جست‌وجوی استاد و پژوهشگر

• Computational Mechanics
• Contact Mechanics
• Finite Element Method
• +۱۸ مورد دیگر

Giorgio Zavarise is a Full Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Politecnico di Torino, where he also contributes to the SISCON Interdepartmental Center for Safety of Infrastructures and Constructions. His academic work spans computational and structural mechanics, with a focus on contact mechanics, finite element methods, and thermomechanical modeling. He has held leadership roles in numerous international conferences and serves on the editorial board of Computational Mechanics . His research interests include contact mechanics, isogeometric analysis, cohesive zone modeling, beam-to-beam contact, and the mechanics of masonry and massive concrete structures. He has extended his work into advanced technological applications such as subatomic particle detectors (e.g., Mu2e, SuperB, MEG), thermonuclear fusion (RFX, ITER), large optical telescopes (LBT), and structural fire analysis. His methodologies integrate physical modeling with computational efficiency, often involving multi-scale and coupled problems. The recent publications reflect a strong trend in computational contact mechanics, particularly using NURBS and T-splines for isogeometric analysis, as well as cohesive zone models for fracture and delamination. His work consistently emphasizes algorithmic robustness, geometric accuracy, and real-world engineering applications across civil, aerospace, and energy sectors. Scientific Awards and Recognitions: Fellow of the International Association for Computational Mechanics (IACM), 2013–2022 Professional Memberships: Full Member, IACM Full Member, Italian Group of Computational Mechanics Full Member, AIMETA (Italian Association of Theoretical and Applied Mechanics) Full Member, EUROMECH (European Mechanics Society) Advising and Grants: He has supervised PhD students in Civil, Mechanical, and Complex Systems Engineering at Politecnico di Torino and Università del Salento. He has led multiple PRIN-funded national research projects on contact and fracture mechanics and is currently managing a commercial consulting project on reconstructed stone materials. His editorial role in Computational Mechanics and chairmanship of the ICCCM series highlight his leadership in the computational mechanics community. He has also contributed to the Encyclopedia of Computational Mechanics . Laboratories and Teams: He is affiliated with the SISCON Interdepartmental Center, focusing on infrastructure safety, and collaborates internationally with institutions such as INFN (Lecce), Fermilab, CNR, and the University of Arizona’s Steward Observatory.

Cristina G. Fernandesمشاهده پروفایل

دانشیار

• Algorithms
• Combinatorial Optimization
• Graph Theory
• +۷ مورد دیگر

Cristina G. Fernandes is an Associate Professor in the Department of Computer Science at the Institute of Mathematics and Statistics, University of São Paulo (IME-USP), where she conducts research in theoretical computer science, combinatorial optimization, and graph theory. She teaches advanced courses such as Advanced Data Structures and Topics in Algorithm Analysis. Her research interests include algorithms, combinatorial optimization, graph theory, approximation algorithms, data structures (persistent, retroactive, kinetic, succinct), and computational geometry. She applies theoretical methods to solve complex problems in network design, clustering, and discrete structures. The recent publications reflect a strong focus on structural and extremal graph theory, approximation algorithms, and combinatorial optimization. Key themes include tree and path packing, dominating sets, Steiner-type problems, and combinatorial properties of graphs. Her work often involves deep structural analysis and algorithmic design for NP-hard problems. Cristina G. Fernandes has not been mentioned with any specific scientific awards in the provided texts. She has supervised numerous postdoctoral researchers, PhD, MSc, and undergraduate students, many funded by FAPESP, CAPES, and CNPq. She leads significant research projects, including CAPES/MATH/STIC/CLIMAT-AMSU on energy efficiency in distributed computing and CNPq Universal projects on partitioning and connectivity. She is actively involved in academic advising and grant-funded research. She leads or participates in the Research Group in Theoretical Computer Science, Combinatorics and Combinatorial Optimization at IME-USP, fostering collaborative research in algorithms and discrete mathematics.

