جست‌وجوی استاد و پژوهشگر

Ricky Ini Liuمشاهده پروفایل

دانشیار

• Algebraic Combinatorics
• Algebraic Geometry
• Combinatorial Geometry
• +۵ مورد دیگر

Ricky Ini Liu is an Associate Professor in the Department of Mathematics at the University of Washington. Previously, he held positions at North Carolina State University, the University of Michigan, and the University of Minnesota. He earned his Ph.D. in Mathematics from MIT in 2010 under Alexander Postnikov. His research focuses on algebraic combinatorics, particularly its intersections with algebraic geometry, combinatorial geometry, and representation theory. Key interests include Schubert polynomials, polytopes, Hopf algebras, and Kronecker coefficients. He has contributed to foundational work on birational rowmotion, Gelfand-Tsetlin polytopes, and Fomin-Kirillov algebras. Liu has taught a wide range of courses at UW, including special topics in dynamical algebraic combinatorics, combinatorial theory, and problem-solving. He has also been a key instructor at the Mathematical Olympiad Summer Program since 2007 and mentored undergraduates in research programs at the University of Minnesota, Duluth. His publications span high-impact journals like Selecta Mathematica and Journal of Combinatorial Theory , with recent work addressing topics such as determinantal formulas for Schubert polynomials and applications of flow polytopes to diagonal harmonics. Though no specific awards are listed, his extensive publication record and academic roles reflect significant contributions to combinatorial mathematics.

• Algebraic Geometry
• Singularities of Algebraic Varieties
• Hodge Theory
• +۴ مورد دیگر

Mircea Mustata is a Professor in the Department of Mathematics at the University of Michigan. His research focuses on singularities of algebraic varieties and their role in higher-dimensional geometry, with significant work on invariants like log canonical thresholds, minimal log discrepancies, multiplier ideals, and Hodge ideals derived from Saito's mixed Hodge modules. He collaborates extensively, notably with Mihnea Popa on Hodge ideals and with other researchers on topics such as square-free polynomials and F-thresholds. Contact: 3064 East Hall, mmustata@umich.edu Education: Ph.D. from UC Berkeley (2001) Research Interests: Mustata's work bridges algebraic geometry and singularity theory, utilizing tools from resolutions of singularities, jet schemes, D-modules, and positive characteristic methods. His long-term collaboration with Popa explores Hodge ideals, while other projects address Du Bois complexes, stable rationality, and cohomological dimension. Teaching: Courses include Algebraic Geometry I/II, D-modules, commutative algebra, and advanced linear algebra. Lecture notes for topics like toric varieties, rationality, and cohomology are publicly available. Editorial & Organizational Roles: Managing editor of the Michigan Mathematical Journal and member of editorial boards for Compositio Mathematica, Journal de l'École polytechnique-Mathématiques, and Journal of Singularities. Organized events like the Spring School in Ann Arbor and conferences on algebraic geometry.

Johnny Guzmánمشاهده پروفایل

استاد

• Numerical Analysis
• Partial Differential Equations
• Scientific Computing
• +۵ مورد دیگر

Johnny Guzmán is a Professor of Applied Mathematics at Brown University, specializing in numerical analysis of partial differential equations and scientific computing. He holds a Ph.D. in Applied Mathematics from Cornell University (2005) and a B.S. in Mathematics from California State University, Long Beach (1999). His research focuses on numerical methods for PDEs, including discontinuous Galerkin methods, mixed finite element methods, and fluid-structure interaction problems. Key contributions include work on hybridizable and mixed finite element methods, discontinuous Galerkin discretizations, and stability analysis of numerical schemes. He has been funded by multiple NSF grants, including a Postdoctoral Fellowship (2005–2008) and awards totaling over $1M in research support. Notable recognitions include the Comfort and Urry Family Fund Prize (2013). Guzmán collaborates with institutions globally and serves on editorial boards for journals like Journal of Numerical Mathematics and Calcolo . His teaching spans computational linear algebra, numerical methods for differential equations, and finite element analysis.

