جستجوی استاد راهنمای دانشگاهی

Michael Barnesمشاهده پروفایل

استاد

• Plasma Physics
• Magnetic Confinement Fusion
• Astrophysical Accretion Disks
• +۳ مورد دیگر

Michael Barnes is a Tutorial Fellow in Physics and Professor of Physics at the University of Oxford. He contributes to the Department of Physics through teaching and research, with a focus on plasma behavior in magnetic fields. His work has critical applications in sustainable energy production via fusion and astrophysical systems. Professor Barnes teaches Mathematical Methods for Physicists to undergraduate students at University College and lectures on Complex Numbers and Ordinary Differential Equations . His pedagogical emphasis is on developing mathematical fluency for advanced physics topics. His research explores plasma turbulence suppression by sheared flows, particularly in magnetic confinement fusion. Key projects include the development of the TRINITY multiscale gyrokinetic transport code and studies on tokamak transport barriers. Recent publications highlight advancements in gyrokinetic simulations, collision operators, and beam diagnostics for fusion applications. Notable trends in his publications include multiscale modeling of plasma turbulence, zonal flow dynamics, and experimental comparisons for fusion devices like JET, MAST, and ITER. Subfields span from fundamental kinetic theory to applied fusion engineering.

Tobias Müllerمشاهده پروفایل

استاد

• Combinatorics
• Probability Theory
• Random Graphs
• +۵ مورد دیگر

Prof. Tobias Müller is a Professor at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen. His academic journey includes previous positions at Utrecht University, CWI (Centrum Wiskunde & Informatica), Tel Aviv University, and Eindhoven University of Technology, with a doctorate from the University of Oxford under Colin McDiarmid. His research focuses on combinatorics, probability theory, random graphs, percolation, discrete and stochastic geometry, and combinatorial game theory. He has contributed extensively to understanding complex networks, hyperbolic models, and geometric random structures. Research Interests: Random Graphs and Percolation Theory Discrete and Stochastic Geometry Hyperbolic Network Models Probabilistic Combinatorics Geometric Probability Graph Algorithms and Connectivity Notable Contributions: Analysis of Voronoi and Poisson-Voronoi percolation in hyperbolic planes. Studies on Mallows random permutations and their cycle structures. Research on component games and logical limit laws in graph theory. Investigations into the geometry and properties of random geometric graphs. Grants & Collaborations: Active in organizing workshops and conferences on random graphs and geometric networks, including the BIRS Workshop on Random Geometric Graphs and the STAR Workshops series. Labs/Teams: Member of the Bernoulli Institute’s research groups, focusing on stochastic studies, combinatorics, and algorithmic methods.

Bo Zhuمشاهده پروفایل

استادیار

• Computer Graphics
• Computational Physics
• Scientific Machine Learning
• +۳ مورد دیگر

Bo Zhu is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology. His research focuses on computational approaches for complex physical systems, including fluid dynamics, topology optimization, and robotics control. He holds a Ph.D. from Stanford University and completed postdoctoral research at MIT CSAIL. He has been recognized with the NSF Career Award (2022) and multiple best paper awards at SIGGRAPH conferences. Education: B.E.-M.S., Software Engineering, Shanghai Jiao Tong University Ph.D., Computer Science, Stanford University Postdoc, EECS, MIT Research Interests: Develops numerical algorithms and machine learning techniques to simulate fluidic systems, soft materials, and multi-scale phenomena. His work emphasizes vorticity preservation, real-time simulation, and physics-based AI integration. Key Contributions: Pioneered Particle Flow Map (PFM) methods for fluid simulation, developed open-source libraries like SimpleX and PFM Hub, and contributed to projects like Genesis physics engine. Over 50 peer-reviewed publications in top venues (SIGGRAPH, NeurIPS, IEEE TVCG). Awards: NSF Career Award (2022) Best Paper Honorable Mention (SIGGRAPH 2025) Best Paper Award (SIGGRAPH Asia 2024) Grants & Projects: Leads NSF-funded research on Physical AI Design, collaborating with Sandia National Labs on real-time CFD solvers. Active in open-source software development for computational physics and graphics.

