جستجوی استاد راهنمای دانشگاهی

Jose J. Muñoz is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mathematics and the LACÀN research group. His work focuses on computational mechanics, mechanobiology, and inverse problems in biological systems. He holds a PhD in Aeronautics from Imperial College London (2004) and a dual degree in Mechanical Engineering from UPC and Civil Engineering from École Centrale Paris (1997). His research combines finite element methods, vertex models, and optimal control to study tissue morphogenesis, wound healing, and cancer mechanics. Current roles include leading the LACÀN research group and supervising PhD students in projects like optimal control of contractile systems and inverse mechanical analysis. Former students include Ashutosh Bijalwan and Cécilia Olivesi. He teaches Numerical Methods and Computational Mechanics at the UPC's Faculty of Mathematics and Statistics. His research interests span vertex and finite element modeling, cell rheology, and stability analysis of biological tissues. Notable contributions include models for epithelial wound healing, Drosophila embryo development, and mechanical oscillations in tissues. His work often integrates experimental data with computational frameworks to infer non-observable mechanical parameters.

• Mechanobiology
• Computational Mechanics
• Finite Element Methods
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Yann Ponty is a tenured CNRS Researcher at the Computer Science Department (LIX) of École Polytechnique (Institut Polytechnique de Paris, France). He leads the AMIBio team and serves as Deputy Director of LIX. His work focuses on developing bioinformatics methods at the intersection of computer science, mathematics, and molecular biology, particularly for RNA structure prediction, design, and evolution. He holds leadership roles in the ISCB Board of Directors (2025-2027) and the HDR referent for the IDIA department (CS&Interactions) at IP Paris. Research Interests: RNA folding/design/evolution, RNA-RNA/RNA-protein interactions, random generation, enumerative combinatorics, discrete algorithms, parameterized complexity, RNA visualization Key Contributions: Developed algorithms for RNA inverse folding, pseudoknot modeling, and dynamic programming optimization Collaborations: Partnerships with institutions like Simon Fraser University, Boston College, and Université Paris-Saclay His recent publications (15 most recent) span RNA structure prediction, pseudoknot partition functions, linear-time inverse folding algorithms, and parameterized sampling techniques. The work emphasizes dynamic programming, combinatorial approaches, and integration of experimental data for improving RNA modeling. Scientific awards include election to the ISCB Board of Directors (2025-2027) and leadership roles in academic networks like GdR BIM. He actively contributes to software development (VARNA, RNANR, SPARCS, IncaRNAtion, RNARedPrint) and serves as Associate Editor for Bioinformatics (OUP). Teaching engagements include graduate-level courses in combinatorial optimization, RNA bioinformatics, and algorithms at Université Paris-Saclay and École Polytechnique.

• RNA Folding
• RNA Design
• RNA Evolution
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Rafael Sebastian is a Full Professor at Universitat de Valencia and General Director for Science and Research of the Generalitat Valenciana. He leads the Computational Multiscale Simulation Lab (CoMMLab) and collaborates with institutions like Oxford University and Yale University. Department of Computer Science, Universitat de Valencia CoMMLab Founder Spanish Network of Excellence in Cardiac Modeling His research focuses on multi-scale computational models and artificial intelligence for patient-specific cardiac simulations , aiming to improve arrhythmia risk stratification and therapy planning . Key topics include cardiac conduction system modeling , scar-related ventricular tachycardia , and machine learning pipelines for clinical applications. Recent publications emphasize automata-based simulations for atrial arrhythmias, machine learning in arrhythmia localization, and 3D geometric characterization of aortic diseases. Trends show integration of computational modeling with clinical data and medical imaging . Scientific Awards: Best Poster Award, Functional Imaging and Modeling of the Heart (2021) Cum Laude Award, SPIE Medical Imaging (2009) Student Presentation Award (2011) He has supervised 7 PhD/Master students and led grants exceeding €1 million, including projects like iSARC-GENETICS and iCardioTwins , focusing on digital twin technology and cardiac disease stratification .