Stéphan Thomasséمشاهده پروفایل

استاد

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

Stéphan Thomassé is a Professor in the Computer Science Department at Ecole Normale Supérieure de Lyon, where he is affiliated with the Parallel Computing Laboratory (LIP) and leads the Computational Models, Complexity, Combinatorics (MC2) research team (2023-2025). He was a Member of the University Institute of France from 2016-2021 and has held significant administrative roles including Head of M2 Fundamental Computer Science (2013-2015) and Deputy Director of the Computer Science Department (2013-2015). Thomassé's research focuses on graph theory, combinatorics, algorithms, and theoretical computer science. His work spans structural graph theory , parameterized complexity , graph coloring , and combinatorial optimization . He is particularly known for his groundbreaking work on twin-width, a graph parameter that has revolutionized understanding of sparse and dense graph classes and their algorithmic properties. His research connects combinatorial structures with computational complexity, often bridging theoretical insights with practical algorithmic applications. His recent publications demonstrate a strong focus on structural graph theory, with the twin-width series representing a major contribution to the field. These papers have established connections between graph parameters, model theory, and algorithm design, particularly for problems that were previously thought to be intractable on dense graph classes. Thomassé's work on graph coloring, particularly regarding dense triangle-free graphs and the Erdős-Hajnal conjecture, has resolved long-standing open problems. Member of University Institute of France (2016-2021) ANR projects: GRAAL, AGAPE, STINT, COMPA, Digraphs, TWIN-WIDTH, GODASse As an advisor and educator, Thomassé has taught numerous advanced courses including Algorithmics, Optimization and Approximation, Tree Decompositions and FPT Algorithms, and Graph Decompositions. His teaching reflects his research expertise, emphasizing both theoretical foundations and practical applications of discrete mathematics. His administrative leadership in the MC2 team and the Computer Science Department demonstrates his commitment to advancing research and education in theoretical computer science. Thomassé maintains active collaborations with researchers worldwide, as evidenced by his extensive publication record with co-authors from various institutions. His work continues to shape the landscape of structural graph theory and parameterized algorithms, with recent results opening new avenues for research in combinatorics and theoretical computer science.

Jaroslav Hronمشاهده پروفایل

دانشیار

• Fluid Mechanics
• Biomechanics
• Numerical Analysis
• +۳ مورد دیگر

Dr. Jaroslav Hron is an Associate Professor at the Department of Numerical Mathematics within the Faculty of Mathematics and Physics at Charles University in Prague, Czech Republic. His primary research focuses on fluid mechanics, biomechanics, and numerical analysis, with particular expertise in fluid-structure interaction problems and their applications to cardiovascular mechanics. Dr. Hron's research interests span fluid mechanics, biomechanics, numerical analysis, and computational mathematics. His work primarily investigates fluid-structure interaction problems, particularly as they apply to cardiovascular mechanics and hemodynamics. He has made significant contributions to the understanding of non-Newtonian fluids, pressure-dependent viscosities, and the development of advanced numerical methods for solving complex fluid flow problems. His research often bridges the gap between theoretical mathematics and practical applications in biomedical engineering. Analysis of his recent publications reveals a strong focus on cardiovascular applications, particularly in determining pressure data from velocity measurements and modeling blood flow in complex geometries. His work demonstrates a consistent progression from theoretical considerations to practical applications in biomechanics, with increasing emphasis on computational methods for fluid-structure interaction problems. The research shows interdisciplinary collaboration across mathematics, engineering, and medical fields. Dr. Hron has been actively involved in academic advising and research supervision, contributing to the development of computational methods in fluid mechanics. His work has established important benchmarks in fluid-structure interaction simulation, particularly in hemodynamic applications. His laboratory work primarily focuses on computational fluid dynamics and fluid-structure interaction, with applications to cardiovascular mechanics. He has developed and refined numerical methods for simulating complex fluid behaviors, particularly those relevant to biological systems.

• Probability Theory
• Statistical Mechanics
• Mathematical Physics
• +۸ مورد دیگر

Nathanael Berestycki is a University Professor (Univ.-Prof.) in the Department of Mathematics within the Faculty of Mathematics. His research spans multiple areas of probability theory and mathematical physics with a particular focus on stochastic processes and their connections to statistical mechanics and quantum gravity. Professor Berestycki's research interests center around probability theory, with significant contributions to the understanding of Gaussian free fields, Liouville quantum gravity, and random processes. His work explores deep connections between statistical mechanics and mathematical physics, particularly in the context of conformal invariance and scaling limits. He has made substantial contributions to the theory of dimers, Brownian motion, random graphs, and branching processes, often revealing unexpected connections between seemingly disparate areas of mathematics. Analysis of his recent publications shows a consistent focus on the intersection of probability theory and mathematical physics, with particular emphasis on conformal invariance properties, scaling limits of discrete models, and the mathematical structure of quantum gravity. His work often bridges theoretical developments with concrete applications in statistical mechanics, demonstrating how deep mathematical structures emerge from seemingly simple probabilistic models. The breadth of his research is reflected in publications across top probability and mathematical physics journals. Throughout his career, Berestycki has maintained a high level of productivity with consistent publication output across leading journals in probability theory and mathematical physics. His collaborative work with researchers across institutions demonstrates strong connections within the mathematical community, particularly in the European probability research network.

