جست‌وجوی استاد و پژوهشگر

Oriol Serraمشاهده پروفایل

استاد

• Combinatorics
• Graph Theory
• Combinatorial Number Theory
• +۵ مورد دیگر

Oriol Serra is a full professor of Applied Mathematics at the Department of Mathematics of the Universitat Politècnica de Catalunya (UPC) since 1999. He holds a PhD in Mathematical Sciences from UPC (1988) and a degree in Mathematics from the Universitat de Barcelona (1983). His primary research areas include combinatorics, graph theory, and combinatorial number theory, with a focus on isoperimetric problems, Ramsey Theory, extremal and probabilistic combinatorics, and additive combinatorics. He has held leadership roles such as Chair of the Department of Mathematics (2011–2017), Vice-Dean of Research at the School of Mathematics (2007–2011), and member of the Executive Committee of the Barcelona Graduate School of Mathematics (2012–2015). He has organized and participated in numerous international conferences and workshops, including the European Conference on Combinatorics (2017, 2019) and the British Combinatorial Conference (2019). His research spans foundational topics in discrete mathematics, with contributions to additive combinatorics, graph labeling, and probabilistic methods. Recent work includes studies on random walk mixing, Sidon set systems, and discrete Brunn-Minkowski inequalities. He has advised over 20 PhD students and numerous master’s students, contributing to the training of new researchers in combinatorics and theoretical computer science. His teaching includes courses on combinatorics, graph theory, and probability at the undergraduate and graduate levels at UPC. Oriol Serra is affiliated with the research group Geometric, Algebraic, and Probabilistic Combinatorics (GAPCOMB) and has been involved in multiple funded projects, including the Marie Curie fellowship GEOSUMSETS (2010–2012) and the Spanish-funded project GEOMETRÍA DISCRETA (2018–2020).

• Partial Differential Equations
• Nonlinear PDEs
• Nonlocal Equations
• +۹ مورد دیگر

Marcos Solera Diana is an Assistant Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, Universitat de València. His research lies at the intersection of partial differential equations, functional analysis, and applied mathematics, with a focus on nonlocal and nonlinear phenomena. His primary research interests include: Nonlinear and nonlocal partial differential equations Gradient flows in discrete and metric spaces Applications to image processing and clustering Geometric flows and inequalities Instability and non-uniqueness in fluid mechanics His recent publications, spanning from 2020 to 2023, demonstrate a consistent focus on PDEs in the context of metric random walk spaces and graphs. These works explore the heat flow, total variation flow, and doubly nonlinear diffusion, contributing to the theoretical understanding of evolution equations in discrete settings. The research trends indicate a strong foundation in analysis and a growing interest in connections with geometry and fluid dynamics. Marcos earned his PhD in 2021 from the Universitat de València with a thesis on Gradient flows in random walk spaces , supervised by Dr. José Manuel Mazón Ruiz and Dr. José Julián Toledo Melero. He is an active member of the EDPNOL (Nonlinear Partial Differential Equations) research group. He has collaborated extensively with researchers such as J. Julián Toledo and José M. Mazón Ruiz, resulting in publications in high-quality journals including Journal of Functional Analysis , Calculus of Variations and Partial Differential Equations , and Advances in Calculus of Variations .

Jose Julian Toledo Meleroمشاهده پروفایل

استاد

• Partial Differential Equations
• Nonlocal Diffusion
• Calculus of Variations
• +۷ مورد دیگر

Jose Julian Toledo Melero is a Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, Universitat de València. He is a leading researcher in nonlinear partial differential equations, with a focus on nonlocal diffusion, evolution equations, and optimal transport in metric random walk spaces. His work bridges pure and applied analysis, with strong collaborations with mathematicians such as José M. Mazón and Julio D. Rossi. His research interests include: Nonlinear Partial Differential Equations Nonlocal Diffusion and Operators Calculus of Variations and Optimal Transport Evolution Problems in Metric Spaces Geometric Analysis and Minimal Surfaces Doubly Nonlinear and Degenerate Equations The recent articles show a consistent focus on analytical and geometric properties of nonlocal models, particularly in discrete and metric random walk settings. His work frequently appears in top journals such as Calculus of Variations , SIAM Journal on Mathematical Analysis , and Journal of Evolution Equations , often in collaboration with leading experts. The publications reveal a deep engagement with both theoretical foundations and structural analysis of solutions. He has co-authored influential books such as Nonlocal Diffusion Problems (AMS, 2010) and Variational and Diffusion Problems in Random Walk Spaces (Birkhäuser, 2023), which are key references in the field. His research is highly cited, indicating significant impact in the mathematical community. He advises no publicly listed students in the provided data. There is no mention of specific grants or teaching roles, but his extensive publication record and book authorship reflect a sustained and high-level research career. He maintains an active research profile with upcoming events such as the 2025 CIMPA-UCA School on optimal transport and PDEs, suggesting ongoing leadership and contribution to the international mathematical community.

