جست‌وجوی استاد و پژوهشگر

• Computational Complexity
• Logic in Computer Science
• Proof Complexity
• +۴ مورد دیگر

Nicola Galesi serves as an Associate Professor in the Department of Computer, Control and Management Engineering (DIAG) at Sapienza University of Rome since 2022, following 17 years in Sapienza's Department of Computer Science (2005-2022). His academic journey began with an Associate Professorship at Universitat Politecnica de Catalunya (2001-2005) after postdoctoral positions at the Institute for Advanced Studies in Princeton (2000-2001) and University of Toronto (2002-2003) under Stephen Cook and Toni Pitassi. His educational background features a PhD from Universitat Politecnica de Catalunya supervised by Maria Luisa Bonet, complemented by dual Italian habilitations as full professor in Mathematical Logic (2012) and Computer Science. These qualifications underpin his rigorous theoretical approach across research domains. Galesi's research program centers on Computational Complexity and Logic in Computer Science , with specialized expertise in Proof Complexity (investigating resolution refinements and algebraic proof systems), SAT-Solving , Optimization , and applied domains like Group Testing and Network Tomography . His seminal work on space complexity in algebraic proof systems (JACM 2015) established foundational frameworks, while recent network tomography research develops mathematical models for node failure identification in communication networks using Boolean algebra and graph connectivity principles. Analysis of his 15 most recent publications (2022-2025) reveals a cohesive research trajectory bridging theoretical proof complexity and practical network analysis. Key trends include depth lower bounds in stabbing planes for combinatorial principles, vertex-connectivity metrics for failure localization, and algebraic investigations of vanishing sums in polynomial calculus. His work consistently applies combinatorial principles to derive tight bounds across graph structures while advancing the theoretical understanding of proof systems through tensor isomorphism and roots of unity analyses. His scientific recognition includes: ACM Computing Review Most Notable paper in Theory of Computing for 2012 Galesi mentors the next generation through PhD supervision of Massimo Lauria (2009), Ilario Bonacina (2015), and Fariba Ranjbar (2021), while hosting postdocs including Alan Skelley, Olaf Beyersdorff, and Massimo Lauria. His research is amplified through prestigious visiting positions at the Simons Institute for Theory of Computing (2015, 2021) and Tokyo Institute for Technology (2015), building on his foundational work at IAS Princeton and Toronto. He actively shapes the theoretical CS landscape as organizer of the Sapienza LOC3 (Logic, Complexity, Combinatorics, Computability) seminar series and founder of the RaTLoCC workshops (Ramsey Theory in Logic, Complexity and Combinatorics). His editorial role for Logical Methods in Computer Science (LMCS) and program committee service for CIAC, IJCAI, and FSTTCS conferences demonstrate sustained community leadership beyond his core research and teaching responsibilities in Calculus, Mathematical Logic, and Computational Complexity.

Naoki Yamamotoمشاهده پروفایل

استادیار

• Graph Pattern Matching
• Static Type Checking
• Graph Rewriting Languages
• +۴ مورد دیگر

Naoki Yamamoto is an Assistant Professor (non-tenure lecturer) at Waseda University's School of Fundamental Science and Engineering, Department of Computer Science and Engineering since April 2025. He also holds a part-time lecturer position at the University of Tokyo's College of Arts and Sciences (Junior Division) since October 2025. Previously, he served as a Research Associate at Waseda University from April 2022 to March 2025. He received his Doctor of Engineering from Waseda University in March 2025, following his Master of Engineering (2021) and Bachelor of Engineering (2019) from the same institution. Dr. Yamamoto's educational background is impressive, having earned his Bachelor's, Master's, and Doctoral degrees consecutively from Waseda University's School of Fundamental Science and Engineering. During his doctoral studies under Professor Kazunori Ueda, he focused on advanced topics in programming languages and graph theory. He was awarded the Outstanding Student Award (Dean's Award) from Waseda University in March 2019. His research interests center around graph-based programming language theory, with particular expertise in Graph Pattern Matching , Static Type Checking for complex data structures , and Graph Rewriting Languages . He has developed innovative approaches to handling graph structures that go beyond traditional algebraic data types like lists and trees. His work bridges theoretical computer science with practical implementation, focusing on how to safely manipulate complex graph structures in programming languages. His publication record demonstrates consistent advancement in graph-based type systems. Starting with foundational work on static type checking for graph operations (2019), he progressed to handling numeric constraints (2020), extending type expression power (2022), and developing grammar-based approaches for difference data structures (2024). His research shows a clear trajectory from theoretical foundations to practical applications, with increasing sophistication in handling complex graph structures. His work on LMNtal ShapeType represents a significant contribution to the field of graph rewriting languages. Outstanding Student Award (Dean's Award), Waseda University (2019) Dr. Yamamoto has been actively involved in teaching and research supervision, having served as a Teaching Assistant for 14 courses between 2018-2021. He currently teaches Introduction to C Programming and C Application Development at Waseda University, and Introduction to Algorithms at the University of Tokyo. He has received research funding through the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research, collaborating with Professor Kazunori Ueda on projects related to high-level languages with powerful data structures and concurrency. As a member of Ueda Laboratory at Waseda University, Dr. Yamamoto has contributed to the development of tools like Lambda Friends, a web-based interpreter for lambda calculus written in TypeScript. His research group focuses on advancing programming language theory, particularly in the areas of graph rewriting and type systems, with applications in both programming languages and modeling languages. His work demonstrates how graph rewriting languages can unify program execution and model checking functionalities while guaranteeing well-formedness of graph structures.