• Numerical analysis
• Partial differential equations
• Fluid mechanics
• +۵ مورد دیگر

Dr. Jean-Christophe Nave is an Associate Professor in the Department of Mathematics and Statistics at McGill University. He holds a PhD from the University of California, Santa Barbara (2004), under advisors Xu-Dong Liu and Sanjoy Banerjee. Prior to McGill, he served as a Lecturer and Instructor at MIT's Mathematics Department (2005-2010). His research focuses on numerical analysis, partial differential equations, fluid mechanics, and computational methods for interface problems. He has led research groups involving postdocs, PhD, and undergraduate students, collaborating on projects like the Correction Function Method for PDEs and the Characteristic Mapping Method for advection problems. Education: Ph.D. in Applied Mathematics from UCSB (2004). Affiliations include the Institut des Sciences Mathematiques Steering Committee, Centre de Recherches Mathematiques Applied Math Lab, and CNRS-UMI. Active in teaching courses like Numerical Analysis I/II and Non-Linear Dynamics at McGill, with sabbatical periods noted in recent years. Research interests span numerical methods for PDEs, fluid-structure interaction, and multi-phase flows. His work integrates computational geometry and invariant numerical techniques, addressing challenges in complex fluid dynamics and interface-driven phenomena. Over 40 peer-reviewed publications and continuous contributions to the field of computational applied mathematics. Scientific advising includes over 20 graduate and undergraduate students, with notable alumni now in academia and industry. Collaborations include projects on volcano dynamics, fiber drawing instabilities, and concentrated solar power systems. His methods have advanced numerical simulations for engineering and physical systems involving discontinuous coefficients and sharp interfaces.

Jason Schweinsbergمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Mathematical Biology
• +۵ مورد دیگر

Jason Schweinsberg is a Professor in the Department of Mathematics at the University of California, San Diego (UCSD), where he has been a faculty member since Fall 2004. His academic journey began with a Ph.D. in Statistics from the University of California, Berkeley in 2001, followed by a three-year NSF Postdoctoral Fellowship at Cornell University. His research focuses on probability theory with applications to evolutionary biology and population genetics. Schweinsberg's work centers on stochastic processes involving coalescence, branching Brownian motion, and their connections to biological phenomena. He has made significant contributions to understanding population models undergoing selection, cancer evolution, and spatial mutation processes. Recent publications reveal a strong emphasis on coalescent theory (particularly Λ-coalescents and nested coalescents), branching processes with absorption, and spatial evolutionary models. His work often bridges rigorous mathematical analysis with biological applications, especially in population genetics and cancer modeling. The 15 most recent articles demonstrate consistent focus on asymptotic analysis of stochastic processes, genealogical structures, and mutation dynamics in evolving populations. Scientific Awards: Fellow of the Institute of Mathematical Statistics NSF Postdoctoral Research Fellowship While specific student names aren't listed in the source material, Schweinsberg has delivered numerous lecture series at international institutions including the Indian Institute of Science (Bangalore), Centre de Recherches Mathématiques (Montreal), and the Isaac Newton Institute (Cambridge), indicating active mentorship and academic leadership. His collaborations span multiple institutions, with frequent co-authorship with researchers like Julien Berestycki, Nathanaël Berestycki, and Rick Durrett. Though no formal lab structure is mentioned, Schweinsberg participates in interdisciplinary research communities through workshops at institutions like BIRS (Banff International Research Station), where he presented on mutation patterns in spatially structured populations in May 2025. His work connects probability theory with biological applications through sustained collaborations across mathematics, statistics, and computational biology fields.

Daniel Hugمشاهده پروفایل

استاد

• Probability
• Geometry
• (Convex) geometric analysis
• +۳ مورد دیگر

Prof. Dr. Daniel Hug is a Professor at the Karlsruhe Institute of Technology (KIT) , affiliated with the Department of Mathematics and the Institute of Stochastics . His research focuses on Probability , Geometry , Convex geometric analysis , Stochastic geometry , and Educational mathematics . He contributes to the DFG Priority Program Random Geometric Systems and previously participated in the DFG research unit Geometry and Physics of Spatial Random Systems . Prof. Hug has co-authored two influential monographs: Poisson Hyperplane Tessellations (Springer Monographs in Mathematics) and Lectures on Convex Geometry (Springer Graduate Texts in Mathematics, 2020). His work spans theoretical advancements in convex and stochastic geometry , including integral geometry, random mosaics, and tensor valuations, alongside applied studies in digital microstructures and Minkowski tensors . His publications from 2025–2024 emphasize hyperbolic space , Boolean models , and Minkowski tensor estimators , reflecting ongoing collaborations with researchers like M. Klatt, C. Thäle, and R. Schneider. Prof. Hug leads courses such as Stochastic Geometry and seminars on Random graphs and tessellations , and is actively involved in working groups like AG Stochastische Geometrie and AG Stochastik .

