جست‌وجوی استاد و پژوهشگر

Angel Gimenez Pastorمشاهده پروفایل

استاد

• Differential Geometry
• Lorentzian Geometry
• Dynamical Systems
• +۴ مورد دیگر

Angel Gimenez Pastor is a Professor of Mathematics at Universidad Miguel Hernández (UMH) in Spain, specializing in differential geometry and dynamical systems. His research primarily focuses on the intersection of Lorentzian geometry, null curve theory, and applications to fluid mechanics and suspension flows. He completed his doctorate at Universidad de Murcia in 2002 with a thesis on "Geometría de curvas degeneradas" under the supervision of Dr. Pascual Lucas Saorín. His research interests encompass differential geometry, particularly Lorentzian geometry and null curves, dynamical systems theory, ergodic theory, and mathematical physics applications. His work bridges theoretical mathematics with practical applications in fluid mechanics and suspension modeling. He has made significant contributions to understanding the geometry of null curves in Lorentzian space forms and their applications to relativistic particle models. Professor Gimenez Pastor's publication record reveals a clear trajectory of research connecting geometric structures with dynamical behavior. His work on topological entropy of multimodal maps, switching systems, and suspension flows demonstrates his ability to connect abstract mathematical concepts with physical applications. The recurring themes across his publications include null curve geometry, dynamical system analysis, and mathematical modeling of complex physical phenomena. His scientific collaborations are extensive, with significant joint work with José María Amigó, Pascual Lucas, José Valero, and other researchers in Spain and internationally. These collaborations span multiple disciplines, reflecting the interdisciplinary nature of his research. As an academic advisor, he has mentored numerous students who have gone on to make their own contributions in mathematics and related fields, particularly in the areas of dynamical systems and mathematical physics. His research continues to influence both theoretical developments and practical applications in mathematical physics and fluid dynamics.

• Nuclear Fusion
• Plasma Physics
• Magnetohydrodynamics (MHD)
• +۳ مورد دیگر

Jose Miguel Reynolds Barredo is an Associate Professor and Director of the Doctorate in Plasmas and Nuclear Fusion at Carlos III University of Madrid. His research focuses on plasma physics, magnetohydrodynamics (MHD), and energy systems resilience. He leads studies on stellarator reactor design, plasma confinement optimization, and the integration of renewable energy into power grids. His work spans advanced MHD equilibrium solvers (e.g., SIESTA, FLIPEC) and fusion device optimization for ITER and Wendelstein 7-X. He also investigates climate impacts on renewable energy efficiency and power grid stability under high renewable penetration. Notable contributions include HVDC grid segmentation strategies and non-axisymmetric plasma transport modeling. Key Areas: Fusion reactor design, MHD stability, power grid resilience, climate-energy interactions Tools: SIESTA, FLIPEC, GENE, OPA cascading blackout model Projects: Doctorate in Plasmas and Nuclear Fusion, W7-X bootstrap current studies, climate-energy system interdependencies Research emphasizes computational plasma physics and interdisciplinary energy solutions, blending theoretical, numerical, and applied engineering approaches.

• Algorithms
• Randomized Data Structures
• Divide-and-Conquer Algorithms
• +۵ مورد دیگر

Salvador Roura Ferret is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Informatics of Barcelona (FIB) and the Department of Computer Sciences. He is an active researcher in the ALBCOM group, focusing on algorithmics, bioinformatics, complexity, and formal methods. His research interests span algorithms , randomized data structures , divide-and-conquer methods , and computational complexity . His work often bridges theoretical computer science with practical applications in voting systems, game theory, and educational technologies. The recent publications (2013–2025) reflect a strong trend in theoretical computer science, particularly in algorithm design, data structures (e.g., K-d trees, binary search trees), and game-theoretic models. There is a notable emphasis on mathematical rigor, complexity analysis, and formal modeling of computational problems. Best student paper award Distinció Jaume Vicenç Vives a la qualitat docent universitària (modalitat individual) 18è Premi UPC a la Qualitat en la Docència Universitària Roura has contributed to teaching innovation through projects like Eines per a la Transformació de la Docència en Programació and the development of Jutge.org , an online programming judge platform. He has participated in numerous competitive R+D+i projects, often in collaboration with researchers such as Conrado Martinez, Xavier Molinero, and Maria Serna. His work has been supported by national and regional funding programs. While no direct mention of grants or student advising is made, his extensive publication and project history suggest significant research leadership.