• Complex Networks
• Artificial Intelligence
• Urban Networks
• +۵ مورد دیگر

Dr. José Francisco Vicent Francés serves as an Associate Professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante's Higher Polytechnic School. He directs the Master's Degree in Data Science and leads the ANVIDA research group (Data Analysis and Visualization in Complex Networks), with active roles in teaching, research supervision, and interdisciplinary projects. His educational foundation includes a Doctorate in Computer Engineering and Computing from the University of Alicante (2007) and a Degree in Physical Sciences from the Complutense University of Madrid (1987), specializing in Automatic Computing. Research focuses on complex network analysis, AI applications in urban systems, and evolutionary algorithms for simulation. His work bridges theoretical computer science with practical urban challenges, emphasizing data visualization and spatio-temporal modeling. Recent efforts target explainable AI frameworks and network-based approaches to environmental and transportation problems. Current publications (2024-2025) reveal strong interdisciplinary trends: deep learning models for urban noise pollution, traffic accident forecasting, and carbon concentration monitoring using graph-based spatio-temporal methods. These works integrate computer science with environmental science and urban planning, demonstrating consistent innovation in network analysis and AI-driven prediction systems. Dr. Vicent has directed four doctoral theses and 17 master's/undergraduate theses in the past five years. His research funding includes seven public projects since 2020, notably the ongoing 'Development of AI and Complex Networks Techniques for Urban Sustainability Management' (2024-2025) and the 'Data Analysis for COVID-19 Prevention' initiative. As director of the ANVIDA research group, he fosters collaborations across computer science, urban planning, and environmental sciences, maintaining strong ties with municipal authorities and international research teams through projects like the 'City as a Multiple Data Network' study.

• Combinatorics
• Extremal Combinatorics
• Geometric Combinatorics
• +۳ مورد دیگر

Richard Johannes Lang is a Researcher 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 GAPCOMB research group specializing in Geometric, Algebraic, and Probabilistic Combinatorics, contributing to UPC's prominence in discrete mathematics. His research centers on Combinatorics with deep expertise in Extremal, Geometric, Algebraic, and Probabilistic subfields. He investigates structural graph properties, tiling problems, and combinatorial designs using probabilistic frameworks and computational methodologies, addressing fundamental theoretical challenges. Lang's recent work on perfect mixed tilings exemplifies his integrative approach, merging geometric constraints with randomness to establish new existence conditions in combinatorial structures. Scientific recognition: Ramon y Cajal Fellowship He secured competitive funding including a Ramon y Cajal Fellowship with additional grant and participation in the R&D project "Structure, Randomness and Computational Methods in Extremal Combinatorics". Lang also supervises predoctoral researchers, evidenced by his role in the Ministry of Spain Predoctoral Grant (2024) for Antonio Kaique Barroso Fernandes. Lang actively collaborates within the GAPCOMB group and internationally with researchers including Rue, Perarnau-Llobet, Serra, Hurley, and Joos, driving innovative combinatorial research at UPC.

FERNANDO ALCALDE CUESTAمشاهده پروفایل

استاد

• Geometry and Topology
• Dynamics of groups
• Foliations and dynamical systems
• +۴ مورد دیگر

Fernando Alcalde Cuesta is a Professor at the Department of Mathematics, Faculty of Mathematics, University of Santiago de Compostela. He is affiliated with the Galician Mathematical Research and Technology Center (CITMAga) and actively engages in interdisciplinary research at the intersection of geometry, topology, and dynamical systems. Educational Background: PhD, University of Santiago de Compostela (1990), thesis: Symplectic integration of Riemannian Poisson manifolds PhD, Université Claude Bernard Lyon 1 His research focuses on topological and measurable dynamics, including group dynamics, foliations, negative curvature systems, and evolutionary dynamics on complex networks with applications in systems biology. He has organized and participated in numerous geometry and topology seminars and colloquia, such as the Atlantic Geometry Seminar and the Spanish Topology Network. Scientific Activities: Coordinator, Scientific Committee of the Spanish Topology Network (2019) Member, Scientific Committees of Spanish Topology Network (2018–2020), IMAT (2018–2021), and GDR PLATON CNRS (2010–present) Research projects: Dinámica de grupos, grafos y foliaciones (MTM2016-77642-C2-2-P, 2017–2019) and others Collaborations: Gilbert Hector, Alberto Verjovsky, Françoise Dal'Bo, Matilde Martínez, and members of the BioMatDataAnalysis group in systems biology.