V. Arvindمشاهده پروفایل

استاد

• Computational Complexity Theory
• Structural Complexity
• Randomized Computation
• +۵ مورد دیگر

V. Arvind is a Professor in the Theoretical Computer Science faculty at the Institute of Mathematical Sciences (IMSc) , Chennai. His research is centered on computational complexity theory, with a focus on structural complexity, randomized and algebraic computation, and quantum information and computation. He explores the deep connections between theoretical computer science and mathematics. Institution: Institute of Mathematical Sciences (IMSc), Chennai School: Theoretical Computer Science Academic Rank: Professor Arvind's research interests include computational complexity, structural complexity theory, algebraic computation, derandomization, and quantum computing. He is particularly interested in the interplay between mathematical structures and computation. His work often bridges theoretical computer science with algebra, combinatorics, and logic. His recent publications, primarily expository articles in the EATCS Bulletin’s Computational Complexity Column, cover a wide range of topics such as robust oracle machines, the Alon-Roichman theorem, noncommutative arithmetic circuits, graph isomorphism, and quantum computation. These works reflect trends in foundational complexity theory, algebraic methods in computation, and the exploration of quantum models. The articles emphasize structural insights, lower bounds, and connections to mathematical disciplines. Professional Service and Editorial Roles: Associate Editor, ACM Transactions on Computation Theory Editor, EATCS Computational Complexity Column (since June 2011) Editorial Board Member, International Journal of Computer Mathematics (2009–2013) Co-organizer, ICM Satellite Conference on Algebraic and Probabilistic Aspects of Combinatorics and Computing Program Committee Member for WALCOM 2014, STACS 2012, COCOON 2009, FSTTCS (multiple years, including chair roles), CCC 2006, INDOCRYPT (2002, 2005), and others Teaching: Arvind has taught advanced courses including Computational Complexity, Algorithms, Algebra and Computation, and Discrete Mathematics, often based on foundational texts and notes from leading experts. Lecture notes from his courses have been compiled by students and collaborators. Collaborations: He has an extensive list of co-authors, including prominent researchers such as Manindra Agrawal, Eric Allender, Johannes Köbler, Meena Mahajan, Jacobo Torán, and Ramprasad Saptharishi, indicating strong collaborative research networks in complexity theory and algorithms.

• Graph Neural Networks
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Fabian Jogl is a PreDoc Researcher at the Vienna University of Technology (TU Wien) within the Faculty of Informatics, holding dual affiliations in the Department of Databases and Artificial Intelligence (Institute E192) and the Department of Machine Learning (Institute E194). His work centers on theoretical and applied aspects of graph neural networks under the StruDL (2023–2027) and VHH (2019–2023) research projects. His research focuses on the expressivity limits of graph neural networks, particularly investigating whether enhanced expressivity translates to better predictive performance. Key areas include outerplanar graph analysis, path-based GNN architectures, global feature integration, and connections to the Weisfeiler-Lehman hierarchy. He examines structural properties of GNNs through homomorphisms and graph transformations to advance graph representation learning. Recent publications reveal trends toward unifying theoretical expressivity frameworks with empirical validation across diverse graph datasets. His work bridges geometric deep learning for cell complexes and practical applications like historical film analysis via the Historian dataset. Jogl actively contributes to major conferences including NeurIPS, ICML, and LoG while co-supervising student projects in machine learning algorithms. As a core member of the StruDL project, he investigates deep learning model structures for graph data, extending prior work on historical film annotation under the VHH project. His technical contributions include novel GNN simulation techniques and methods for enhancing message-passing architectures through graph transformations.