Michael Raskinمشاهده پروفایل

مدرس

• Theoretical Computer Science
• Distributed Systems
• Algorithms
• +۶ مورد دیگر

Michael Raskin is a Lecturer (maître de conferences) at LaBRI, University of Bordeaux, where he conducts research in theoretical computer science with a focus on distributed systems and formal methods. His work bridges theoretical foundations with practical implementations, particularly in population protocols, temporal graphs, and Petri nets. His research interests span Theoretical Computer Science , Distributed Systems , Algorithms , and Formal Methods , with specific expertise in population protocols, temporal graph analysis, vector addition systems, and verification techniques for parameterized systems. His publications demonstrate a consistent focus on computational complexity, state complexity, and threshold phenomena in distributed models. Recent publication trends show a strong emphasis on temporal graph theory (with multiple papers on random temporal graphs and giant components), population protocol analysis (including modular protocols and leaderless rendez-vous systems), and verification techniques for parameterized systems. His work often combines mathematical rigor with practical implementation insights. Raskin has developed significant software projects including: Agnostic Lizard - A portable code walker for Common Lisp QueryFS - A filesystem defined through compiled queries His technical contributions span both theoretical advances and practical systems implementation, with a recurring theme of applying programming language techniques to systems problems. His work on Common Lisp tools demonstrates a commitment to practical language implementation alongside theoretical research.

• Computational Geometry
• Service Localization
• Spatial Data Analysis
• +۳ مورد دیگر

Marta Fort Masdevall is a Lecturer in the Department of Computer Science, Applied Mathematics and Statistics at the University of Girona. She is affiliated with the Graphics and Image Laboratory Research Group (GILAB) and specializes in computational geometry with applications in service localization and spatial/spatio-temporal data analysis. She has participated in five R&D projects funded through public calls and teaches programming subjects. Her research focuses on Computational geometry algorithms Geospatial data processing Temporal data modeling Location-based service optimization She collaborates with the Institute of Computing and Applications and can be reached at Building P4, Office 236 (Girona) or via phone at +34 9338 (internal) / +34 618361888 (external).

• Lie Algebras
• Combinatorial Mathematics
• Nonassociative Rings and Algebras
• +۳ مورد دیگر

Manuel Ceballos González is a Researcher at the Universidad de Sevilla within the Department of Economics, Quantitative Methods, and Economic History. His academic work spans mathematics, computer science, and combinatorics, focusing on Lie algebras , Leibniz algebras , and evolution algebras . Education: PhD in Mathematics from Universidad de Sevilla (2012), with a thesis on abelian subalgebras and ideals in Lie algebras. His research explores the intersection of algebraic structures and combinatorial methods , particularly through matrix representations and graph-theoretic approaches. Key contributions include algorithms for computing abelian subalgebras, classifications of filiform Lie algebras, and studies on evolution algebras linked to (pseudo)digraphs. The 15 most recent publications highlight his work on solvable Leibniz algebras, Zinbiel algebras, and combinatorial structures in upper-triangular matrices. These articles reflect a blend of nonassociative ring theory , graph theory , and computational algebra , with applications in mathematical modeling and symbolic computation. Collaborations with prominent mathematicians like Juan Núñez-Valdés and Ángel F. Tenorio underscore his integration into the academic community. While no specific awards are listed, his extensive co-authorship network (35 joint publications) and contributions to zbMATH-indexed journals indicate significant scholarly impact.