Renjie Fengمشاهده پروفایل

پژوهشگر ارشد

• Probability Theory
• Random Matrix Theory
• Machine Learning
• +۵ مورد دیگر

Renjie Feng is a Research Fellow in Mathematics and AI at the School of Mathematics and Statistics and the Sydney Mathematical Research Institute , University of Sydney. His work bridges probability theory, statistics, and applications in machine learning, deep learning, and artificial intelligence. His research interests focus on probability theory and its applications to machine learning , random matrix theory , and statistical physics . He investigates extreme value problems, spectral properties of random matrices, and topological features of random fields over Riemannian manifolds. Recent publications highlight trends in random matrix theory (GUE, GOE, GSE), extreme gap problems , determinantal point processes , and Wiener chaos . Collaborative works with F. Götze, D. Yao, and R. Adler emphasize U-statistics , multivariate linear statistics , and random topology inspired by Poisson point process studies.

Gianluca Iaccarinoمشاهده پروفایل

استاد

• Scientific Computing
• Uncertainty Quantification
• Turbulence Modeling
• +۶ مورد دیگر

Gianluca Iaccarino is a Professor of Mechanical Engineering at Stanford University and the Robert Bosch Chairholder. He serves as Director of the PSAAP Center and leads large-scale computational research initiatives in uncertainty quantification, exascale computing, and multiphysics simulations. His academic journey includes a PhD in Mechanical Engineering from Politecnico di Bari (2005), postdoctoral work at Stanford's Center for Turbulence Research, and progression from Research Engineer to full Professor. Education : PhD (Politecnico di Bari), MS/BS in Aeronautical Engineering (University of Naples) Research : Computational engineering, turbulence modeling, uncertainty quantification, biomedical fluid dynamics, and exascale-ready algorithms Publications : 15+ recent articles focus on turbulence modeling, data-driven simulations, and uncertainty quantification across diverse applications in aerospace, biomedical, and energy systems Awards : PECASE (2010), APS Fellow (2019), multiple best paper awards (AIAA, ASME), Terman Fellow (2007) Students : Advises doctoral and master's students in mechanical engineering and computational methods Leadership : Director of PSAAP Center (2014-present), Chair of Mechanical Engineering Department (2024-present)

• Algebraic Geometry
• Syzygies of Algebraic Varieties
• Secant Varieties
• +۶ مورد دیگر

Jinhyung Park is an Associate Professor in the Department of Mathematical Sciences at KAIST, Daejeon, Korea. He obtained his Ph.D. from KAIST in 2014 under Prof. Sijong Kwak and was mentored as a CMC Fellow at KIAS (2014–2019). His research focuses on Algebraic Geometry , particularly syzygies of algebraic varieties , secant varieties , and positivity of line bundles . Education: Ph.D., KAIST (2014); MS/BS, KAIST and University of Chicago (2002/2001). Research Interests: His work explores geometric properties of projective manifolds, singularities in algebraic geometry, and applications of Okounkov bodies to divisors and syzygies. Recent trends include Castelnuovo-Mumford regularity bounds (e.g., for threefolds with rational singularities) and subadditivity of Okounkov bodies in fiber spaces. Teaching: Courses include Matrix Groups, Algebraic Geometry, and Calculus. He previously taught at Sogang University and Purdue University. Professional Affiliations: Member of the Korean Mathematical Society, American Mathematical Society, and other international societies. Organized the 8th East Asia Number Theory Conference at KAIST (2019).