• Graph Drawing
• Information Visualization
• Visual Analytics
• +۳ مورد دیگر

Professor Seokhee Hong is a distinguished academic at the School of Computer Science, The University of Sydney. With prestigious appointments including an ARC Future Fellowship (2013-2016) and Humboldt Fellowship (2013-2014), she has emerged as a leading researcher in graph drawing and visual analytics. Her research focuses on developing scalable algorithms for information visualization of massive complex networks, with applications spanning security analytics, computational biology, and software engineering. Key contributions include the creation of open-source visual analytics software GEOMI and foundational work in 2.5D graph visualization. 2013-2016: ARC Future Fellowship 2008-2012: ARC Research Fellowship 2013-2014: Humboldt Fellowship Recent publications demonstrate her ongoing innovation in graph drawing algorithms, network fairness, and computational geometry. She has served on editorial boards of key journals and as program chair for major conferences in her field. 2006: CORE Chris Wallace Award 2012: Eureka Prize Finalist Multiple Graph Drawing Competition wins Her work bridges theoretical algorithm development with practical applications, addressing challenges in biological network analysis, dynamic graph visualization, and cluster-preserving layouts. With over 140 publications and significant research funding, she continues to shape network visualization research.

Nicholas Touikanمشاهده پروفایل

دانشیار

• Geometric Group Theory
• Algorithmic Group Theory
• Low-dimensional Topology
• +۲ مورد دیگر

Nicholas Touikan is Associate Professor in Mathematics and Statistics at the University of New Brunswick, specializing in geometric group theory. His research examines groups as geometric objects, focusing on computational problems in infinite discrete groups exhibiting large-scale curvature properties. Primary investigations develop algorithms for group-theoretic problems using geometric insights from hyperbolic and negatively curved groups. Complementary research applies low-dimensional topology techniques to analyze group structures and actions. Current projects include solving conjugacy problems for automorphism groups and developing efficient folding algorithms for virtually free groups.

Christino Tamonمشاهده پروفایل

استاد

• Theoretical Computer Science
• Quantum Computing
• Machine Learning
• +۳ مورد دیگر

Christino Tamon is a Professor of Computer Science at Clarkson University's Coulter School of Engineering & Applied Sciences. He holds a Ph.D. from the University of Calgary (1993-1996), an M.S. from the University of Toronto (1990-1992), and a B.Sc. in Computer Science and Applied Mathematics from the University of Calgary (1986-1990). His research focuses on theoretical computer science, quantum computing, graph theory, and machine learning, with notable contributions to quantum state transfer and quantum walks on graphs. Recipient of the Clarkson University Distinguished Teaching Award (2009) and New Teacher Award (2000). Principal Investigator on multiple NSF grants, including quantum computing and REU mathematics programs. Visiting appointments at institutions like the Institut Henri Poincaré and the University of Waterloo. Research interests include quantum algorithms, graph spectral theory, and the application of algebraic methods to discrete systems. His work on quantum walks explores perfect state transfer, fractional revival, and spatial search optimization. Recent grants support quantum advantage in algorithm design and interdisciplinary research in quantum dynamics. Advised numerous graduate students and mentors undergraduate research through REU programs. Active in professional service, including organizing workshops on quantum mathematics and algebraic graph theory.

Mikael Pichotمشاهده پروفایل

دانشیار

• Geometric Group Theory
• Analysis
• Group Theory
• +۳ مورد دیگر

Mikael Pichot is an Associate Professor in the Department of Mathematics and Statistics at McGill University, located in Montreal, Quebec. His research focuses on Geometric Group Theory, Analysis, and related areas such as Operator Algebras and Metric Geometry. He is actively involved in organizing academic events and seminars, including the Group Theory Seminar and CRM-ISM Colloquium, and has contributed to numerous collaborations, often with co-authors like Sylvain Barre and Robert Graham. His teaching includes courses such as Math 223 (Linear Algebra) and Math 570/571 (Higher Algebra sequences). Pichot's research interests span topics like geometric group actions, sofic dimension, L2 invariants, and random groups. He has published extensively in peer-reviewed journals and presented at international conferences. His work often bridges algebraic, geometric, and analytic approaches to group theory. Despite his active academic contributions, no specific awards or grants are explicitly listed in the provided texts. He maintains a personal webpage and collaborates on projects such as 'Surgery on discrete groups' and 'Random groups and nonarchimedean lattices.' His research also touches on foundational questions in operator algebras and geometric topology, reflecting a deep engagement with the structural properties of groups and their applications.