Sergio Galindo Torresمشاهده پروفایل

دانشیار مدعو

• Geotechnical Engineering
• Fluid Dynamics
• Computational Modeling
• +۵ مورد دیگر

Dr. Sergio Galindo Torres is an Adjunct Associate Professor at the School of Civil Engineering, University of Queensland (UQ). His research focuses on geotechnical engineering, fluid dynamics, and computational modeling of granular and porous media. He specializes in discrete element methods (DEM), lattice Boltzmann methods (LBM), and their coupling for simulating particle-fluid interactions. His work addresses transient two-phase flow, hydraulic fracturing, dispersion in porous media, and erosion mechanisms. His publications (45 journal articles, 31 conference papers, and technical reports) highlight his expertise in micromechanical analysis and numerical simulation of complex geological systems. Recent studies examine Péclet-number-dependent dispersion and airblast hazards in block caving. The 15 most recent articles reflect trends across computational geomechanics, with emphasis on: Fluid flow in static/dynamic porous media DEM-LBM coupling for granular-fluid systems Two-phase displacement under varying boundary conditions Airblast hazard simulation in mining Liquefaction micromechanics Capillary pressure-saturation dynamics Dr. Galindo Torres collaborates with researchers like Alexander Scheuermann and Ling Li, and his work appears in journals such as Water Resources Research , Physical Review , and Computers and Geotechnics . He does not list specific awards or advisees in this dataset.

Michael E. O'Sullivanمشاهده پروفایل

استاد

• Coding Theory
• Algebraic Geometry
• Error-Correcting Codes
• +۶ مورد دیگر

Michael E. O'Sullivan is a Professor and Chair in the Department of Mathematics and Statistics at San Diego State University. He has taught advanced courses such as Commutative Algebra and Algebraic Geometry (Math 621) and Groups, Rings, and Fields (Math 620), with a focus on integrating computational tools like Sage, Maple, and Magma into his teaching. Research Focus: His work centers on Coding Theory , particularly Algebraic Geometry Codes , Hermitian Codes , and LDPC Codes . His research includes developing decoding algorithms (e.g., Groebner basis methods, Sudan's list decoding), analyzing code properties (e.g., minimum distance, redundancy), and optimizing code constructions. Publications: His most recent articles (2014–2006) address unique decoding of AG codes, list decoding techniques, and applications of algebraic structures to code optimization. These span journals like IEEE Transactions on Information Theory and Designs, Codes and Cryptography , as well as conferences such as IEEE International Symposium on Information Theory and Canadian Workshop on Information Theory . Emails: Contact him at mosullivan@mail.sdsu.edu or m.osullivan@math.sdsu.edu .

Milan Predojevićمشاهده پروفایل

استادیار

• Bioinformatics
• Computational Biology
• Combinatorial Optimization
• +۴ مورد دیگر

Milan Predojević is a senior assistant (equivalent to Assistant Professor) at the Department of Computer and Information Sciences, Faculty of Science and Mathematics, University of Banja Luka, where he has been employed since January 2021. Previously, he served as an assistant professor at the same institution from March 2017 to January 2020. He holds a Master of Informatics from the Faculty of Science and Mathematics, University of Novi Sad (2020), and a degree in Mathematics and Computer Science from the Faculty of Natural Sciences and Mathematics, University of Banja Luka (2016). He is currently pursuing doctoral studies at the Faculty of Mathematics in Belgrade, University of Belgrade. Dr. Predojević's research focuses on the intersection of computer science and biology, particularly in bioinformatics and computational biology. His work explores protein-protein interaction networks, combinatorial optimization problems, and the application of machine learning techniques to biological data analysis. He teaches courses including Databases, Compiler Construction, Algorithms, and Introduction to Artificial Intelligence. His recent publications demonstrate a strong emphasis on applying computational methods to solve biological problems, particularly in protein complex identification and analysis. His research often involves collaboration with colleagues like Milana Grbić, Dragan Matić, and Marko Đukanović. Dr. Predojević is actively involved in multiple research projects related to bioinformatics, machine learning applications in biology, and combinatorial optimization. His work bridges theoretical computer science with practical applications in biological data analysis.