Johan Taflinمشاهده پروفایل

مدرس

• Complex Dynamics
• Pluripotential Theory
• Dynamical Systems
• +۲ مورد دیگر

Johan Taflin is a Lecturer at the University of Burgundy, affiliated with the Institute of Mathematics of Burgundy (IMB) under the Faculty of Science. His research focuses on complex dynamics in several variables and pluripotential theory, with significant contributions to attracting sets, equidistribution, and moduli spaces of dynamical systems. He has led the ANR DynAtrois project since 2025 and oversees the new Master of Mathematics program launching in 2025. Research Interests: Complex dynamics in projective spaces and several variables Pluripotential theory and its applications Dynamical systems, attractors, and moduli spaces Interdisciplinary links with mathematical physics and algebraic geometry Publications Trends: His work spans complex dynamics, including studies on blenders, postcritically finite maps, and equidistribution toward Green currents. Key subfields include holomorphic endomorphisms, algebraic geometry, and mathematical physics. Leadership: He directs the ANR DynAtrois project (2025–2030) and manages the Dijon Master of Mathematics program, which emphasizes fundamental and applied mathematics with ties to artificial intelligence.

Brian Lawrenceمشاهده پروفایل

استادیار

• Arithmetic Geometry
• Number Theory
• Diophantine Geometry
• +۲ مورد دیگر

Brian Lawrence is an Assistant Professor in the Department of Mathematics at the University of Wisconsin–Madison, currently on leave as of 2025. Previously, he held positions at UCLA, the University of Chicago, and Columbia University, following doctoral studies at Stanford University under Akshay Venkatesh. His educational background includes: PhD in Mathematics from Stanford University (advisor: Akshay Venkatesh) Lawrence's research centers on arithmetic geometry, specializing in Diophantine problems through p-adic methods. His work develops innovative approaches to Mordell's conjecture, Shafarevich-type results, and rational point distribution using p-adic Hodge theory, étale cohomology, and period mappings. He bridges theoretical number theory with computational frameworks, particularly in algorithmic solutions for Diophantine equations. His publication trends reveal sustained focus on foundational Diophantine geometry problems, with recent work emphasizing conditional algorithms for the Mordell problem and sparsity phenomena in integral points. Collaborations with leading mathematicians like Venkatesh and Sawin demonstrate interdisciplinary engagement across number theory and algebraic geometry. Lawrence actively mentors undergraduate researchers, supervising projects on resultants, Hodge theory, and symmetric polynomials by students including Pramana Saldin, Yuchen Chen, Anuj Sakarda, and Spencer Dembner. His organizational roles include founding the Crystalline Cohomology seminar at Columbia and co-organizing the University of Chicago Number Theory Seminar, fostering collaborative research environments. He contributes extensively through expository notes on schemes, polynomials on lattices, and Fibonacci numbers modulo p, reflecting commitment to mathematical education and knowledge dissemination across multiple institutions.

Ram Vasudevanمشاهده پروفایل

دانشیار

• Optimization and control of nonlinear systems
• Legged robot locomotion
• Autonomous systems safety
• +۴ مورد دیگر

Ram Vasudevan is an Associate Professor and Associate Chair of Graduate Studies in the Department of Robotics at the University of Michigan. His research focuses on developing tools for safe and robust deployment of robotic systems, emphasizing optimization, nonlinear control, and real-world applications. Key areas include legged robot locomotion, shared control systems, and safety-critical autonomous systems. Research Interests: Optimization and control of nonlinear systems, locomotion of legged robots, shared control active safety systems, and automation of diagnostic/rehabilitative tasks. His ROAHM Lab prioritizes mathematical guarantees for robotic performance, with applications in medical robotics, autonomous vehicles, and soft robotics. Recent work emphasizes trajectory optimization, sensor fusion, and safety-aware control strategies. He has contributed to benchmarks for autonomous vehicle perception and novel methods in thermal image restoration using neural radiance fields. Awards: None explicitly listed in provided text. Labs/Teams: Directs the ROAHM Lab, collaborating on projects like robotic tail mechanics, real-time motion planning, and sensor data analysis. Active in academic conferences including RSS and ICRA.