Pooran Memariمشاهده پروفایل

پژوهشگر

• Geometric Modeling
• Computer Graphics
• Computational Geometry
• +۵ مورد دیگر

Pooran Memari is a CNRS Researcher at the Laboratoire d'Informatique de l'École Polytechnique (LIX), UMR CNRS 7161, Institut Polytechnique de Paris, and an Affiliate Professor (part-time) at École Polytechnique. She leads research in geometric modeling within the GeomeriX team at LIX-Inria, focusing on theoretical foundations and applications in accessibility and neurocognition. Her academic journey includes: HDR (Habilitation à diriger des recherches), Institut Polytechnique de Paris, 2024 Ph.D. in Geometric Modeling, INRIA Sophia-Antipolis, 2010 Master in Image and Geometry, University of Nice-Sophia Antipolis, 2006 Engineering Degree, École Polytechnique, 2005 Bachelor in Mathematics, Sharif University of Technology, 2002 Dr. Memari's research bridges geometric modeling, computational geometry, and computer graphics with real-world impact. She pioneers techniques in shape representation, point pattern synthesis, and surface reconstruction, advancing proximity encoding and clustering algorithms. Her work extends to accessibility applications—developing geometric models for visually impaired navigation through multisensory perception—and neurocognition validation via tactile interfaces. This interdisciplinary approach integrates theoretical rigor with practical tools like the CGAL library. Recent publications (2024-2019) reveal a cohesive trajectory in geometric processing: advancing point pattern synthesis through image-based editing (Patternshop), stability-incorporated neighborhood graphs (SING), and multi-class disk distributions; innovating surface reconstruction via Voronoi-based methods (BallMerge); and expanding applications to virtual worlds simulation and neurocognitive accessibility. Key themes include bridging discrete geometry operators with high-dimensional data analysis and translating theoretical insights into tools for visual computing. Dr. Memari actively mentors the next generation of researchers, advising eight PhD students on topics ranging from generalized Voronoi diagrams to neurocognition-driven tactile navigation. She coordinates Computer Science Projects for École Polytechnique's Bachelor program since 2019 and co-leads the Interaction, Graphics & Design master's program at IP-Paris. Her leadership extends to editorial roles at Computer Graphics Forum and Graphical Models Journal, alongside prominent conference positions including SGP Program Co-Chair (2023) and Eurographics STARs Co-Chair (2025). As a core GeomeriX team member, she drives collaborative projects in geometric modeling and virtual environments. She coordinates the LIX Seminar since May 2025 and serves on the French Eurographics Chapter board, fostering community engagement through initiatives like the IGD master's program and Eurographics symposia.

MARIA ALONSO PENAمشاهده پروفایل

استادیار

• Nonparametric Statistics
• Circular Regression
• Statistical Modeling
• +۳ مورد دیگر

María Alonso-Peña is an Assistant Professor at the University of Santiago de Compostela , affiliated with the Faculty of Biology and the Department of Statistics, Mathematical Analysis, and Optimization . Her research focuses on nonparametric statistical methods, particularly in circular regression models and their applications in neuroscience and animal behavior analysis. She holds a PhD in Statistics from the University of Santiago de Compostela (2022), with a thesis titled New approaches to nonparametric circular regression models . Education: PhD in Statistics (2022), University of Santiago de Compostela Research Interests: Nonparametric statistics, circular regression, optimization, and statistical modeling in neuroscience and ecology Her work bridges theoretical statistics with applied problems, such as analyzing neuronal spike counts and animal escape behavior using advanced circular regression techniques. She has collaborated with institutions like KU Leuven and Universidad de Granada. Recent research includes a grant from the Xunta de Galicia (ED481A-2019/139) for neuroscientific applications. Key contributions include frameworks for circular local likelihood regression and parametrically guided kernel density estimators for spherical data. These methods address challenges in modeling directional and multimodal datasets, with implications for fields like neuroscience and environmental science.