Hasan Gumralمشاهده پروفایل

استاد

• Differential Equations
• Geometric Mechanics
• Poisson Structures
• +۵ مورد دیگر

Professor Hasan Gumral is a distinguished faculty member at Yeditepe University's Faculty of Arts and Sciences, Department of Mathematics. With a career spanning several decades, he has established himself as a leading researcher in geometric mechanics and mathematical physics. His educational background includes a PhD from Bilkent University (1988-1992) with a thesis on "Integrability and Poisson structures of three dimensional dynamical systems and equations of hydrodynamic type," a Master's degree (1986-1988), and undergraduate studies (1981-1986) from Middle East Technical University, all in Physics/Mathematics. Professor Gumral's research focuses on the intersection of differential geometry and dynamical systems, particularly examining Hamiltonian structures in various physical contexts. His work bridges theoretical mathematics with applications in plasma physics and fluid dynamics, demonstrating how geometric frameworks can illuminate complex physical phenomena. His approach combines deep mathematical rigor with physical intuition, making significant contributions to understanding the geometric underpinnings of dynamical systems. His publication record shows consistent output in high-impact journals like Journal of Mathematical Physics and Journal of Geometric Mechanics, with research evolving from foundational work on Poisson structures to sophisticated analyses of plasma dynamics and geometric mechanics. TÜBİTAK Teşvik Award (Ministry of Science, Industry and Technology) Professor Gumral has supervised multiple graduate students, including Oğul Esen (Master's 2006, Doctoral 2010) and Aytan (Doctoral 2023). His teaching portfolio is extensive, covering undergraduate courses like Differential Equations and Differential Geometry, as well as graduate courses including Lie Groups and Lie Algebras and Introduction to Geometric Mechanics. He previously served as Department Chair at Yeditepe University from 2003.

Marco Manettiمشاهده پروفایل

استاد

• Algebraic Geometry
• Deformation Theory
• Complex Surfaces
• +۴ مورد دیگر

Marco Manetti is a Full Professor of Geometry at the Dipartimento di Matematica 'Guido Castelnuovo' of Sapienza Università di Roma. His primary academic role involves research and teaching in algebraic geometry and deformation theory. He has held editorial positions, including Editor-in-Chief of Rendiconti di Matematica e delle sue Applicazioni and editor of Annali di Matematica Pura ed Applicata . Research interests focus on algebraic surfaces, moduli spaces, deformation theory, and differential graded Lie algebras. Notable contributions include work on semiregularity maps, formality conjectures, and L∞-algebras. He has authored influential textbooks like Topologia and Lie Methods in Deformation Theory . He actively engages in outreach, organizing mathematics competitions and events like Intrecci Matematici . Awards include the Premio Bartolozzi (1999). His work bridges pure mathematics with applications in mathematical physics and topology.

Francesca Da Lioمشاهده پروفایل

استاد

• Partial Differential Equations
• Mathematical Analysis
• Geometric Analysis
• +۲ مورد دیگر

Francesca Da Lio is a Professor at the Department of Mathematics, ETH Zurich, where she has held a titular professorship since 2014. Her research focuses on nonlinear elliptic and parabolic partial differential equations (PDEs), with applications in stochastic and deterministic optimal control, homogenization, front propagation, and geometric analysis. She has pioneered work on conformally invariant variational problems and nonlocal PDEs, including fractional harmonic maps and stability analysis for critical points. PhD in Mathematics (1998) and Summa Cum Laude Degree in Mathematics (1994) from University of Padova. Her research explores the interplay between nonlinearity and non-locality, particularly in problems arising from geometry, mathematical finance, and physics. She has led major Swiss National Fund (SNF) projects, including grants for geometric analysis and conformally invariant variational theory. Her work on 3-commutators, integrability by compensation, and Morse index stability has advanced the understanding of harmonic maps and elliptic systems. Francesca Da Lio has mentored numerous PhD, postdoctoral, and Master/Bachelor students, including Dominik Schlagenhauf, Jerome Wettstein, and Ali Hyder. She has served on hiring committees for full professorships at ETH Zurich and co-organized international conferences such as 'Recent Advances in Nonlocal and Nonlinear Analysis' and 'Topics in Sub-Elliptic PDEs.' Scientific Awards: Italian Scientific Qualification as Full Professor in Mathematical Analysis (2013). She contributes to editorial boards, including Advances in Calculus of Variations , and participates in academic services like refereeing for SNF projects and international journals.

