جست‌وجوی استاد و پژوهشگر

Anna De Mier Vinueمشاهده پروفایل

دانشیار

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

Anna De Mier Vinue is an Associate Professor at the Department of Mathematics, Universitat Politècnica de Catalunya (UPC), affiliated with the Facultat d'Informàtica de Barcelona (FIB). She leads research in combinatorics, graph theory, and matroid theory as part of the UPC's GAPCOMB research group (Geometric, Algebraic and Probabilistic Combinatorics). Her work focuses on structural combinatorics, polynomial invariants, and discrete geometry. Education: Holds a PhD in Applied Mathematics from UPC. Research Interests: Combinatorial enumeration, graph polynomials (Tutte, U-polynomials), matroid representations, non-crossing structures, and algorithmic combinatorics. Her contributions bridge algebraic methods with geometric and probabilistic approaches. Publications: Over 77 works including articles in Discrete Mathematics, European Journal of Combinatorics, and SIAM Journal on Discrete Mathematics. Recent research explores marked graphs, Tutte polynomial evaluations, and lattice approximations in clutter theory. Active in international projects like COCOA and R+D+I initiatives. Grants & Collaborations: Co-leads projects on extremal combinatorics, geometric algorithms, and mathematical education. Collaborates with researchers from BarcelonaTech and international institutions. Involved in initiatives addressing gender equality in STEM education through statistical analysis. Labs/Teams: Core member of the UPC's GAPCOMB group, contributing to interdisciplinary projects at the Institut de Matemàtiques de la UPC-BarcelonaTech. Supervises research in combinatorial geometry and algebraic structures.

• Bayesian Statistics
• Spatial Epidemiology
• Disease Mapping
• +۶ مورد دیگر

Miguel Ángel Martínez Beneito is an Associate Professor in the Department of Statistics and Operations Research at the Faculty of Mathematics, University of Valencia. His research focuses on Bayesian statistics, spatial epidemiology, and disease mapping, with applications in public health and risk cluster detection. Education: PhD in Statistics from the University of Valencia (2005), thesis on statistical methods for detecting risk foci in epidemic outbreaks. His research interests include Bayesian modeling, spatial statistics, and computational epidemiology. He is a member of the Valencia Bayesian Research Group (VABAR), contributing to advanced statistical methodologies in health sciences. The recent publications attributed to him span topics in stochastic processes, biomechanics, and mathematical biology. However, there is a possibility of name disambiguation, as some works on biomechanics appear more aligned with a researcher from the University of Zaragoza. The core research at UV remains in statistical and epidemiological modeling. Scientific Contributions: Development of Bayesian methods for disease mapping. Application of statistical models to public health surveillance. Potential contributions to stochastic modeling in biological systems. He advises students in statistics and public health, though no specific advisees are listed. He has collaborated extensively with researchers in applied mathematics and biomechanics, though the nature of these collaborations requires further clarification due to potential name overlap. He is affiliated with the VABAR research group, focusing on Bayesian inference and its applications in real-world health problems.

• Computational Geometry
• Discrete Geometry
• Combinatorial Geometry
• +۷ مورد دیگر