• Signal Processing
• Machine Learning
• Acoustic Engineering
• +۵ مورد دیگر

Manuel Rosa Zurera is a Full Professor at the Universidad de Alcalá, specializing in Signal Theory and Communications. He leads the AES3 research group focused on Acoustic and Electromagnetic Smart Sensor Networks and Signal Processing. His research emphasizes machine learning applications in audio analysis, biomedical signal processing, and passive radar systems. Dr. Rosa holds a PhD from Universidad de Alcalá (1999), supervised by Francisco López Ferreras. Research Interests : Dr. Rosa’s work spans acoustic signal localization, UAV detection, emotion recognition via speech analysis, and evolutionary studies of hominin auditory systems. His innovations include robust detection algorithms for passive radar, energy-efficient anger detection systems, and age/gender classification from speech using neural networks. He has pioneered acoustic sensor networks for urban security and biomedical diagnostics. Key Contributions : Over 150 peer-reviewed articles since 1999 demonstrate his expertise in signal processing for aerospace flutter analysis, real-time violence detection in smart cities, and 3D reconstruction of Neanderthal auditory capacities. His work bridges theoretical signal processing with practical applications in healthcare, surveillance, and evolutionary anthropology. Labs/Teams : Directs the AES3 group and collaborates on EU-funded projects like DVB-T radar systems and acoustic drone detection initiatives. Active in designing microphone arrays for hearing aids and wireless sensor networks.

Jose A. Ruiperez Valienteمشاهده پروفایل

دانشیار

• Computational Social Science
• Educational Technology
• Cyberdefence
• +۳ مورد دیگر

Jose A. Ruiperez Valiente is an Associate Professor at the Information and Communications Engineering Department of the University of Murcia. His academic journey includes a B.Eng. and M.Eng. in Telecommunications, followed by an M.Sc. and Ph.D. in Telematics from UC3M, with research conducted at IMDEA Networks. He completed research stays at MIT and the University of Edinburgh, and a postdoc at MIT Teaching Systems Lab/Playful Journey Lab. He has held academic appointments at Complutense University of Madrid and industry roles at Multimedia Vocento, Accenture, and ExoClick. Current role: Associate Professor, University of Murcia Previous institutions: UC3M, IMDEA Networks, MIT, University of Edinburgh, Complutense University of Madrid Industry experience: Multimedia Vocento, Accenture, ExoClick His research focuses on computational social science, educational technology, cyberdefence, and data science. Key methodologies include learning analytics, game-based assessment, and serious games for skill evaluation. Recent publications analyze trends in educational technology, develop frameworks for game-based assessments, and explore disinformation detection. His work combines machine learning with educational innovation, particularly in stress detection and competency evaluation through biometric data. Scientific awards include: BBVA Award as Outstanding Young CS Researcher Humboldt Research Fellowship He has co-authored over 100 publications with 2100+ citations and participated in 20+ funded projects like DEFENDER, SEMANTIC, and EU-GUARDIAN, focusing on cybersecurity training and decentralized AI systems.

• Pure and Applied Mathematics
• Algebraic Geometry
• Moduli Spaces
• +۴ مورد دیگر

Dr. David Alfaya Sánchez is an Associate Professor at the Department of Applied Mathematics, ICAI-Comillas, and an Associate Researcher at the Institute for Research in Technology (IIT). He holds a PhD in Mathematics from Universidad Autónoma de Madrid (2018), with prior degrees in Mathematics and Computer Science (both First National Prizes in their respective areas). His research integrates pure and applied mathematics, focusing on moduli spaces of decorated bundles (Higgs bundles, parabolic structures), Information Geometry, and AI-Math interactions. Education: PhD in Mathematics, UAM (2018) MSc in Mathematics and Applications (2014) MSc in Research & Innovation in ICT (2015) BSc in Mathematics (2013, First National Prize) BSc in Computer Science Engineering (2013, First National Prize) Research Interests: Algebraic Geometry: Moduli spaces of bundles, Higgs bundles, parabolic structures Information Retrieval & Geometry Blockchain technologies Applications of AI to mathematics His work bridges theoretical foundations (e.g., Torelli theorems) with computational tools (e.g., SymPy implementations). Grants & Projects: ERC Synergy Grant: Mathematicae Lingua Franca (2025–2031) Computational methods for moduli spaces (2023–2026) DLT-based distributed networks (2019–2020) Teaching & Innovation: Leads the Maths Team Contest (MTC), fostering collaborative problem-solving. Authored textbooks like Matemáticas Empresariales II and Habilidades Profesionales . Recent Publications: Focus on moduli spaces (e.g., Torelli theorems), AI applications (e.g., neural network sensitivity analysis), and symbolic computation (e.g., λ-ring simplifications).

