جست‌وجوی استاد و پژوهشگر

• Applied Topology
• Dynamical Systems
• Algebraic Topology
• +۵ مورد دیگر

Robert Ghrist is the Andrea Mitchell University Professor at the University of Pennsylvania with dual appointments in the Department of Mathematics and the Department of Electrical and Systems Engineering. He serves as Associate Dean for Undergraduate Education for Penn Engineering. His educational background includes a B.S. in Mechanical Engineering from the University of Toledo (1991), and M.S. and Ph.D. degrees in Applied Mathematics from Cornell University (1994, 1995). Ghrist's research bridges pure and applied mathematics, focusing on applied algebraic topology , dynamical systems , and geometric methods in data science. His work extends to network theory, topological data analysis, and computational geometry, with applications spanning robotics, neuroscience, and social dynamics. Key innovations include developing sheaf-theoretic approaches for networked systems and persistence homology techniques for high-dimensional data. Analysis of his recent publications reveals a strong emphasis on lattice-theoretic frameworks , topological robotics , and network dynamics , with emerging applications in neural data interpretation and geometric computing. His research consistently integrates category theory with real-world engineering challenges. Significant scientific recognition includes: Presidential Early Career Award (PECASE, 2004) Scientific American 'Top 50' Research Leader (2007) Mathematical Association of America's Chauvenet Prize (2013) University of Pennsylvania Lindback Award for Distinguished Teaching (2015) DoD National Security Science and Engineering Faculty Fellowship (NSSEFF, 2015) Ghrist leads multiple federally funded research initiatives supported by AFOSR, DARPA, NSF, and ONR. He directs the development of educational tools including the Calculus BLUE/GREEN Project video series and custom GPTs for mathematical pedagogy. His open online courses have reached over 100,000 learners globally.

Smirnov Stanislavمشاهده پروفایل

استاد

• Mathematical Physics
• Probability
• Complex Analysis
• +۳ مورد دیگر

Stanislav Smirnov is a Professor at the University of Geneva's Department of Mathematics since 2003 and Head of the Chebyshev Laboratory at St. Petersburg State University since 2010. He holds a Ph.D. from the California Institute of Technology (1996) and a B.Sc./M.Sc. from St. Petersburg State University (1992). His research focuses on mathematical physics, probability, complex analysis, and dynamical systems, with groundbreaking contributions to the understanding of critical phenomena in statistical physics. Key achievements include receiving the Fields Medal (2010), the highest honor in mathematics, for his work on percolation and the Ising model. He has organized major international conferences, such as the 'St. Petersburg School in Probability & Statistical Physics' (2012) and the '2D Statistical Physics Workshop' (2013). His academic career includes positions at Yale University, the Max-Planck Institute, and KTH Royal Institute of Technology. Education: Ph.D., Mathematics, California Institute of Technology (1996) B.Sc./M.Sc., Mathematics (with honors), St. Petersburg State University (1992) Awards: Fields Medal (2010) European Research Council Advanced Grants (2008, 2013) Rollo Davidson Prize (2002) Salem Prize (2001) Smirnov’s research bridges probability theory and complex analysis, with notable results on conformal invariance in two-dimensional models. His work has advanced understanding of critical exponents, percolation thresholds, and the universality of phase transitions. He advises doctoral students and collaborates internationally on projects funded by Swiss and European grants. He co-organized over 20 conferences worldwide, including plenary talks at the International Congress of Mathematicians (2006, 2010) and the World Congress in Probability and Statistics (2012). His lab fosters interdisciplinary research, linking mathematics to physics and computer science.

• General Relativity
• Theoretical Physics
• Black Hole Mechanics
• +۶ مورد دیگر

Harvey Reall is a Professor of Theoretical Physics at the University of Cambridge , affiliated with the Department of Applied Mathematics and Theoretical Physics (DAMTP) and a Fellow of Trinity College . His research focuses on General Relativity and Effective Field Theory , particularly in the context of black hole mechanics , higher-dimensional gravity , and cosmic censorship . He has held prestigious positions including a Royal Society University Research Fellowship from 2005 to 2013. Education: PhD from DAMTP, University of Cambridge. Previous Appointments: Lecturer at the University of Nottingham (2005-2007); Postdoctoral positions at the Kavli Institute (2003-2005), Queen Mary University of London (2000-2003), and University of California, Santa Barbara (2003-2005). Reall's work explores the uniqueness and stability of black holes , causality in gravitational theories , and effective field theory approaches to gravity . His recent publications address nonperturbative second law formulations , event horizon dynamics , and axisymmetry theorems in extended theories of gravity. He has supervised numerous researchers including Aidan McSharry (2025-) , Maxime Gadioux (2022-) , and Iain Davies (2020-24) , contributing to the training of the next generation of physicists. Scientific Awards: Royal Society University Research Fellow (2005-2013)

