrees from Abilene Christian University. His research focuses on geometric computing, physically-based simulation, graphics, and modeling, with notable contributions to 3D visualization and computational geometry. Keyser's educational background includes advanced degrees in Computer Science, Applied Mathematics, and Engineering Physics. He has received prestigious awards such as the William Keeler Faculty Fellowship and teaching accolades from the Association of Former Students and Tenneco. His research interests span robust geometric modeling, physically-based simulation, brain networks, and graphics. Keyser's work bridges theoretical foundations with applied systems, including innovations in particle-based fluids, mesh rendering, and filament tracking in microscopy. Awards: William Keeler Faculty Fellow (2009-2010), Teaching Excellence Awards (2007), Montague Scholar (2003-2004). Advising: Graduate Advisor role with expertise in guiding students through complex computational projects. Keyser collaborates on advanced imaging techniques like the Knife-Edge Scanning Microscope (KESM) for brain tissue analysis and contributes to GPU-accelerated algorithms for real-time simulations. His research trends emphasize interdisciplinary applications of geometric computing in both academic and industrial contexts.

Jacob Bourjailyمشاهده پروفایل

استاد

• Particle Physics
• Quantum Field Theory
• Theoretical Physics
• +۳ مورد دیگر

Jacob Bourjaily is a Professor of Physics at the Pennsylvania State University (Penn State) and maintains an affiliation with the Niels Bohr International Academy of the University of Copenhagen. His research focuses on theoretical physics, particularly particle physics and quantum field theory, with emphasis on scattering amplitudes, supersymmetric Yang-Mills theory, and mathematical methods in high-energy physics. Education: PhD in Physics, Princeton University (2011) Master of Advanced Study (MaSt) in Mathematics, University of Cambridge (2006) BS in Physics and Mathematics, University of Michigan (2005) Research Interests: Bourjaily explores advanced theoretical frameworks to understand particle interactions, including the geometry of scattering amplitudes, loop integrands, and the interplay between gauge theories and gravity. His work integrates algebraic geometry, elliptic functions, and computational tools to address challenges in perturbative quantum field theory. Grants & Awards: European Research Council Starting Grant (€1.5M, 2018) Villum Foundation Young Investigator Award (2017) Harvard Society of Fellows Membership (2011–2014) Research Group: Bourjaily collaborates with postdoctoral researchers and students on topics like elliptic amplitudes, Calabi-Yau geometries, and non-planar contributions. Current advisees include PhD students at Penn State and Copenhagen. Labs & Teams: He contributes to international projects such as the FalconD collaboration for high-field magnets and maintains ties with the Niels Bohr Institute’s theoretical physics group.

Juan Rivera-Letelierمشاهده پروفایل

استاد

• Dynamical Systems
• Number Theory
• Ergodic Theory
• +۳ مورد دیگر

Juan Rivera-Letelier is a Professor of Mathematics at the University of Rochester's School of Arts & Sciences. He holds a Doctorat en Mathématiques Pures (equivalent to a PhD) from Université de Paris Sud, obtained in 2000. His research focuses on dynamical systems, number theory, and ergodic theory, with particular emphasis on non-Archimedean dynamics, statistical properties of maps, and applications to arithmetic geometry. He has authored numerous influential papers on topics such as Fatou components, Gibbs states, and p-adic distributions of algebraic points. His recent work explores phase transitions in intermittent maps, sensitive dependence in geometric Gibbs states, and equidistribution of CM points in toric varieties. He has contributed to foundational results in ultrametric dynamics, including studies on wildly ramified power series and residue fixed point indices. Rivera-Letelier’s research bridges complex dynamics, real analysis, and number theory, often employing techniques from thermodynamic formalism and non-uniform hyperbolicity. His work has implications for understanding the interplay between arithmetic structures and dynamical systems, with applications to Diophantine geometry and statistical mechanics.