• Cardiac Computational Modeling
• Artificial Intelligence in Medicine
• Medical Imaging
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Oriol Guasch Fortuny is Full Professor at the Department of Engineering, La Salle, Ramon Llull University in Barcelona, specializing in computational acoustics and aeroacoustics. He holds a five-year Physics degree from Universitat de Barcelona and a PhD in Computational Mechanics from UPC. His research spans acoustic black holes , graph theory in vibroacoustics, parametric array technology , and numerical voice production . Current projects: GENIOVOX (expressive voice generation), EUNISON (voice simulation) Editorial roles: Subject Editor , Journal of Sound and Vibration Leadership: Heads acoustics research in the GTM group His 15 most recent publications focus on acoustic black hole applications in vibration control, parametric loudspeaker optimization , and chaotic vocal fold modeling . Work combines finite element analysis with theoretical acoustics . Collaborations include: CIMNE (UPC, Barcelona) GIPSA-LAB (Grenoble, France) INSA Lyon (France) Northwestern Polytechnical University (Xi’an, China) KTH Stockholm (Sweden) Patents: NºU-201230809: Horn amplifier for parametric arrays Nº201230043: Omnidirectional ultrasonic sound source

• Computational Acoustics
• Aeroacoustics
• Graph Theory in Vibroacoustics
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Ana Muñoz Sánchez is an Associate Professor in the Department of Mechanical Engineering at University Carlos III of Madrid, where she conducts research in composite materials, additive manufacturing, and manufacturing processes. Her work bridges theoretical modeling with practical applications, particularly in drilling processes, ballistic protection, and engineering education. Her research focuses on several key areas within mechanical engineering and materials science: Composite materials machining, particularly carbon fiber reinforced polymers (CFRP) Tool wear analysis and optimization of drilling parameters Numerical modeling of manufacturing processes Additive manufacturing applications in medical and educational contexts Ballistic protection systems Engineering education tools and methodologies Dr. Muñoz Sánchez's publication record demonstrates consistent contributions to both fundamental manufacturing research and practical educational applications. Her recent work shows a strong emphasis on improving manufacturing processes for composite materials while simultaneously developing innovative educational tools, including specialized resources for visually impaired students. Her research combines computational methods with experimental validation to address complex engineering challenges. She has secured funding from multiple Spanish research agencies for projects including "DIGITDRILL - Digitalization of industrial drilling process" and "DISEÑO AVANZADO, FABRICACIÓN Y ENSAYO DE PROTECCIONES BALÍSTICAS DE CABEZA (PROTECT_BAL)". Her work has practical applications in aerospace, medical simulation, and inclusive education.

• Mechanical Engineering
• Composite Materials
• Additive Manufacturing
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Sergio Segura de León is a full Professor in the Faculty of Mathematics at the University of Valencia, Spain. He is affiliated with the Department of Mathematical Analysis and is a member of the EDPNOL (Nonlinear Partial Differential Equations) research group. He obtained his PhD from the University of Valencia in 1988. PhD: University of Valencia, 1988 His primary research interests lie in nonlinear partial differential equations, particularly focusing on elliptic and parabolic equations involving the p-Laplacian and 1-Laplacian operators, singular terms, gradient growth, and asymptotic behavior as p → 1. His work combines deep analytical techniques from functional analysis, operator theory, and calculus of variations. Applications of his research include image processing, such as MRI denoising, and geometric problems like inverse mean curvature flow. The 15 most recent publications highlight a consistent trend in studying singular limits (especially p → 1), existence and uniqueness of solutions for equations with L1 or measure data, and problems with nonlinear boundary conditions such as Robin or absorption terms. The research spans theoretical analysis of eigenvalues, Gelfand-type problems, and evolution equations, often involving variational methods and renormalized or entropy solutions. No scientific awards are explicitly mentioned in the provided text. Sergio Segura de León has collaborated extensively with leading researchers including Fuensanta Andreu, José M. Mazón, Daniela Giachetti, Anna Mercaldo, and Cristina Trombetti. His work has been supported by various national and international research projects, though specific grants are not detailed. He has advised PhD students, contributing to the training of new researchers in nonlinear PDEs. He is a key member of the EDPNOL research group, which focuses on the analysis and applications of nonlinear partial differential equations, particularly those arising in physics, engineering, and image processing.