Jesús Giráldez Crúمشاهده پروفایل

پژوهشگر ارشد

• satisfaction and optimization problems
• complex networks
• agent-based modeling
• +۲ مورد دیگر

Jesús Giráldez Crú is a Research Fellow holding a Juan de la Cierva postdoctoral fellowship at the University of Granada, Spain. He is affiliated with the Department of Computer Science and Artificial Intelligence within the School of Computer Science and Telecommunications Engineering and contributes to the Andalusian Research Institute in Data Science and Computational Intelligence. He leads the SOCCER Lab (SOft Computing applications for Complex EnviRonments) under Oscar Cordón in the Soft Computing and Intelligent Information Systems research group. He earned his PhD in Computer Science (2016) from the Autonomous University of Barcelona, conducted at the Artificial Intelligence Research Institute (IIIA-CSIC). His academic background includes a BsC in Software Engineering and Computer Science (2010) and MsC in Computation, Logics and Artificial Intelligence (2011), both from the University of Seville, followed by postdoctoral work at the Royal Institute of Technology (KTH) in Stockholm. His research centers on satisfaction and optimization problems, complex networks, agent-based modeling, complex systems, and deep learning. He applies soft computing methodologies to address challenges in complex environments, with emphasis on graph feature analysis for SAT instances and random network modeling. His work bridges theoretical computer science and practical AI applications. Dr. Giráldez Crú has co-authored over 30 publications in top venues including Artificial Intelligence, IJCAI, and SAT conferences. His scientific recognition includes the competitive Juan de la Cierva fellowship, and he serves on Program Committees for IJCAI and AAAI conferences. He actively mentors through his research but lists no formal advisees. His work is supported by the Juan de la Cierva fellowship and collaborative grants within the SCI2S group. He develops open-source tools like GraphFeatSAT and random network models (Community Attachment, Popularity-Similarity, B2B) for complex system analysis. As an invited lecturer, he teaches in the Master's in Artificial Intelligence Research (Spanish Association for Artificial Intelligence) and Master's in Data Science and Big Data (University of Seville), extending his expertise beyond UGR.

Laurent Feuilloleyمشاهده پروفایل

پژوهشگر

• Distributed Computing
• Graph Theory
• Algorithms
• +۴ مورد دیگر

Laurent Feuilloley is a junior CNRS researcher (Chargé de recherche) at LIRIS, Université de Lyon 1 since 2022. He previously held postdoctoral positions at LIRIS, Universidad de Chile, and LIP6 at Sorbonne Université. His research focuses on Distributed Computing , Graph Theory , and Local Certification , with applications in Fault-Tolerant Systems and Algorithm Engineering . He collaborates extensively with researchers like Nicolas Bousquet, Franck Petit, and José Correa. Education: PhD in Computer Science (2018) at IRIF, Université Paris Diderot, supervised by Pierre Fraigniaud. Research: Works on graph algorithms, certification, and robustness in dynamic networks, with a focus on maximal independent sets and self-stabilizing systems. Scientific Contributions: His publications include lower bounds for local certification, robustness refinements in dynamic networks, and space complexity for leader election algorithms. He has received multiple Best Paper Awards at SAND 2023 and SSS 2022 Best Student Paper at OPODIS 2021 Best Reviewer Award at DISC 2020 Advising: Currently supervising Sébastien Zeitoun's PhD (co-advised with Nicolas Bousquet and Éric Duchêne) and Antonin Kiladjian's M1 internship (with Théo Pierron). He has also advised Guillermo Dinamarca's master thesis in 2019-2020.

• Theoretical Computer Science
• Algorithm Design
• Distributed Computing
• +۳ مورد دیگر