• Geometry
• Machine Learning
• Data Science
• +۲ مورد دیگر

Vidit Nanda is a Professor in the Department of Mathematics at the University of Oxford, actively contributing to Geometry, Machine Learning, Data Science, and Topological Data Analysis. His work bridges discrete Morse theory, persistence modules, and computational topology with practical applications in data science and biology. Research Focus: Topological Data Analysis, Algebraic Structures, and Computational Topology Recent Publications: Focus on hyperquiver representations, stratification theory, and Wasserstein-based dimension estimation (2023–2025) Collaborations: Regularly works with researchers in applied mathematics, computer science, and computational biology

• Algorithms
• Computational Geometry
• Discrete Mathematics
• +۴ مورد دیگر

Dr. Maarten Löffler is an Assistant Professor at Utrecht University's Information and Computing Sciences department within the Science faculty. He is also currently serving as a Visiting Professor at Tulane University. His research bridges theoretical computer science with practical applications in geometric algorithms, game research, and data science. Education : PhD in Geometric Uncertainty (Utrecht University), Post-Doc in Social Network Analysis (University of California, Irvine) His expertise lies in computational geometry, discrete mathematics, and algorithm design, with applications in graph drawing and geogaming. He contributes to the Game and Media Technology and Informatica study programs, teaching courses like Three-Dimensional Modeling. Contact: Buys Ballotgebouw, Princetonplein 5, Room BBL411, 3584 CC Utrecht, Netherlands. Phone: +31 30 253 6759.

Marco Castronovoمشاهده پروفایل

استادیار

• Topology
• Symplectic Geometry
• Algebraic Geometry
• +۲ مورد دیگر

Marco Castronovo is a Barnard Assistant Professor in the Department of Mathematics at Columbia University, affiliated with Barnard College. His research focuses on Topology, specifically symplectic structures as a framework for quantizing classical invariants and developing open-string versions of Schubert calculus. His primary research areas include: Topology Symplectic Geometry Algebraic Geometry Mathematical Physics Combinatorics His work bridges continuous and discrete phenomena through computational tools like DubrovinDynamics, Posetroids, and ClusterExplorer, which analyze Grassmannians, positroid strata, and mirror symmetry phenomena. Recent publications examine Lagrangian cobordisms, Fukaya categories, and Liouville domains. He actively contributes to academic service as a referee and co-organizer of the Columbia SGGTC Seminar. Current teaching responsibilities include mentoring summer research students (B. Basson and S. Kesavan) and scheduled courses: Calculus I (Fall 2025) and Introduction to Differentiable Manifolds (Spring 2026).

Marissa Kawehi Lovingمشاهده پروفایل

استادیار

• Low-dimensional topology
• Mapping class group
• Geometric group theory
• +۳ مورد دیگر

Marissa Kawehi Loving is an Assistant Professor of Mathematics at the University of Wisconsin-Madison and a Nellie Y. McKay Fellow. Her research focuses on low-dimensional topology, the mapping class group, and geometric group theory. She is affiliated with the Geometry, Group Actions, and Dynamics Research Training Group (RTG) and currently holds an NSF Standard Grant. Her scientific contributions span both topology and algebraic combinatorics. In topology, she has advanced the study of end-periodic homeomorphisms, mapping tori, and spectral rigidity, while her combinatorial work includes (t,r) broadcast domination, weight multiplicity formulas for Lie algebras, and automorphisms of curve graphs. Marissa co-founded the SUBgroups, paraDIGMS (Diversity in Graduate Mathematical Sciences), and the Indigenous Mathematicians Network, highlighting her commitment to community building. NSF Graduate Research Fellowship NSF Postdoctoral Research Fellowship NSF Standard Grant Nellie Y. McKay Fellow 2023 Black Mathematician Honoree (Mathematically Gifted & Black) Her recent publications analyze topics such as stretch factors for end-periodic homeomorphisms, volumes of mapping tori, spectral rigidity of surfaces, and combinatorial structures in Lie algebras. She mentors students and collaborates on projects involving undergraduates, as seen in her co-authored works with undergraduate researchers.

Hadi Kharaghaniمشاهده پروفایل

استاد

• Combinatorial design theory
• Hadamard matrices
• Orthogonal designs
• +۲ مورد دیگر