Lijie Chenمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Computational Complexity Theory
• Quantum Complexity Theory
• +۴ مورد دیگر

Lijie Chen is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley, where he is part of the Berkeley Theory Group. Previously, he was a Miller Research Fellow at UC Berkeley, hosted by Avishay Tal and Umesh Vazirani, and earned his Ph.D. from MIT under Ryan Williams. His research focuses on theoretical computer science, particularly computational complexity theory, with applications to quantum physics and AI safety. Education: Ph.D. in Computer Science from MIT (2022), B.Sc. from Yao Class at Tsinghua University. Research Interests: Complexity theory, quantum complexity, derandomization, circuit lower bounds, and foundational aspects of AI safety. Chen has made significant contributions to understanding fundamental questions in complexity theory, including circuit lower bounds and the connections between randomness and computation efficiency. His work often bridges theoretical insights with practical implications in quantum computing and algorithm design. Awards and Honors: Machtey Award for Best Student Paper (2019). Danny Lewin Best Student Paper Award (2019). Invited to SICOMP Special Issues for FOCS and STOC papers. He has organized workshops on complexity theory and derandomization, and his research has been recognized in venues like STOC, FOCS, and the Journal of the ACM.

Catherine Laiمشاهده پروفایل

دانشیار

• Speech and Language Processing
• Computational Linguistics
• Prosody
• +۱۷ مورد دیگر

Catherine Lai is a Reader (~Associate Professor) in the Department of Linguistics and English Language at the University of Edinburgh, with strong affiliations to the Centre for Speech Technology Research (CSTR) and the Institute for Language, Cognition and Computation (ILCC) in the School of Informatics. She is based in the School of Philosophy, Psychology and Language Sciences and is actively involved in research, teaching, and academic service. Department: Department of Linguistics and English Language School: School of Philosophy, Psychology and Language Sciences Research Institutes: Centre for Speech Technology Research, Institute for Language, Cognition and Computation Email: C.Lai@ed.ac.uk Her research centers on the role of prosody—non-lexical aspects of speech—in spoken communication. She investigates how prosody contributes to discourse structure, information structure, and affect in dialogue, using interdisciplinary methods from linguistics and machine learning. Her work bridges theoretical linguistics and practical speech technology, aiming to improve spoken language understanding and synthesis systems. She is particularly interested in how prosody shapes listener expectations and how affect and topic are expressed and perceived in conversation. Her recent publications reflect a strong focus on self-supervised learning in speech models, emotion recognition, ASR error correction using large language models, cognitive state classification, and ethical considerations in language technology. She explores topics such as the uncanny valley in synthetic speech, gender expression through voice, and community-centered development of language technologies. Prize from Scopus Profile Catherine Lai has supervised several PhD students, including Leimin Tian and Yuanchao Li, and has been involved in significant research projects, such as a Toyota-funded initiative on spoken dialogue for robot companions. She has secured multiple grants and leads a research agenda that integrates theoretical inquiry with real-world applications in assistive technologies and social science. Her academic service includes organizing major conferences like Interspeech and UK and Ireland Speech. She is a key member of research teams at CSTR and ILCC, collaborating across disciplines to advance the understanding of spoken communication and the development of robust, ethical speech technologies.

Jacob Foxمشاهده پروفایل

استاد

• Combinatorics
• Probability
• Graph Theory
• +۳ مورد دیگر

Jacob Fox is a Professor at Stanford University, specializing in Combinatorics and Probability. His research focuses on extremal combinatorics, Ramsey theory, graph theory, and additive combinatorics. He advises students like Maya Sankar. His work explores structural and enumerative aspects of graphs, hypergraphs, and combinatorial configurations. Recent studies include advancements in Ramsey numbers, sumset theory, and probabilistic methods in discrete mathematics. Key research areas include Ramsey numbers for sparse structures, hypergraph properties, and applications of combinatorial geometry. His publications often bridge theoretical insights with algorithmic applications. No scientific awards are listed in the provided text. His advising includes Maya Sankar, with research aligned to combinatorial problems. Collaborative projects involve extremal graph theory and probabilistic combinatorics. No labs or dedicated research groups are explicitly mentioned.