• Physics
• Computer Science
• Mathematics
• +۱۰ مورد دیگر

Cristopher Moore is a Professor at the Santa Fe Institute, where he conducts interdisciplinary research at the intersection of physics, computer science, and mathematics. His work focuses on understanding phase transitions in computational problems, statistical inference, and network analysis. Moore has made significant contributions to the fields of complex systems, quantum computing, and algorithmic justice. Moore's primary research areas include phase transitions in computational problems and statistical inference, where he investigates how problems suddenly become hard or impossible to solve when certain thresholds are crossed. His work spans social networks, big data analysis, quantum computing, algorithmic transparency, and decarbonization efforts. He is particularly known for applying physics-inspired approaches to computational problems, using techniques from spin glass theory, network theory, and computational complexity. His recent publications reveal a strong focus on community detection in networks, phase transitions in data science problems, algorithmic fairness in criminal justice systems, and quantum computing applications. Moore's work demonstrates consistent patterns across multiple disciplines, with recurring themes of phase transitions, computational limits, and the application of physics concepts to computational problems. Moore actively mentors students and has advised numerous PhD and Master's students who have gone on to successful careers in academia and industry. His work on algorithmic justice has influenced policy discussions in New Mexico and beyond, particularly regarding risk assessment in the criminal justice system.

Garvesh Raskuttiمشاهده پروفایل

دانشیار

• Statistical Machine Learning
• Optimization Theory
• Graphical and Network Modeling
• +۵ مورد دیگر

Garvesh Raskutti is an Associate Professor in the Department of Statistics at the University of Wisconsin–Madison, affiliated with the School of Computer, Data & Information Sciences. He holds joint affiliations with the Departments of Computer Science, Electrical and Computer Engineering, and the Wisconsin Institute of Discovery Optimization Group. His research focuses on statistical machine learning, optimization, graphical/network modeling, and information theory, with applications to systems biology and neuroscience. Education: MEng from the University of Melbourne (2008), PhD from UC Berkeley (2012, advised by Martin Wainwright and Bin Yu), and postdoctoral work at SAMSI. Teaching awards include Honored Instructor (2014, 2017) and Madison Teaching and Learning Excellence Fellow (2015). He advises multiple PhD and undergraduate students, including Yuan Li, Hyebin Song, and Lili Zheng. His grants include NGA HM0476-17-1-2003 (Co-PI), ARO W911NF-17-1-0357 (Co-PI), and NSF-DMS 1407028 (Sole PI). Research interests span large-scale statistical inference, computational-statistical trade-offs, and applications in systems biology and neuroscience. His work bridges optimization (e.g., gradient descent, convex regularization), high-dimensional regression, and network analysis. Recent trends in publications emphasize methods for non-convex optimization, sparse models, and network structure learning. Awards include teaching recognition and grants in statistical methodology. Advising spans theoretical and applied projects, with former students like Gunwoong Park (now at University of Korea). Collaborations include interdisciplinary teams in machine learning and signal processing.

• Geometric Analysis
• Partial Differential Equations
• Calculus of Variations
• +۳ مورد دیگر