Hadi Kharaghani is a Professor of Mathematics at the University of Lethbridge, specializing in combinatorial design theory with a focus on Hadamard matrices and orthogonal designs. His research explores the intricate relationships between discrete structures, algebraic methods, and applications in coding theory and graph theory. Education: B.Sc. in Mathematics, University of Tehran (1966) M.Sc. in Mathematics (Probability), Pahlavi University (1969) Ph.D. in Mathematics, University of Calgary (1975) Research Interests: His work centers on Hadamard matrices , orthogonal designs , and their applications. A notable contribution includes the introduction of "Bush-type" Hadamard matrices, which have shown connections to the energy of graphs. His investigations span classification problems, existence criteria, and constructions of these combinatorial objects. Grants and Funding: Kharaghani's research is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC). Recent grants include: "Orthogonal designs, Hadamard matrices and applications" (NSERC, $110,000 over 5 years) Publications: His recent work (2020–2023) delves into advanced topics such as projective plane-related Hadamard matrices, optimal ternary codes, and quasi-balanced weighing matrices, published in leading journals like Journal of Combinatorial Theory, Series A and Designs, Codes and Cryptography . Editorial Roles: He serves as an Honorary Editor for the Journal of Combinatorial Designs and as a member of the Editorial Board for Contributions to Discrete Mathematics .

K. R Arunمشاهده پروفایل

دانشیار

• Hyperbolic systems of conservation laws
• Asymptotic preserving schemes
• Genuinely multidimensional numerical schemes
• +۳ مورد دیگر

K. R. Arun is an Associate Professor at the School of Mathematics, Indian Institute of Science Education and Research Thiruvananthapuram . His research focuses on hyperbolic conservation laws , asymptotic preserving schemes , and nonlinear wavefront propagation . He has held prestigious positions including an Alexander von Humboldt Fellowship and has contributed to multidimensional numerical methods for fluid dynamics. PhD in Mathematics from Indian Institute of Science, Bangalore M.Sc. in Mathematics from Indian Institute of Technology Madras His work spans numerical analysis , partial differential equations , and computational fluid dynamics , with a focus on developing schemes for shallow water flows , acoustic waves , and gas dynamics . Publications highlight applications in heterogeneous media and low Froude number flows . Scientific awards include the Martin Forster Medal for his PhD thesis and a DST-DAAD joint research grant . He has collaborated with institutions in Germany and contributed to advanced numerical algorithms.

Carl Ollivier-Goochمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Algorithm Development for CFD
• Applied Aerodynamics
• +۵ مورد دیگر

Carl Ollivier-Gooch is a Professor and Associate Head of Equity, Diversity, Inclusion, Indigeneity & Engagement at the Department of Mechanical Engineering, Faculty of Applied Science, University of British Columbia (UBC). His research focuses on computational fluid dynamics, particularly algorithm development for computational aerodynamics, high-order accurate methods, unstructured mesh adaptation, and error assessment and control. Dr. Ollivier-Gooch received his B.A. in Russian and B.S.M.E. from Rice University, followed by M.S. and Ph.D. degrees from Stanford University. He is a Member of ASME, Senior Member of AIAA, and Member of the Canadian CFD Society. His educational background combines engineering expertise with strong mathematical foundations. Dr. Ollivier-Gooch's research spans multiple critical areas in computational fluid dynamics. His work on algorithm development aims to combine the geometric flexibility of unstructured mesh methods with the accuracy benefits of high-order methods. He has developed highly efficient, high-order accurate methods for inviscid compressible aerodynamics problems, demonstrating that high-order methods can achieve engineering accuracy more quickly than second-order methods. His research group also studies unstructured mesh generation, developing techniques for mesh improvement and refinement, particularly for anisotropic meshes used in high Reynolds number viscous flows. Additionally, his work on error assessment and control seeks to provide known error bounds for CFD simulations, improving understanding of error for unstructured mesh finite volume methods. His research on stability and convergence addresses problems where aerodynamics simulations don't converge properly to steady-state. Analysis of Dr. Ollivier-Gooch's recent publications reveals a strong focus on numerical stability, mesh optimization, and high-order methods in computational fluid dynamics. His work consistently addresses challenges in unstructured mesh methods, with particular emphasis on improving stability, convergence rates, and error estimation. The research shows a progression toward more sophisticated techniques combining traditional numerical methods with machine learning approaches for mesh optimization and stability improvement. His recent work has increasingly integrated modal analysis and machine learning techniques to identify problematic mesh features and improve solution convergence. Member ASME Senior Member AIAA Member Canadian CFD Society Dr. Ollivier-Gooch leads the ANSLab (tetra.mech.ubc.ca/ANSLab), which has developed a widely used software library for unstructured mesh generation that has been downloaded by over 6000 users in 62 countries since 1998. His research group develops techniques that take advantage of both the geometric flexibility of unstructured mesh methods and the accuracy benefits of high-order methods. They have written and maintain a software library for unstructured mesh generation that has been freely available for non-profit use since January 1998, now in its tenth version, with applications spanning fluid and solid mechanics, cancer research, microbiology, and simulation of star and planet formation.