• Data Science
• Machine Learning
• Computational Harmonic Analysis
• +۶ مورد دیگر

Pierre Vandergheynst is a Full Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) in the Department of Electrical Engineering, with a courtesy appointment in Computer and Communication Sciences. He serves as EPFL’s Vice-Provost for Education since 2015 and leads the Signal Processing Laboratory 2 (LTS2). His research spans harmonic analysis, sparse approximations, mathematical data processing, and applications in signal/image processing, computer vision, machine learning, and graph-based data analysis. PhD in Mathematical Physics (1998), Université catholique de Louvain Postdoctoral Researcher at EPFL (1998-2001) Assistant Professor at EPFL (2002-2007) His research explores geometry/symmetry in high-dimensional data, redundant dictionaries for dimensionality reduction, and computational harmonic analysis on manifolds. Recent work focuses on protein structure modeling, geometric deep learning, and graph-based signal processing. Key article trends include graph neural networks for protein analysis, geometric deep learning in neuroscience, and structured knowledge priors in neural models. His 2023-2025 publications emphasize interpretable AI, long-range dependencies in graphs, and molecular representation learning. Scientific Awards: IEEE Signal Processing Magazine Best Paper Award (2023) Signal Processing Society Best Paper Award (2022) Apple ARTS Award (2007) De Boelpaepe Prize, Royal Academy of Sciences of Belgium (2009-2010) He has supervised over 30 PhD theses and contributed to foundational work in graph signal processing, compressive sensing, and geometric deep learning. His lab develops tools for data science on non-Euclidean structures, with applications in medicine, astronomy, and wireless systems.

Mark D. Haimanمشاهده پروفایل

استاد

• Algebra
• Combinatorics
• Algebraic Geometry
• +۱۲ مورد دیگر

Mark D. Haiman is a Professor at the University of California, Berkeley, Department of Mathematics, with research interests spanning algebra, combinatorics, and algebraic geometry. His work connects symmetric function theory with geometric objects like Hilbert schemes and algebraic structures such as Cherednik algebras and Hecke algebras. Appointed: 2001 Contact: mhaiman@math.berkeley.edu Teaching: Math 256B—Algebraic Geometry (Spring 2025), Math 249—Algebraic Combinatorics (Spring 2024), and others in calculus and Lie groups. Research Interests : Haiman's research focuses on Macdonald polynomials, LLT polynomials, Hilbert schemes of points in the plane, and their combinatorial and geometric implications. His work includes resolving the Macdonald positivity conjecture and the n! conjecture through algebraic geometry. Publications : Haiman has contributed to foundational papers in combinatorial and algebraic structures, including generalizations of the shuffle theorem and positivity results for LLT polynomials. His articles often bridge representation theory, symmetric functions, and geometric methods. Students : He has supervised numerous PhD students, including Magda Hlavacek (2023), Foster Tom (2022), Jeremy Meza (2021), Maryam Farahmand-Asil (2018), Maria Monks Gillespie (2016), and others working on combinatorial algebraic geometry and related fields.

Kenneth McLaughlinمشاهده پروفایل

استاد

• Integrable Systems
• Mathematical Physics
• Nonlinear Dynamics
• +۳ مورد دیگر

Kenneth McLaughlin is the Evelyn and John G. Phillips Distinguished Chair in Mathematics at Tulane University's School of Science & Engineering. He holds a Ph.D. and B.A. in Mathematics from New York University (1994 and 1989). Prior to Tulane, he served as faculty at the University of North Carolina, Chapel Hill, the University of Arizona, Universidade Federal de Brasília, and Colorado State University, where he also held leadership roles as Department Head and Chair. His research focuses on integrability, applying techniques across mathematics to study complex systems and phenomena. He has held visiting positions at institutions worldwide, including France, Italy, Brazil, Belgium, and the UK. McLaughlin’s research spans integrable systems, nonlinear dynamics, and asymptotic analysis. His work often involves the Riemann-Hilbert problem approach, orthogonal polynomials, and random matrix theory. Notable contributions include studies on soliton gases, the KdV equation, and universality in quantum operator dynamics. His recent articles explore topics such as asymptotic behavior of polynomials, soliton gas condensation, and hydrodynamic limits in integrable systems. McLaughlin’s academic career is marked by interdisciplinary collaboration and international research engagement.