Yannic Maus is a Professor at the Faculty of Computer Science and Biomedical Engineering at Graz University of Technology (TU Graz), Austria, where he heads the Institute of Algorithms and Theory (founded in 2025). He is also a co-leader of one of the five Fields of Expertise (FoE) at TU Graz, specifically in Information, Communication & Computation. Dr. Maus received his PhD from the Algorithms and Complexity group at the University of Freiburg (Germany) under the supervision of Fabian Kuhn. Prior to joining TU Graz, he was a postdoctoral researcher at the Technion in Israel in the group of Keren Censor-Hillel. His research focuses on theoretical computer science and algorithm design, particularly problems arising in distributed computing. He is fascinated by clean mathematical questions and the techniques involved in solving them, especially when these questions are motivated by real-world systems. His specific interests include distributed graph algorithms, efficient algorithms, data structures, complexity theory, and geometric algorithms. Dr. Maus's work bridges theoretical foundations with practical applications in large-scale networked systems. Analysis of his recent publications reveals a strong emphasis on distributed algorithms for graph problems, with significant contributions to graph coloring, symmetry breaking, and vertex cover problems across various computational models. His research demonstrates increasing focus on massively parallel computation (MPC) models alongside traditional distributed computing frameworks, addressing challenges related to bandwidth limitations, memory constraints, and adaptive algorithms. The interdisciplinary nature of his work connects theoretical computer science with practical system constraints. GI Dissertationspreis 2018 Wolfgang-Gentner-Nachwuchsförderpreis 2019 2020 Principles of Distributed Computing Doctoral Dissertation Award Best Paper Award at PODC 2016 Best Paper Award at SIROCCO 2016 Best Paper Award at DISC 2017 Dr. Maus actively mentors students at all levels, offering bachelor's and master's theses as well as PhD positions in his research group. His research is supported by multiple competitive grants including FWF grants P36280-N (2023-2027), DOC 183 (2024-2028) and I6915 (2024-2028), and FFG grant No. 59263962. His group maintains strong international collaborations with research teams across Germany, Finland, Iceland, and Israel, facilitating knowledge exchange and joint research initiatives. The group provides fully funded PhD positions with excellent working conditions, including competitive salaries and travel support. The Institute of Algorithms and Theory, under Dr. Maus's leadership, is part of TU Graz's rapidly growing Faculty of Computer Science and Biomedical Engineering. The research group maintains an inclusive environment that actively encourages women to apply and supports work-life balance for all members. Located in Graz, Austria's second-largest city, the institute benefits from the city's high quality of life, cultural vibrancy, and proximity to both the Alps and Mediterranean regions, providing an excellent environment for academic work and personal life.

• Proof Complexity
• Computational Complexity
• Algorithmics
• +۵ مورد دیگر

Ilario Bonacina is a Lecturer at the Department of Computer Science within the College of Computer Science of Barcelona (FIB) at the Polytechnic University of Catalonia . His research focuses on Proof Complexity , Computational Complexity , and Algorithmics , particularly in Polynomial Calculus and MaxSAT Optimization . Education: Laurea in Mathematics, Laurea Specialistica in Mathematics, and Doctorate from UPC. Research Interests include proof systems (Sherali-Adams, Nullstellensatz), algebraic methods, and theoretical computer science. Recent publications analyze complexity bounds and optimization algorithms. Scientific Awards include recognition for Best Italian PhD Theses in Theoretical Computer Science. He participates in competitive R+D+i projects like the State Plan for Scientific Research and Innovation.

• Discrete Mathematics
• Matrix Analysis
• Potential Theory
• +۳ مورد دیگر

Maria Jose Jimenez is a Professor at the Department of Mathematics in Universitat Politècnica de Catalunya (UPC) , affiliated with the MAPTHE (Matrix Analysis and Discrete Potential Theory) and OMGRAPH (Optimization Methods on Graphs) research groups. Her work bridges discrete potential theory, matrix analysis, and biomedical applications, particularly in network modeling and inverse problems. Her research focuses on the intersection of discrete mathematics , linear algebra , and medical imaging , with recent publications analyzing M-matrices , Laplacian networks , and 3D breast models for early cancer detection. She has developed patents for impedance estimation in biological tissues and contributes to educational innovation in engineering. Scientific collaborations include co-authors like A. Carmona , A. Encinas , and E. Monso , with projects funded under Spain’s R+D+i programs. Her 15 most recent works highlight advancements in random walk metrics , spectral analysis , and medical device prototyping , particularly in spider and network geometries.

Cameron Freerمشاهده پروفایل

پژوهشگر

• Probabilistic Computing
• Random Structures
• Mathematical Logic
• +۴ مورد دیگر

Cameron Freer is a Research Scientist at the Massachusetts Institute of Technology's Probabilistic Computing Project. His academic career spans multiple institutions including Keio University, Harvard University, and University of Hawaii at Manoa, with roles ranging from Postdoctoral Fellow to Project Associate Professor. Current affiliation: MIT Probabilistic Computing Project Past academic roles: Keio University SFC (2021–2024), MIT Brain and Cognitive Sciences (2013–2015), MIT Mathematics (2008–2010) Research interests focus on probabilistic computing , random structures , and their intersections with logic, mathematics, and artificial intelligence. Key contributions include foundational work on Markov categories , graphons , and feedback computability . Recent publications explore probabilistic programming systems , random graph modeling , and computable aspects of measure theory . Collaborators include prominent researchers from Harvard, Oxford, and MIT. Professional engagements include committee memberships in major conferences like POPL (2024), LAFI (2024–2025), and PLDI (2024). Holds PhD in Mathematics from Harvard University (2008).