Andrea Pinamonti is an Associate Professor at the University of Trento. His research focuses on geometric analysis, partial differential equations, calculus of variations, and functional analysis in metric measure spaces, particularly in sub-Riemannian and Carnot group settings. He frequently collaborates with researchers from institutions such as the Universities of Pisa, Jyväskylä, and others, addressing topics like geometric measure theory, regularity of solutions, and nonlocal functionals. His recent work examines structures in Heisenberg groups, such as perimeter minimization, CR geometry, and differentiability theorems. He has also explored equations involving the p-Laplacian, fractional operators, and universal differentiability sets in non-Euclidean spaces. These studies reflect a sustained engagement with the interplay between geometry and analysis in sub-Riemannian frameworks. Events and Contributions: Speaker at Warsaw Analysis Days Event WADE25 (2025), Summer school in fluid dynamics (2024), and Workshop on Synthetic Curvature Bounds (2024). Organizer of Three days between Analysis and Geometry in Trento (2025, 2024) and EUregio School on Control Theory and Applications (2024). He has maintained a prolific publication record across high-impact journals such as Journal of Geometric Analysis , Advances in Mathematics , and Communications in Contemporary Mathematics . His academic activities include promoting collaborative research through workshops and open positions at his institution.

Luca Vitaglianoمشاهده پروفایل

استاد

• Differential Geometry
• Mathematical Physics
• Poisson Geometry
• +۴ مورد دیگر

Luca Vitagliano is a Full Professor of Geometry at the Department of Mathematics, University of Salerno. His research focuses on Differential Geometry and Mathematical Physics, with specializations in Poisson Geometry, Lie Algebroids/Groupoids, Differentiable Stacks, and Geometric Methods for PDEs. He has advised four PhD students, including Antonio Maglio (2025) and Pier Paolo La Pastina (2020). He teaches courses such as Geometry II, Homology and Cohomology, and Higher Geometry. His recent articles explore shifted contact structures, Nijenhuis integrations, and deformation cohomology. Education: Not explicitly stated in text Research Groups: Geometry Group at University of Salerno Affiliations: INdAM Intensive Period on Poisson Geometry, Poisson 2024 Conference His work bridges pure mathematics (homological methods, stack theory) with applications in mathematical physics, emphasizing geometric structures like Jacobi manifolds and coisotropic submanifolds. He actively participates in international conferences and publishes with collaborators globally.

• Differential Geometry
• Complex Geometry
• Geometric Structures on Manifolds
• +۴ مورد دیگر

Anna Fino is a Full Professor at the Department of Mathematics, University of Turin. Her research focuses on differential and complex geometry, particularly geometric structures on manifolds such as nilmanifolds, solvmanifolds, G₂-structures, and Hermitian manifolds. She has contributed to studies on special metrics (balanced, SKT, Calabi-Yau), holonomy groups, cohomology theories, and geometric flows like the Laplacian flow for G₂-structures. Her work often intersects with algebraic topology and geometric analysis, addressing topics such as tamed symplectic structures, Ricci solitons, and invariant geometric properties on homogeneous spaces. Recent activities include organizing conferences on differential geometry and participating in international collaborations. Key research themes include: Geometric structures on nilpotent and solvable Lie groups Special holonomy and calibrated geometries Hermitian and almost complex manifolds Cohomological aspects of complex and symplectic manifolds Her publications frequently explore interplays between differential geometry and algebraic structures, with applications to geometric flows and classification problems.

James Pascaleffمشاهده پروفایل

دانشیار

• Symplectic Geometry
• Floer Theory
• Homological Mirror Symmetry
• +۳ مورد دیگر

James Pascaleff is an Associate Professor in the Department of Mathematics at the University of Illinois at Urbana-Champaign (UIUC), where he has held tenured faculty positions since 2014. He specializes in symplectic geometry, Floer theory, and homological mirror symmetry. His work bridges geometric and algebraic approaches, with notable contributions to Fukaya categories and their applications in mirror symmetry. Education: Ph.D. in Mathematics, MIT (2011), advised by Denis Auroux A.B. in Mathematics, University of Chicago (2006, honors) Research Interests: Focus on symplectic topology, including Fukaya categories, Lagrangian submanifolds, wall-crossing phenomena, and their connections to algebraic geometry and mirror symmetry. Recent work explores higher categorical structures and applications of monoidal Fukaya categories. Awards & Grants: Simons Foundation Collaboration Grant (2019–2024) NSF Award (2014–2017) on symplectic cohomology and equivariant Lagrangians Paul R. Cohen Memorial Prize (2006), MIT Presidential Fellowship Teaching & Mentorship: Teaches undergraduate and graduate courses in algebraic topology, abstract algebra, and differential geometry. Advises Ph.D. students in symplectic geometry and related fields. Serves as Chair of the Undergraduate Affairs Committee and faculty liaison for student success initiatives.