Clemens Huemer is a professor affiliated with the Department of Mathematics at the Escola d'Enginyeria de Telecomunicació i Aeroespacial de Castelldefels (EETAC), part of the Universitat Politècnica de Catalunya (UPC). He is a key member of the DCCG (Discrete, Combinational, and Computational Geometry) research group, where he contributes extensively to theoretical and applied geometric research. His work spans computational, discrete, and combinatorial geometry with strong ties to graph theory and combinatorics. His primary research interests include computational geometry, discrete and combinatorial geometry, Voronoi diagrams (especially higher-order variants), geometric graphs, point set configurations, and algorithmic geometry. He investigates structural properties of geometric objects, combinatorial configurations, and optimization problems in discrete settings. His recent publications emphasize Voronoi constructions, matching problems in colored point sets, spectral properties of token graphs, and production matrices for enumerating geometric graphs. The trends in his recent articles (2021–2024) reflect a deep focus on higher-order Voronoi diagrams, geometric matching, and combinatorial properties of point sets and graphs. His work combines theoretical depth with algorithmic insights, often involving polynomial representations, spectral analysis, and geometric enumeration. The recurring themes include structural analysis of geometric arrangements, extremal problems in point sets, and algebraic-combinatorial methods in geometry. Clemens Huemer has been involved in multiple competitive R&D projects, including those funded under the Spanish State Research Plans and Horizon 2020, often in collaboration with leading researchers in computational geometry. He has served on scientific committees of conferences such as the Workshop on Geometric Networks and the Intensive Research Program on Discrete, Combinatorial and Computational Geometry, indicating leadership in the academic community. He advises and collaborates with numerous researchers and students, though specific advisees are not listed in the provided data. His research is supported through national and European grants, and he actively contributes to the dissemination of results via conference presentations and journal publications in top venues such as Discrete and Computational Geometry , Computational Geometry: Theory and Applications , and European Workshop on Computational Geometry . Clemens Huemer is based at the Baix Llobregat campus of UPC and is deeply embedded in the UPC research network, with extensive collaborations across institutions in Spain and internationally. His work is central to the DCCG group’s efforts in advancing the theoretical foundations of discrete and computational geometry.

• Combinatorics
• Discrete Mathematics
• Random Graphs
• +۴ مورد دیگر

Juan José Rué Perna is an Associate Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (UPC), where he serves in the Faculty of Mathematics and Statistics. He also holds the position of Director of CFIS (Centro de Formación Interdisciplinaria Superior) and maintains strong affiliation with the Centre de Recerca Matemàtica (CRM). His academic career spans prestigious institutions across Europe, including Freie Universität Berlin, CSIC-ICMAT in Madrid, and École Polytechnique in Paris. Licenciado en Matemáticas (5-year degree) Engineering degree in Telecommunications (5-year program) PhD in Applied Mathematics (2009), supervised by Professor Marc Noy Rué's research focuses on combinatorics and discrete mathematics, with expertise in combinatorial structures, random graphs, and enumerative problems. His work bridges theoretical mathematics with applications in computer science, particularly in structural graph theory and probabilistic methods. He has made significant contributions to the understanding of planar graphs, random discrete structures, and additive combinatorics problems. His research combines analytic techniques with combinatorial reasoning to solve challenging enumeration and structural problems. His recent publications demonstrate a consistent trajectory in combinatorial mathematics, with emphasis on planar structures, random discrete objects, and additive problems. The works span theoretical investigations of graph structures, enumeration techniques, and probabilistic approaches to combinatorial problems. His research group GAPCOMB (Geometric, Algebraic and Probabilistic Combinatorics) at UPC continues to produce influential work in these areas. Premi Albert Dou de la SCM Rué has successfully supervised multiple PhD students to completion, including Clément Requilé, Christoph Spiegel, Vasiliki Velona, and Maximilian Wötzel. His research has been supported through numerous competitive grants, including ERC projects, ExploreMaps, and participation in the Berlin Mathematical School. He has organized significant academic events such as EUROCOMB 2021 and various workshops on combinatorics and discrete mathematics. As leader of the GAPCOMB research group at UPC, Rué fosters collaboration between geometric, algebraic, and probabilistic approaches to combinatorial problems. The group maintains strong connections with international research centers including ICMAT in Madrid and institutions across Europe, contributing to the vibrant combinatorial research community in Spain and internationally.

Oriol Serra Alboمشاهده پروفایل

استاد

• Combinatorics
• Additive Number Theory
• Graph Theory

Oriol Serra Albo is a Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (UPC), affiliated with the Institute of Mathematics of UPC-BarcelonaTech (IMTech) and the Faculty of Mathematics and Statistics (FME). He leads the research group GAPCOMB (Geometric, Algebraic and Probabilistic Combinatorics) and maintains collaborations with the Barcelona Graduate School of Mathematics. Research Focus: Serra's work spans three interconnected domains: Combinatorics : Developing novel frameworks for discrete structure analysis Additive Number Theory : Investigating sumset properties in algebraic structures Graph Theory : Exploring coloring problems and structural graph properties Publication Trends: His recent articles (2021-2024) demonstrate a focus on extremal problems in additive combinatorics, structural properties of random graphs, and algebraic methods in discrete mathematics. Common themes include product-free sets in non-abelian groups, vertex bisection in random regular graphs, and probabilistic approaches to combinatorial optimization. Research Leadership: Serra coordinates multiple competitive research projects including: Structure, Randomness and Computational Methods in Extremal Combinatorics Contemporary Combinatorics and Applications (COCOA) Geometric, Algebraic and Probabilistic Combinatorics Combinatoria: nuevas tendencias y aplicaciones Academic Service: Regularly serves on scientific committees for international conferences including the European Conference on Combinatorics and French Combinatorial Conference.