• Natural Language Processing
• Artificial Intelligence
• Data Science
• +۳ مورد دیگر

Jorge Turmo Borras es profesor del Departament de Ciències de la Computació en la Universitat Politècnica de Catalunya. Forma part del Grup de Processament del Llenguatge Natural (GPLN) i del Centre de Tecnologies i Aplicacions del Llenguatge i la Parla (TALP). Su investigación se centra en procesamiento del lenguaje natural, inteligencia artificial y minería de datos clínicos. Investigación: NLP, Deep Learning, Salud Digital Colaboraciones: IDEAI-UPC, XarTEC Salut Sus intereses principales incluyen extracción de información de documentos médicos, resolución de anáforas mediante hipergrafos, y normalización léxica de microtextos. Ha publicado sobre modelado de temas para enlazado de entidades y detección de negaciones en textos clínicos. En los últimos 5 años ha trabajado en sistemas de asistencia para diagnóstico , procesamiento de tweets médicos , y redes neuronales para historiales de salud . Sus artículos destacan aplicaciones de Transformers, CRF y modelos híbridos. Patrocinadores: HORIZON 2020, Plan Estatal de Investigación 2021-2023, RIS3CAT. Colabora con investigadores como Alicia Ageno, Lluís Padró y Horacio Rodríguez-Hontoria.

Ramon Ferrer-i-Canchoمشاهده پروفایل

دانشیار

• Quantitative Linguistics
• Computational Linguistics
• Complexity Science
• +۳ مورد دیگر

Ramon Ferrer-i-Cancho is an Associate Professor in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB). He leads the Complexity & Quantitative Linguistics Lab and is part of the LQMC research group (Quantitative, Mathematical, and Computational Linguistics). His research focuses on quantitative linguistics, mathematical models of language structure, and computational methods to analyze linguistic universals like Zipf’s law and syntactic dependency distances. Education: PhD in Computer Science from UPC (2003), with a thesis on 'Language: universals, principles and origins.' Editorial Roles: Section editor of Encyclopedia of Language and Linguistics (3rd edition), editorial board member of Glottometrics, Journal of Quantitative Linguistics, and Lingua. Research Interests: Quantitative analysis of syntactic structures, language evolution, cognitive constraints in grammar, and cross-species communication patterns (e.g., chimpanzees, dolphins). He applies principles from complexity science, information theory, and optimization to linguistic problems. Notable Achievements: Recipient of the Joan Lluís Vives Prize (2003) for popular science communication, Barcelona City Research Prize (2003), and UPC’s Best PhD Thesis award (2003-2004). Authored influential papers on dependency distance minimization and Zipfian laws, with over 200 indexed publications. Teaching & Mentorship: Advised Master’s theses on dolphin communication, syntactic dependency distances, and data mining applications. Active in the Master in Innovation and Research in Informatics (MIRI), clarifying academic requirements like SIRI seminar credits. Outreach: Authored popular science books, including Lingüística quantitativa i lleis lingüístiques , and featured in media like National Geographic and Scientific American for bridging linguistics with biology and physics.

Marc Noyمشاهده پروفایل

استاد

• Combinatorics
• Graph Theory
• Discrete Geometry
• +۳ مورد دیگر

Marc Noy is a Professor at the Department of Applied Mathematics II, Polytechnic University of Catalonia (UPC), affiliated with the School of Mathematics and Statistics. He is the Director of the Barcelona Graduate School of Mathematics (BGSMath) and leads the 2015-2019 Excellence program BGSMath/María de Maeztu. His research focuses on Combinatorics and Graph Theory, including asymptotic enumeration, random graphs, discrete geometry, and Tutte polynomials. He has advised multiple PhD and Master’s students and contributes to editorial roles for the Electronic Journal of Combinatorics and the Catalan Mathematical Society’s Bulletin. His teaching spans undergraduate and graduate courses in Combinatorics, Graph Theory, Complex Analysis, and Discrete Mathematics at UPC. He has participated in numerous international conferences and workshops, including the ICM 2014 and FOCM 2017. His work emphasizes the probabilistic analysis of graph structures, limit laws, and enumerative combinatorics. His recent publications explore topics like logical limit laws in graph classes, random planar graphs, and Tutte polynomial evaluations. He maintains active collaborations in combinatorial enumeration, with contributions to understanding graph properties in minor-closed classes and random geometric configurations.