Jeffrey F. Brockمشاهده پروفایل

استاد

• Low-dimensional geometry
• Hyperbolic geometry
• Topology
• +۳ مورد دیگر

Jeffrey F. Brock is the Dean of the School of Engineering & Applied Science and the William S. Massey Professor of Mathematics at Yale University. He holds the Zhao and Ji Chair in Mathematics. His research focuses on low-dimensional geometry and topology, particularly hyperbolic geometry and its applications to data analysis. He completed his undergraduate studies at Yale and earned his Ph.D. from UC Berkeley. He held positions at Stanford, the University of Chicago, and Brown University, where he chaired the Mathematics Department from 2013 to 2017 and founded Brown’s Data Science Initiative in 2016. He joined Yale in 2018, serving as inaugural Dean of Science in the Faculty of Arts and Sciences until assuming his current role in 2022. He is a Guggenheim Fellow and Fellow of the American Mathematical Society. His research spans hyperbolic 3-manifolds, Teichmüller dynamics, and geometric methods in data science. Notable contributions include work on Thurston’s geometrization program, classification of hyperbolic manifolds, and applications of geometric topology to complex datasets. He co-authored foundational papers on ending laminations, Weil-Petersson geometry, and renormalized volume. His recent work bridges pure mathematics with applied challenges, such as algorithmic detection of medical imaging patterns. Awarded the Guggenheim Fellowship (2008) and AMS Fellow (2017), Brock has also led interdisciplinary initiatives at Brown and Yale. His administrative roles include overseeing engineering, natural sciences, and data science programs. Beyond academia, he co-founded the Vijay Iyer Trio, showcasing his passion for music performance and creativity.

Kai Xuمشاهده پروفایل

استادیار مهمان

• Geometric Analysis
• Calculus of Variations
• Metric Geometry
• +۴ مورد دیگر

Kai Xu is a Morrey Visiting Assistant Professor in the Mathematics department at the University of California, Berkeley, mentored by Richard Bamler. Appointed in 2025, he holds a PhD from Duke University supervised by Hubert Bray. His research addresses foundational problems at the intersection of differential geometry and analysis. His educational background includes: PhD in Mathematics, Duke University (2025), supervised by Hubert Bray Xu's research spans geometric analysis, calculus of variations, and metric geometry with concentrated focus on 3D scalar curvature geometry, weak inverse mean curvature flow, nonlinear potential theory (p-harmonic functions for $1 \leq p \leq \infty$), and spectral Ricci curvature bounds. His work systematically explores connections between curvature constraints, topological properties, and geometric flows through rigorous analytical methods. His publication record (2022-2025) reveals consistent advancement in scalar curvature theory, inverse mean curvature flow, and spectral Ricci geometry. Key contributions include spectral splitting theorems, drawstring constructions for scalar curvature constraints, and topological gap theorems for positive scalar curvature 3-manifolds. His collaborative work with leading mathematicians appears in journals including Duke Mathematical Journal and Calculus of Variations and Partial Differential Equations. No scientific awards are mentioned in the provided text. Teaching responsibilities include Math 104 in Fall 2025. Information regarding student advising and grant funding is not specified in available materials. No dedicated laboratory or research team structure is described in the source text.

Annina Iseliمشاهده پروفایل

مدرس

• Fractal Geometry
• Complex Dynamics
• Geometric Measure Theory
• +۳ مورد دیگر

Annina Iseli is a Lecturer in the Department of Mathematics at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the College of Basic Sciences. She holds dual roles as both a Scientist and Lecturer, contributing to research and teaching within the Institute of Mathematics (MATH-GE). Her work bridges pure and applied mathematics, focusing on geometric and analytical properties of fractals. University: École Polytechnique Fédérale de Lausanne (EPFL) School: College of Basic Sciences Department: Institute of Mathematics (MATH-GE) Role: Lecturer and Scientist Research interests span multiple areas in mathematics: Fractal geometry and its connections to complex dynamics Geometric measure theory applications to projections in normed spaces Conformal and quasiconformal geometry Analysis in metric spaces Her publications include work on projection theorems, fractal dimensions, and hyperbolic space properties. She co-organizes the Quasiworld Seminar and EPFL Geometry Seminar, collaborating with researchers like Mario Bonk, Nicolas Monod, and Zoltán Balogh. Contact: annina.iseli@epfl.ch