Carmona Mejias, Angelesمشاهده پروفایل

استاد

• Matrix Analysis
• Discrete Potential Theory
• Graph Theory
• +۵ مورد دیگر

Angeles Carmona Mejías is a Professor in the Department of Mathematics at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona Est School of Engineering (EEBE). She is a core member of the research groups MAPTHE (Matrix Analysis and Discrete Potential Theory) and OMGRAPH (Optimization Methods on Graphs). Her work focuses on advancing mathematical theories with interdisciplinary applications, particularly in biomedical engineering and discrete mathematics. Research Interests: Her primary areas include matrix analysis, discrete potential theory, and their applications to graph theory, random walks, and inverse problems. She has pioneered work in electrical impedance tomography (EIT) for medical diagnostics, notably developing prototypes for early breast cancer detection. Her methodologies often integrate stochastic processes, spectral graph theory, and numerical algorithms to solve real-world challenges. Collaborations & Projects: She leads and collaborates on competitive R&D projects, such as the technical validation of EIT devices and optimization methods for discrete imaging techniques. Her contributions span over 340 academic activities, including peer-reviewed articles, conference presentations, and patents (e.g., a 2024 patent for impedance estimation in biological tissues). She actively participates in international congresses, including the European Congress of Mathematics and the International Congress on Industrial and Applied Mathematics. Awards & Recognition: While no specific prizes are listed, her extensive publication record and project leadership reflect significant scholarly impact. She maintains profiles on ORCID (0000-0001-7713-1066), Scopus (7005541869), and ResearcherID (L-3528-2014). Research Infrastructure: Her work involves collaboration with multidisciplinary teams, including engineers and clinicians, to advance medical imaging technologies. Current efforts emphasize improving EIT accuracy through discrete mathematical techniques and validating prototypes for clinical use.

• Autonomous Mobile Robots
• Computer Vision
• Reinforcement Learning
• +۵ مورد دیگر

Dr. Jaime Boal Martín-Larrauri is an Associate Professor at the School of Engineering (ICAI) of Comillas Pontifical University, affiliated with the Electronics, Control and Communications Department. He holds a PhD in Engineering Systems Modeling (2014) and coordinates the M.Eng. in Intelligent Industry since 2019. His research focuses on robotics, computer vision, reinforcement learning, IoT, energy efficiency, and Industry 4.0 applications. He co-founded Stemy Energy (2018–2024) as CTO, developing energy efficiency solutions. Education: PhD in Research in Engineering Systems Modelling, Comillas Pontifical University (2014) M.Sc. in Research in Engineering Systems Modelling, Comillas Pontifical University (2012) Industrial Engineer (Electronics), Comillas Pontifical University (2010) Research Interests: His work integrates hardware-software systems, emphasizing robotic control, energy-efficient IoT platforms, and AI-driven solutions for industrial automation. Key projects include drone detection systems, smart energy grids, and reinforcement learning for industrial robots. Publications & Trends: Recent articles emphasize robotic learning, energy efficiency, and AI interpretability. Notable contributions include reinforcement learning robustness improvements and IoT energy platform architectures. Awards: Multiple Chair for Smart Industry Awards (2021–2024) for outstanding student projects under his supervision Extraordinary End-of-Degree Award (2011) Grants & Labs: Lead projects funded by ENDESA, Ferrovial, MIT, and the Madrid Regional Government. Active in the Institute for Research in Technology (IIT), collaborating on robotics and energy systems. Labs/Teams: Contributes to the IIT’s robotics and IoT research groups, focusing on autonomous systems and smart industry applications.