Oded Yacobiمشاهده پروفایل

دانشیار

• Representation Theory
• Algebraic Groups
• Categorification
• +۳ مورد دیگر

Associate Professor Oded Yacobi is affiliated with the University of Sydney's Faculty of Science. His research focuses on advanced algebraic structures, including representation theory, categorification, and geometric methods in quantum groups. He holds a Ph.D. from the University of California, San Diego (2009), followed by postdoctoral roles at the University of Toronto and Tel Aviv University. Yacobi is actively involved in grants exploring dualities in representation theory and braid group dynamics. His work bridges algebraic geometry and combinatorics, with recent articles addressing Weyl groups, braid group actions, and affine Grassmannians. He leads a vibrant research program with collaborations spanning North America and Australia. Education: Ph.D. in Mathematics, University of California, San Diego (2009) Postdoctoral Fellowships: University of Toronto, Tel Aviv University Research Interests: Representation theory of algebraic groups and quantum groups Categorification techniques and their applications Geometric methods in Lie theory and combinatorics Braid groups and their algebraic structures Key Grants: 2023: ARC DP Grant (Braid groups via representation theory and machine learning) 2018: ARC DP Grant (New Dualities in Modular Representation Theory) Professional Activities: Maintains an active research group and collaborates internationally. His work has been published in top journals like Mathematische Zeitschrift and Advances in Mathematics. He is also engaged in teaching advanced algebra courses at the University of Sydney.

• Artificial Intelligence
• Machine Learning
• Social Network Analysis
• +۴ مورد دیگر

Andreas Kaltenbrunner is a Part-Time Lecturer at the Universitat Pompeu Fabra (UPF) in Barcelona, specializing in Data Driven Social Analytics and Information Retrieval. He serves as Director of Research on AI and Data Science at IN3 - UOC R&I and is an Affiliate Researcher at ISI Turin, Italy. His research focuses on computational social science, user behavior analysis, and applications of AI/ML in social media and network dynamics. Key interests include large language models (LLMs), personality assessment simulations, and digital epidemiology. His work bridges theoretical frameworks with practical applications, such as predicting urban mobility patterns and evaluating AI systems’ performance in political contexts. He collaborates with institutions like UNICEF and the ISI Foundation, contributing to projects on data-driven decision-making and social impact. His interdisciplinary approach integrates network science, computational methods, and socio-cultural analysis. Recent publications highlight innovations in LLM validation, cross-lingual Wikipedia reliability modeling, and climate-related forecasting. While no explicit awards are listed, his prolific output reflects sustained contributions to computational social science and AI ethics.

Bojan Moharمشاهده پروفایل

استاد

• Topological Graph Theory
• Graph Minors
• Graph Coloring
• +۳ مورد دیگر

Bojan Mohar is a Professor in the Department of Mathematics at Simon Fraser University (SFU), within the Faculty of Science. He holds a Ph.D. in Mathematics from the University of Ljubljana, Slovenia (1986). His research focuses on advanced topics in graph theory, including topological graph theory (graphs on surfaces, planar graphs), graph minors, graph coloring (list coloring, edge-coloring, nowhere-zero flows), algebraic graph theory (Laplace eigenvalues, spectral analysis), and graph algorithms. Mohar's work bridges theoretical foundations with computational methods, emphasizing interdisciplinary applications. His research interests span diverse areas such as the spectral properties of infinite graphs, graph embeddings, and combinatorial optimization. He is affiliated with the Centre for Operations Research and Decision Sciences (CORDS) at SFU. Mohar has made significant contributions to understanding graph structures, eigenvalues, and algorithm design, with a particular emphasis on topological and algebraic aspects. His recent work includes proofs of long-standing conjectures in graph theory and the development of efficient approximation algorithms for graph genus calculations. Mohar’s academic contributions are reflected in his extensive publication record, focusing on graph minors, eigenvalue analysis, and topological embeddings. He teaches courses such as MATH 345 D100: Introduction to Graph Theory (Fall 2025). No formal advising relationships or awards are explicitly listed in the provided materials, though his research impact is evident through collaborations and symposium participations like the International Symposium on Computational Geometry (SoCG).