Gleb Pogudinمشاهده پروفایل

استادیار

• Symbolic computation
• Algorithms for differential equations
• Algorithms for difference equations
• +۵ مورد دیگر

Gleb Pogudin is an Assistant Professor at École Polytechnique, Institute Polytechnique de Paris, where he is a member of the MAX team within the Laboratoire d'informatique. His research focuses on the intersection of symbolic computation, differential equations, and algebraic methods with applications across multiple scientific domains. Dr. Pogudin's primary research interests span several interconnected areas: Symbolic computation and computer algebra algorithms Theory and applications of differential and difference equations Nonlinear algebra and polynomial systems Structural identifiability of dynamical models Model reduction techniques for complex systems His recent publications (2024-2025) demonstrate a strong focus on developing theoretical foundations for differential elimination, structural identifiability analysis, and model reduction. These works span applications in systems biology, epidemiology, pharmacology, and optics. Notably, his research bridges pure mathematical theory with practical computational implementations, creating tools that address real-world scientific challenges. Dr. Pogudin has developed several significant software tools that implement his theoretical advances: StructuralIdentifiability.jl: A Julia package for assessing structural identifiability CLUE: Software for exact model reduction of ODE models via constrained lumping SIAN: Software for structural identifiability analysis of ODE models His GitHub repositories contain numerous implementations of algorithms from his papers on differential elimination and related topics, demonstrating his commitment to making theoretical advances practically accessible to researchers across disciplines.

Simo Alamiمشاهده پروفایل

مربی

• Deep Learning
• Reinforcement Learning
• Inverse Reinforcement Learning
• +۴ مورد دیگر

Simo Alami is a Ph.D. candidate and Tutor at Ecole Polytechnique, affiliated with the LIX computer science laboratory under the supervision of Professor Jesse Read. He teaches tutorials for the Advanced Machine Learning and Autonomous Agents course (Computer Science, Ingénieur 3A/Master1) since 2020, focusing on practical implementations of machine learning algorithms and autonomous systems. His academic background includes undergraduate and graduate studies in Mathematics and Computer Science at Université Pierre et Marie Curie and Ecole CentraleSupélec. Ph.D. Candidate, Ecole Polytechnique (2020-Present) Master's Studies, Mathematics and Computer Science, Université Pierre et Marie Curie and Ecole CentraleSupélec Alami's research centers on developing algorithms that learn from experience through self-learned metrics, with core expertise in Deep Learning, Inverse Reinforcement Learning, and Metric Learning. His work targets robotic applications where agents must perform novel tasks by understanding logical concepts, while also extending to energy management systems through non-invasive load monitoring. He explores how meta-learning frameworks can enable transferable reward structures across domains. His publication record reveals a strong trajectory in distributional reinforcement learning and inverse reinforcement learning using generative models, with significant contributions to metric learning for clustering and energy disaggregation. The consistent focus on transferable methodologies across robotics and smart grid applications demonstrates his interdisciplinary approach to solving real-world problems through advanced machine learning techniques. Scientific recognition includes: Nvidia Grant awarded in 2022 for research on Meta-Inverse Reinforcement Learning 3rd Prize at Hi Paris Hackathon (2021) for a reinforcement learning-based smart grid energy management solution While not supervising graduate students as a Ph.D. candidate, Alami has secured competitive external funding including the Nvidia research grant. His industry collaboration with Accenta during a visiting researcher position resulted in ECML 2022 publications on non-invasive load monitoring, highlighting his ability to bridge academic research with practical engineering applications. As an active member of the LIX laboratory at Ecole Polytechnique, Alami participates in cutting-edge computer science research while maintaining external collaborations. His visiting researcher position at Accenta demonstrates engagement with industry partners, and his organization of the IRT SystemX Electromobilité et territoires webinar in 2021 reflects leadership in knowledge dissemination within the energy and mobility research community.