• Partial Differential Equations
• Nonlinear Analysis
• Elliptic and Parabolic Equations
• +۶ مورد دیگر

Fernando Lledo Macau is a Full Professor at the Department of Mathematics at University Carlos III of Madrid (UC3M) . His research focuses on Operator Algebras , Quantum Mechanics , and Spectral Theory , with applications to Graph Theory and Mathematical Physics . Recent publications highlight his work on spectral bracketing , magnetic graphs , and Følner sequences in operator algebras. He investigates discrete weighted graphs , quantum symmetries , and amenability in inverse semigroups. His 2025 article on Isospectral graphs and 2024 work on weighted digraphs reflect trends in geometric and spectral analysis. He supervises theses on topics like coarse geometry and magnetic Laplacian matrices , contributing to grants such as QUITEMAD-CM and 6G-INTEGRATION-3 . His collaborations span institutions in Barcelona , Durham , Münster , and ICMAT .

• Operator Algebras
• Quantum Mechanics
• Spectral Theory
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Jordi Ignés-Mullol is a Full Professor in the Department of Materials Science and Physical Chemistry at the Universitat de Barcelona and a member of the Institute of Nanoscience and Nanotechnology. His research focuses on experimental studies of soft condensed matter systems, including active protein suspensions, surfactant and colloidal Langmuir-Blodgett films, driven colloidal suspensions, and liquid crystals. He earned his PhD in Physics from the University of Pittsburgh and conducted postdoctoral research at École Normale Supérieure de Lyon and Tulane University. Research interests include: Pattern formation in complex fluids Dynamics of structures in liquid crystals Microrheology of Langmuir monolayers Active soft matter systems Colloidal assembly under external fields His recent publications explore topological defects in active nematics, liquid crystal-enabled colloid manipulation, and dynamic transitions in soft matter systems. Research trends show strong emphasis on non-equilibrium physics, interfacial phenomena, and experimental techniques development.

• Soft Condensed Matter
• Active Soft Matter
• Langmuir-Blodgett Films
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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.

• Symbolic computation
• Algorithms for differential equations
• Algorithms for difference equations
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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.

• Deep Learning
• Reinforcement Learning
• Inverse Reinforcement Learning
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Antonio Algaba Duran is a Professor at the Higher Technical School of Engineering within the University of Seville , specializing in Applied Mathematics at the Center for Advanced Studies in Physics, Mathematics, and Computing . His research focuses on dynamical systems , nonlinear differential equations , and bifurcation theory , with significant contributions to the analysis of nilpotent singularities , homoclinic/heteroclinic orbits , and chaotic behavior in systems like the Lorenz , Chen , and Lü systems . Education : PhD from University of Seville (1996), thesis on Hypernormal forms and bifurcations in flat and three-dimensional systems , supervised by Emilio Freire Macías and Estanislao Gamero Gutiérrez. Research Highlights : 131+ publications since 1998, including 2 preprints Developed algorithms for normal forms and nonlinear time transformations to analyze canard explosions and homoclinic bifurcations Key work on Z2-symmetric systems , inverse integrating factors , and geometric criteria for centers Collaborators : Cristóbal García, Alejandro J. Rodríguez-Luis, Manuel Merino, Estanislao Gamero, and others. His scientific work spans applications in electronic circuits, biological systems, and physical models, with a focus on structural stability , analytic integrability , and global bifurcations .