Stephen Kobourovمشاهده پروفایل

استاد

• Algorithm Design
• Computational Geometry
• Graph Drawing
• +۳ مورد دیگر

Prof. Stephen Kobourov is a Professor in the TUM School of Computation, Information and Technology at Technische Universität München (TUM). Previously, he held positions at the University of Arizona from 2000 to 2024, progressing from Assistant Professor to Full Professor, and served as Deputy Director of the Data Science Institute. His expertise lies in algorithm design, computational geometry, and graph visualization, with over 250 publications and significant funding from NSF, ONR, and USDA grants. Education: BS in Computer Science and Mathematics from Dartmouth College (1995), PhD in Computer Science from Johns Hopkins University (2000). Research focuses on efficient algorithms for graph drawing, visualization techniques for networks, and geometric algorithms. Notable contributions include work on stress metrics in graph layouts, hypergraph representations, and non-Euclidean visualization frameworks. He has co-chaired committees for ALENEX, IEEE PacificVis, and GD, and serves as an editor for JGAA, CGTA, and IEEE TVCG. Awards include the Fulbright Distinguished Chair (2015–2016), Humboldt Research Fellowship (2011–2014), and NSF Career Award (2006–2011). His recent work explores multi-layer network visualization, AI-driven graph analysis (e.g., MLLMs perception), and graph embeddings in non-Euclidean spaces. Advising and grants: Extensive grants from NSF and other agencies support his research. He has advised numerous students and collaborates internationally, contributing to labs like the Data Science Institute and initiatives such as the Institutional Knowledge Map (KMAP). Visualization projects include MetroSets (metro map-style set visualization), Wooly Graphs (knitting pattern frameworks), and tools for interactive network analysis. His work bridges theoretical algorithms with practical applications in science and technology.

• Graph Theory
• Operations Research
• Discrete Mathematics
• +۳ مورد دیگر

Dr. Maximilian Fürst is a researcher at the Institute of Optimization and Operations Research of the University of Ulm , focusing on graph theory, discrete mathematics, and algorithmic complexity. His work primarily investigates matching problems in graphs, including uniquely restricted matchings, induced matchings, and acyclic matchings, with applications in theoretical computer science and optimization. Research Interests: Graph Theory (matching theory, subcubic graphs, cycle-free graphs) Operations Research (approximation algorithms, linear programming) Computational Complexity (NP-hardness, graph invariants) Discrete Mathematics (combinatorics, degree sequences) Trends in Recent Publications: His publications emphasize theoretical analysis of graph problems, particularly matching-related algorithms and bounds. Key areas include hardness proofs, approximation methods, and extremal graph theory, with collaborations across European institutions. Teaching: He has taught courses such as Optimization and OR 2 and Graph Theory 2 at the University of Ulm since 2017. Collaborations: Regularly works with colleagues like Dr. Julien Baste, Prof. Dieter Rautenbach, and Prof. Michael A. Henning on graph theory and optimization challenges.

Sheldon Jacobsonمشاهده پروفایل

استاد

• Operations Research
• Optimization
• Probability
• +۳ مورد دیگر

Sheldon Jacobson is a Professor in the Department of Computer Science at the Siebel School of Computing and Data Science, University of Illinois at Urbana-Champaign. He holds cross-appointments in Electrical and Computer Engineering, Industrial and Enterprise Systems Engineering, Biomedical and Translational Sciences, Mathematics, and Statistics. His research spans operations research, optimization, probability, and applied mathematics, with applications in political redistricting, homeland security, stochastic processes, and societal problem-solving. Key focus areas include developing algorithmic frameworks for electoral fairness, optimizing complex systems, and advancing computational solutions for public policy challenges. Recent publications demonstrate strong emphasis on redistricting algorithms, optimization methodologies, and computational social science, with consistent applications in political systems and security domains.

• Algebraic Geometry
• Commutative Algebra
• Combinatorial Algebra
• +۳ مورد دیگر

Francesc d'Assis Planas Vilanova is a Professor in the Department of Mathematics at the Polytechnic University of Catalonia (UPC), affiliated with the Faculty of Mathematics and Statistics. He is a core member of the GEOMVAP research group (Geometry of Varieties and Applications), focusing on Algebraic Geometry, Commutative Algebra, and Combinatorial Algebra. His research emphasizes the interplay between algebraic structures and geometric concepts, with contributions to topics like syzygetic ideals, Noetherian rings, and lattice ideals. Key publications include studies on Gorenstein syzygetic prime ideals, Jacobian divisors, and Rees algebras. His work bridges theoretical algebra with applications in combinatorial topology and graph theory. He has supervised at least one doctoral student, Ferran Muiños Ballester, whose thesis explores Rees algebras of equimultiple ideals. Planas Vilanova has secured grants through the Spanish and Catalan research agencies, contributing to projects like 'Geometria de Varietats i Aplicacions.' His research spans over three decades, with continuous contributions to algebraic theory and its applications.