David Alvarez-Melisمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Optimal Transport
• +۴ مورد دیگر

David Alvarez-Melis is an Assistant Professor of Computer Science at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS). He leads the Data-Centric Machine Learning (DCML) group and holds affiliations with the Kempner Institute, Harvard Data Science Initiative, and the Center for Research on Computation and Society. His research focuses on making machine learning more data-efficient and trustworthy, with applications in natural and medical sciences. He also serves as a researcher at Microsoft Research New England. Affiliations: SEAS, Kempner Institute, Harvard Data Science Initiative, CRCS Education: PhD in Computer Science (MIT), MS in Mathematics (NYU Courant), BSc in Applied Mathematics (ITAM) Research Interests: Optimal Transport, dataset distillation, interpretable AI, medical imaging, robustness, and large language models. His work bridges theory and applications, emphasizing geometric and probabilistic methods. Recent Trends in Publications: Focused on advancing optimal transport for data manipulation, distributional deep equilibrium models, and repurposing LLMs for specialized domains. Key themes include synthetic dataset generation, gradient flows in probability spaces, and robust interpretability frameworks. Awards: Aramont Fellowship, Dean’s Competitive Fund, Top Reviewer awards at major conferences (ICLR, NeurIPS, ICML). Grants: Supported by the Aramont Fund and Harvard’s Dean’s Fund. His lab advises students across Harvard and MIT, with notable contributions to medical imaging, NLP, and foundational ML theory. He actively mentors interns and fosters collaborations with industry and academia.

• Popular Music Studies
• Hip-hop Culture
• Gender Studies
• +۳ مورد دیگر

Alyssa Woods is an Assistant Professor at the School of Fine Art and Music, University of Guelph. Her research focuses on popular music, particularly examining race, gender, and politics within hip-hop culture. She investigates how female artists like Beyoncé, Lily Allen, and Nicki Minaj reclaim discourse around the female body through parody and hyperbole in music videos, challenging hyper-masculine norms in hip-hop. Her work bridges cultural studies and music analysis, addressing contemporary trends in music video production and their sociopolitical implications. Contact: awoods08@uoguelph.ca , Office: Johnston Hall, Rm 113.

• Inverse Problems
• Partial Differential Equations
• Mathematical Physics
• +۳ مورد دیگر

Ali Feizmohammadi is an Assistant Professor, Teaching Stream (LTA) in the Department of Mathematics at the University of Toronto Mississauga, affiliated with the Mathematical and Computational Sciences division. His research focuses on inverse problems, partial differential equations, and geometric analysis. He holds a position emphasizing teaching excellence within the university's framework. His work addresses advanced mathematical challenges such as coefficient identification in subdiffusion equations, fractional Laplacian problems on Riemannian manifolds, and nonlinear elliptic equations on manifolds. Recent articles highlight contributions to the Calderón problem in various contexts, wave equation control, and spacetime finite element methods. No scientific awards or grants are explicitly listed in the provided information. He has not yet listed advisees in the available data. His research trends emphasize rigorous mathematical analysis of inverse problems in both classical and fractional PDE frameworks, with applications to geometric and control-theoretic questions. Dr. Feizmohammadi's work spans theoretical advancements in inverse problems, numerical methods for control systems, and the interplay between differential geometry and PDEs. His contributions address both fundamental theory and applied methodologies in mathematical physics and engineering.

• Numerical Mathematics
• Finite Element Analysis
• Optimal Control
• +۳ مورد دیگر

Richard Franz Löscher is a researcher at the Institute of Applied Mathematics specializing in numerical methods for optimal control problems. He holds a BSc, Diplom-Ingenieur (Dipl.-Ing.), and Doctorate in Technical Sciences (Dr.techn.), demonstrating extensive technical education and engineering expertise. His educational qualifications include: BSc Diploma in Engineering (Dipl.-Ing.) Doctorate in Technical Sciences (Dr.techn.) Löscher's research centers on numerical mathematics with deep specialization in finite element methodologies for distributed optimal control problems governed by partial differential equations. His work addresses elliptic, parabolic, and hyperbolic control systems through regularization techniques, adaptive mesh refinement, and robust solver development. Key innovations include variable energy regularization frameworks, mass-lumping discretizations, and complexity-optimal space-time finite element systems that significantly advance computational efficiency and error estimation in constrained control environments. Analysis of his 2024-2026 publications reveals a cohesive research trajectory focused on overcoming computational bottlenecks in optimal control. His work consistently bridges theoretical rigor with practical implementation, emphasizing discretization schemes that balance accuracy and computational cost while addressing state/control constraints across diverse PDE systems. No scientific awards or honors were documented in available sources. Löscher maintains active research collaborations with prominent figures including Ulrich Langer and Olaf Steinbach, evidenced by co-authored publications and peer-review activities for journals like Journal of Computational and Applied Mathematics. His external research engagement includes a July 2024 visit to Delft University of Technology, highlighting international academic partnerships.