• Number Theory
• Algebraic Geometry
• Modular Forms
• +۳ مورد دیگر

Josep Gonzalez Rovira is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament de Matemàtiques at the Escola Politècnica Superior d'Enginyeria de Vilanova i la Geltrú (EPSEVG). His research focuses on Number Theory, Algebraic Geometry, and computational aspects of modular forms and curves. He is a core member of the STNB (Seminari de Teoria de Nombres de Barcelona) research group, contributing to projects like 'Aritmética de funciones L y estructuras de Galois' and 'Técnicas computacionales en teoría de números.' Key research interests include modular curves, elliptic curves, Q-curves, automorphism groups, and applications to cryptography. He has authored over 80 publications, including studies on division polynomials, bielliptic curves, and Frobenius distributions. His work often intersects computational methods, as seen in projects involving SageMath and collaborations on hyperelliptic curves. Josep has advised doctoral students like Santiago Molina (2011) and contributed to grants funded by Spain's Plan Nacional and Catalan agencies. His academic contributions include editorial roles in journals like Experimental Mathematics and Publicacions Matemàtiques , reflecting his leadership in advancing algebraic number theory and arithmetic geometry.

• Complex Systems
• Data Analysis
• Nonlinear Dynamics
• +۴ مورد دیگر

Cristina Masoller Alonso is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament de Física and the Escola Superior d'Enginyeries Industrial, Aeroespacial i Audiovisual de Terrassa (ESEIAAT). Her research focuses on complex systems, nonlinear dynamics, nonlinear photonics, and data analysis. She is part of the DONLL research group (Dinàmica no Lineal, Òptica no Lineal i Làsers) and holds a PhD from Bryn Mawr College, USA, with a Master's in Physics. Her work spans experimental and theoretical studies in semiconductor lasers, chaos synchronization, and applications of nonlinear dynamics to neural networks and ecological systems. Her recent research highlights include analyzing noise-induced phenomena in neural networks, studying corruption network structures through gender disparity analysis, and developing entropy-based methods for detecting critical transitions in ecological and climatic systems. She has led multiple competitive research projects funded by the Air Force Office of Scientific Research and European programs, and her work is published in high-impact journals like Chaos , Optics Express , and Scientific Reports . Dr. Masoller's contributions include over 400 academic activities, including articles, conference presentations, and research grants. She collaborates extensively with institutions globally and is actively involved in organizing and reviewing for international conferences in nonlinear dynamics and photonics.

• Artificial Intelligence
• Reinforcement Learning
• Generative AI
• +۱۰ مورد دیگر

Álvaro Jesús López López is a researcher at the Instituto de Investigación Tecnológica (IIT) and a professor at the Higher Technical School of Engineering (ICAI), both part of Comillas Pontifical University. He holds the position of Associate Research Fellow and serves as a principal investigator at the Chair of Smart Industry, where he leads applied research on digital technologies such as generative AI, computer vision, and synthetic data generation. He also directs executive programs in generative artificial intelligence for professionals at Comillas Onexed. His research interests include Artificial Intelligence, Reinforcement Learning, Generative AI, Smart Industry, and Railway Systems . His work focuses on applying advanced AI techniques to industrial and transportation challenges, particularly in energy efficiency and automation. He has published extensively in high-impact journals such as Engineering Applications of Artificial Intelligence , Applied Intelligence , and Transportation Research Part C . The recent articles highlight a strong trend toward applied AI in industrial and robotic systems , with a focus on sim-to-real transfer, keyphrase extraction, and reinforcement learning enhanced with semantic knowledge. His work bridges the gap between theoretical AI and real-world industrial applications. Scientific Awards: Honorable Mention from the Industry 4.0 Observatory (2021) Honorable Mention at the 6th Connected Industry Promotion Award Erasmus Teaching/Research Staff Training Grant (2014) He has advised multiple PhD students and leads several industry-funded research projects with organizations such as Ferrovial, Endesa, Metro de Madrid, and the European Commission. He has also organized scientific events and delivered numerous invited talks on AI and digitalization. His research has led to practical applications, including a patent on utilizing regenerative braking energy in railways. He completed a research stay at the Royal Institute of Technology (KTH) in Stockholm and has contributed to books and policy reports on digitalization in industry.