• Computational Engineering
• Numerical Methods for PDEs
• High-order Methods
• +۶ مورد دیگر

Matteo Giacomini is an Associate Professor of Computational Engineering at Universitat Politècnica de Catalunya (UPC), affiliated with the Laboratori de Càlcul Numèric (LaCàN). He is also an affiliated researcher at CIMNE (Severo Ochoa Excellence Centre) and affiliated faculty at IMTech (Institute of Mathematics of UPC-BarcelonaTech). His research focuses on numerical methods for PDEs, including high-order and low-order methods, error estimation, and reduced-order modeling. Applications span computational fluid dynamics, solid mechanics, image segmentation, and industrial sustainability. Education : PhD in Applied Mathematics, École Polytechnique (2016) MSc & BSc in Mathematical Engineering, Politecnico di Milano (2013 & 2010) Research Interests : High-order methods: finite element, discontinuous Galerkin Error & adaptivity: a posteriori estimates, mesh adaptation Dimensionality reduction: reduced order models, scientific ML PDE-constrained optimization: topology/shape optimization Software development: open-source CSE tools Recent Work Trends : Recent articles emphasize multi-fidelity surrogate modeling, domain decomposition for parametric PDEs, and robust finite volume methods for incompressible/compressible flows. He also contributes to HDG method implementations (e.g., HDGlab) and industrial applications of CFD. Labs & Affiliations : LaCàN - UPC CIMNE - Innovative Algorithms & Credible Data-Driven Models groups IMTech - Mathematical Modelling research line

Francesc Alías Pujolمشاهده پروفایل

استاد

• Speech Processing
• Acoustic Signal Processing
• Text-to-Speech Synthesis
• +۷ مورد دیگر

Francesc Alías Pujol is a Professor at the Department of Engineering, Ramon Llull University (La Salle Campus Barcelona), where he also serves as Director of Teaching and Research Staff Policies since September 2019 and coordinates the PhD Program in Information Technologies since February 2022. He is a researcher in the Human-Environment Research (HER) group, focusing on speech and acoustic signal processing for natural human-machine interaction. His educational background includes: BSc in Telecommunications Engineering (1997) MSc in Electronics Engineering (1999) PhD in ICT and their application in Management (2006) MBA in Business Administration (2013) University Expert Program in Digital Transformation (2023) Dr. Alías's research primarily focuses on signal processing, with special emphasis on speech and acoustic signal processing to achieve natural interaction between humans, machines, and their environment. His work spans from Text-to-Speech (TTS) synthesis to vocal biomarkers for digital health applications, numerical voice simulation, and environmental acoustics. He has developed expertise in expressive speech analysis and synthesis, sound source identification, and smart city applications through wireless acoustic sensor networks. His publication record shows a consistent trajectory in speech and acoustic processing, with recent work focusing on the impact of global events like the COVID-19 pandemic on urban soundscapes, advanced techniques for glottal source analysis, and the development of algorithms for anomalous noise event detection in smart city applications. His research bridges theoretical signal processing with practical applications in environmental monitoring and human-computer interaction. Dr. Alías has received numerous scientific awards including: 3rd six-year research merit (2018-2023) from AQU Catalunya Most cited paper in Noise Mapping (2021) for his work on COVID-19's impact on urban noise 2nd six-year research merit (2012-2017) from AQU Catalunya Best academic record award for his MBA (2013) Multiple best paper awards from the Spanish Thematic Network on Speech Technology He has led and participated in numerous research projects including DISTRESIA (stress biomarker identification), FEMVoQ (3D voice simulation), SUARAMAP (acoustic monitoring for dementia detection), GENIOVOX (expressive voice generation), and DYNAMAP (dynamic noise mapping). His work has been supported by various funding bodies including the European Commission, Spanish Ministry of Science, and Catalan Government. As coordinator of the PhD Program in Information Technologies and former Director of the Department of Engineering (2014-2021), Dr. Alías plays a significant role in academic leadership at La Salle-URL. His research group focuses on the intersection of speech processing, environmental acoustics, and smart city applications, contributing to both theoretical advancements and practical implementations in these fields.