John Evansمشاهده پروفایل

دانشیار

• Computational Mechanics
• Fluid Dynamics
• Fluid-Structure Interaction
• +۳ مورد دیگر

John Evans is an Associate Professor and Jack Rominger Faculty Fellow in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, affiliated with the Applied Mathematics program. He serves as Associate Chair for Undergraduate Curriculum and is part of the Aerospace Mechanics Research Center (AMREC). His research focuses on computational mechanics, particularly fluid dynamics, fluid-structure interaction, and turbulence modeling using high-order and structure-preserving methods. Evans holds a PhD (2011) and MS (2008) in Computational and Applied Mathematics from the University of Texas at Austin, and dual BS/MS degrees in Mathematics and Applied Mathematics from Rensselaer Polytechnic Institute (2006). Before joining CU Boulder, he was a postdoctoral fellow at the Institute for Computational Engineering and Sciences (ICES). His research interests include isogeometric analysis, immersed methods, and data-driven turbulence modeling. Notable contributions include development of divergence-conforming discretizations for incompressible flows, stabilized collocation methods, and invariant subgrid stress models. He leads the AMREC lab and collaborates on plasma-fueled propulsion systems and geometrically sensitive simulations. Key Awards: 2021: Rocky Mountain AIAA Educator of the Year 2021: Gallagher Young Investigator Medal 2019-2021: Clarivate Highly Cited Researcher Professional Activities: Editor of Engineering Computations, Senior AIAA Member, Simons Visiting Professor (2019) Evans' work bridges advanced numerical methods with real-world engineering challenges. His lab develops open-source tools like XIGA for multi-material problems and focuses on immersive simulation environments. Current projects explore turbulence closure models, plasma propulsion, and topology optimization with B-spline-based approaches.

• Geometric Topology
• Geometric Group Theory
• Low-Dimensional Topology
• +۶ مورد دیگر

Prof. Harry Hyungryul Baik is a Tenured Associate Professor at KAIST's Department of Mathematical Sciences since 2017. He holds a PhD from Cornell University (2014) and a B.S. from KAIST (2009), advised by William Thurston, John Hubbard, and Dylan Thurston. His research focuses on geometric topology, geometric group theory, and low-dimensional topology, with notable contributions to mapping class groups, Kleinian groups, and Teichmüller theory. Education: PhD in Mathematics (Cornell, 2014), B.S. in Mathematics (KAIST, 2009). Key research areas include asymptotic translation lengths, laminar groups, and circular orders of groups. He co-leads the KAIST-KIAS joint research group 2K-GATE as Director, emphasizing collaboration between topologists. Research highlights: Characterization of Fuchsian groups via laminations, unsmoothability of mapping class group actions on 1-manifolds, and exponential torsion growth in random 3-manifolds. His work bridges topology with dynamical systems and geometric group theory, often involving collaborations with institutions like KIAS and MPIM. Awards include the Sangsan Prize (2018), Young-KAST membership (2020–2023), and multiple grants from Samsung and POSCO. He advises 7 PhD students and has mentored 15+ alumni, many of whom hold postdoc positions globally. His lab actively hosts conferences like the KAIST Geometric Topology Fair. Labs/Teams: Director of 2K-GATE (KAIST-KIAS), core member of the KAIST Topology Research Group, collaborator with international networks including the Harvard-MIT-Princeton topology axis.