• Probabilistic Combinatorics
• Extremal Combinatorics
• Random Combinatorial Structures
• +۲ مورد دیگر

Guillem Perarnau Llobet is an Associate Professor at the Department of Mathematics, Universitat Politècnica de Catalunya (UPC), affiliated with CRM (Centre de Recerca Matemàtica), IMTech (Institut de Matemàtiques de la UPC), and BGSMath (Barcelona Graduate School of Mathematics). His academic journey includes a PhD at UPC under Oriol Serra, followed by a CARP Postdoc Fellowship at McGill University with Bruce Reed and Louigi Addario-Berry (2013–2015), and a Lecturer position at the University of Birmingham (2016–2019). Current Role: Associate Professor, UPC Past Roles: Lecturer, University of Birmingham; Postdoc, McGill University Affiliations: CRM, IMTech, BGSMath Research Focus: Probabilistic and Extremal Combinatorics, Random Combinatorial Structures, Discrete Stochastic Processes, and Analysis of Randomized Algorithms. His work bridges theoretical rigor with practical algorithmic insights, particularly in graph theory and random graph dynamics. Article Trends: Recent publications emphasize algorithmic combinatorics, probabilistic methods in random graphs, and hypergraph Hamiltonicity. Key themes include mixing times, synchronization, and percolation phenomena across diverse graph models. Scientific Awards: CARP Postdoc Fellowship Grants & Collaborations: COCOA Grant (coPI) RandNET MSCA Exchange Programme Participant Spanish Discrete and Algorithmic Mathematics Network Coordinator

Pedro Delicadoمشاهده پروفایل

استاد

• Statistics
• Data Science
• Big Data
• +۷ مورد دیگر

Pedro Delicado is a Full Professor at the Department of Statistics and Operations Research, Universitat Politècnica de Catalunya (UPC), based in Barcelona. He holds a degree in Mathematics and a doctorate in Economics. His research focuses on advanced statistical methods, data science, functional data analysis, and machine learning applications. He leads the ADBD research group (Analysis of Complex Data for Business Decisions) and collaborates with the Institut de Matemàtiques de la UPC. His current project 'Advanced Statistics and Data Science 2: New data, new models, new challenges' (PID2023-148158OB-I00) addresses modern data challenges, including Big Data, wearable devices, EEG analysis, graph data, and nonlinear dimensionality reduction. He supervises PhD students and has expertise in predictive modeling, explainable AI, and interdisciplinary applications in health, environmental science, and education. Delicado has published extensively in top journals like Machine Learning, Test, and Environmental and Ecological Statistics. He teaches advanced statistics and data science courses, leveraging virtual platforms. His work bridges statistical theory with practical applications, emphasizing interpretability and real-world impact.

• Bayesian Statistics
• Biomedical Applications
• Healthcare Analytics
• +۳ مورد دیگر

Dr. Andrea Cremaschi is an Assistant Professor at IE University, specializing in Bayesian statistics with applications in biomedical research, public health, and data science. His academic journey includes roles at institutions such as the Singapore Institute for Clinical Sciences (SICS) and the National University of Singapore (NUS), where he contributed to interdisciplinary projects in biostatistics and clinical research. He holds a Ph.D. in Statistics from the University of Kent and degrees in Mathematical Engineering from Politecnico di Milano. His research focuses on developing novel Bayesian statistical methodologies for healthcare challenges, including drug sensitivity analysis in oncology, maternal and child health outcomes, and cost-effectiveness studies. He also explores applications in digital humanities and climate action, aligning with UN Sustainable Development Goals 3 (Good Health), 4 (Quality Education), and 13 (Climate Action). Key contributions include studies on postpartum diabetes screening, pediatric growth modeling, and ex vivo drug response analysis in leukemia. His work bridges computational statistics with real-world health challenges, emphasizing algorithmic innovation and interdisciplinary collaboration. Education: Ph.D. in Statistics (University of Kent), M.Sc./B.Sc. in Mathematical Engineering (Politecnico di Milano) Professional Affiliations: IE University, Singapore Institute for Clinical Sciences (SICS), National University of Singapore

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 .