Ranjan Singhمشاهده پروفایل

استاد

• Terahertz (THz) Photonics
• Metamaterials
• 6G Communications
• +۶ مورد دیگر

Ranjan Singh is a Professor at the Division of Physics, Nanyang Technological University (NTU) Singapore, specializing in terahertz photonics and metamaterials. He holds an elected fellowship from OPTICA (OSA) for pioneering work in ultrafast terahertz photonics, active metamaterials, and sensors. His research focuses on hybrid THz-electronic-photonic technologies for 6G communications, topological photonics, spintronics, quantum materials, and high-Tc superconductors. Education: B.Eng. in Telecommunications (Bangalore University, 2001); M.Tech in Photonics (Cochin University, 2004); Ph.D. in Photonics (Oklahoma State University, 2009). Postdoctoral research at Los Alamos National Laboratory (2009–2013). Research emphasizes on-chip THz topological photonics for next-gen communication systems, with notable achievements including a $7M grant for TERACOMM (on-chip THz topological photonics). His work integrates AI-driven beamforming, reconfigurable metasurfaces, and phase-change materials for adaptive THz systems. Key awards include the 2020 Web of Science 'Top 1% Highly Cited Researcher' distinction. His lab, TeraX Labs (founded 2013), develops cutting-edge technologies like THz brain-computer interfaces, quantum emitters, and spintronic sensors. Over $12M in competitive grants has fueled innovations in THz integrated circuits, tunable optical coatings, and ultra-sensitive biosensors. Advancing 6G/XG wireless, Singh's team designs topological beamformers, intelligent reflecting surfaces (IRS), and terahertz metamaterials for multi-link systems. His work bridges theoretical physics and applied engineering, with a focus on energy-efficient, reconfigurable photonic systems.

Itsik Pe'erمشاهده پروفایل

استاد

• Human Genetics
• Computational Biology
• Genomics
• +۳ مورد دیگر

Itsik Pe'er is a Full Professor and Vice-Chair in the Department of Computer Science at Columbia University's Fu Foundation School of Engineering & Applied Science, and holds a joint appointment as Professor of Systems Biology at the Vagelos College of Physicians and Surgeons. His research focuses on computational methods in human genetics, including genetic variation analysis, disease association studies, and algorithm development for genomic data. He leads the Itsik Pe'er Lab of Computational Genomics, which develops tools like Xplorigin, Germline, and SEACells to address challenges in genomics and medical research. His work spans machine learning applications in healthcare, microbiome analysis, and cancer genomics. Notable contributions include studies on hypertensive disorders in pregnancy, bias correction in predictive models, and the development of non-Euclidean learning libraries like Manify. Pe'er has advised students including Vladimir Vacic, Anat Kreimer, and Arthi Ramachandran, and collaborates on grants addressing genetic epidemiology and computational biology. His lab's location is in the Computer Science Building at Columbia's Morningside Campus.

• Differential Geometry
• Riemannian Geometry
• Lie Groups
• +۳ مورد دیگر

Megan Kerr serves as the Katharine and Claudine Malone '63 Professor of Mathematics at Wellesley College, where she teaches across the mathematics curriculum from calculus to advanced topics in geometry. Her academic home is within the Mathematics & Statistics Department at this prestigious women's liberal arts college. Her educational journey began as an undergraduate at Wellesley College, where she later returned as faculty, completing a full circle in her academic career. She earned her Ph.D. from the University of Pennsylvania under the supervision of Wolfgang Ziller, with research focused on Homogeneous Einstein Metrics. Professor Kerr's research centers on global differential geometry, particularly exploring the interplay between curvature constraints and large symmetry groups. She specializes in homogeneous and low-cohomogeneity spaces, investigating fundamental questions about the existence of geometric structures, their rarity or commonality, and potential obstructions. Her work bridges the analytic concept of curvature with the algebraic framework of Lie groups, and she has recently expanded into geometric analysis where topology plays a significant role. Analysis of her publication record reveals a consistent focus on homogeneous Einstein metrics across three decades, with particular attention to curvature properties, symmetry constraints, and classification problems in both positive and negative curvature settings. Her research has evolved from foundational work on symmetric spaces to more complex non-symmetric examples and specialized curvature conditions, demonstrating both depth and breadth in differential geometry. Katharine and Claudine Malone '63 Professor of Mathematics Radcliffe Institute Fellowship As an alumna of Wellesley College, Professor Kerr maintains a strong commitment to encouraging women in mathematics. She teaches a diverse range of courses including calculus, linear algebra, combinatorics, real analysis, non-Euclidean geometry, differential geometry, topology, knot theory, and matrix groups as an introduction to Lie groups. Her teaching philosophy emphasizes developing mathematical understanding and confidence that benefits students regardless of their major. Her research has taken her to international destinations including Australia, Germany, and Mexico, reflecting the global nature of her scholarly collaborations.