• Applied Mathematics
• Dynamical Systems
• Nonlinear Dynamics
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Rodrigo Lecaros Lira is an Associate Professor at Universidad Técnica Federico Santa María, with a research focus spanning Inverse Problems, Control Theory, and Numerical Analysis for Partial Differential Equations. His work bridges mathematical modeling with industrial applications, particularly in mining and fluid mechanics. Educated with a PhD in Engineering Sciences (Mathematical Modeling) and a Bachelor of Science in Engineering (Mathematics) from Universidad de Chile Research interests include Controllability , Stability , and Mathematical Modeling of complex systems such as water waves, shock waves, and discrete/stochastic PDEs. His recent work emphasizes semi-discrete systems and numerical methods for inverse problems. Recent publications show a trend in applying Carleman estimates to controllability problems for semi-discrete and stochastic PDEs, with applications in geophysics and ultrasound modeling. Key subfields include dynamic boundary conditions, non-local formulations, and discrete operators. No scientific awards explicitly mentioned in the provided text. No formal advisees or part-time roles noted. Professional experience includes roles at the Center for Mathematical Modeling (CMM) in Chile and the Basque Center for Applied Mathematics (BCAM) in Spain, focusing on industrial projects like seismic risk assessment (GEOSIS software) and mining-related numerical modeling.

• Inverse Problems
• Partial Differential Equations
• Control Theory
• +۱۲ مورد دیگر

Francisco de Asis Guil Asensio is a Professor at the Faculty of Informatics , Universidad de Murcia , with a research focus spanning partial differential equations , integrable systems , and quantum theory . He holds a PhD in Mathematics (1996) from Universidad de Murcia, with a thesis on automorphism groups and Picard groups of finite-dimensional algebras. Education : PhD in Mathematics, Universidad de Murcia (1996) Thesis: "El grupo de automorfismos y el grupo de Picard de un álgebra finitodimensional" Research Interests : Specializing in soliton equations , nonlinear wave phenomena , and geometric methods in physics , his work bridges mathematical physics and applied mathematics . Key contributions include studies on Dirac-KP correspondence , twistor solutions , and quantum lattice states under magnetic fields. Publications (2007–1980): 15 major works on integrable hierarchies, geometric PDE reductions, and quantum systems. Articles explore topics like dromion deformations , self-dual Yang-Mills , and Heisenberg subalgebras in AKNS systems. Collaborations : Frequent co-authorship with Manuel Mañas on integrable systems (21 joint papers) and Luis Martínez Alonso on Whitham hierarchies. His work is cited in 57 documents across 28 serials. Technical Contributions : Developed spectral methods for Davey-Stewartson equations, applied Grassmannian geometry to soliton hierarchies, and formulated Banach-Lie group frameworks for infinite-dimensional integrability.

• Partial Differential Equations
• Dynamical Systems and Ergodic Theory
• Integrable Systems
• +۴ مورد دیگر

Manuel Pena Rodríguez is an Assistant Professor in the Department of Applied Mathematics I at the School of Industrial Engineering, Universidade de Vigo. His research focuses on numerical methods and inverse problems in mechanical engineering, particularly using topological derivatives for damage detection and electromagnetic imaging. Education: Ph.D. from Universidad Politécnica de Madrid (2021), thesis on topological derivative-based inversion methods for infrared thermography and electromagnetic imaging. Research Interests include structural health monitoring, thermography, acoustic wave propagation, and computational methods. In recent years, he has also contributed to interdisciplinary work in metabolic engineering, evidenced by his 2024 publication in Life . Publications (12 total) primarily focus on applied mathematics and inverse problems, with notable contributions to thermography and electromagnetic datasets. His work trends toward computational methods for defect detection in mechanical systems and interdisciplinary biochemistry applications. Collaboration spans institutions like Universidad Politécnica de Madrid and University of San Diego. He is affiliated with the research group DSN: Design and Numerical Simulation in Mechanical Engineering .

• Applied Mathematics
• Numerical Methods in Engineering
• Structural Health Monitoring
• +۵ مورد دیگر

Roberto Morales is a postdoctoral researcher affiliated with the University of Chile , Department of Engineering Sciences. His academic journey includes a PhD in Engineering Sciences (Mathematical Modelling) from the University of Chile (2019) and a Bachelor in Mathematics from the University of Santiago de Chile (2011). Research Interests Control and stabilization of PDEs Inverse problems Dynamic boundary conditions Mathematical modelling His work focuses on controllability of partial differential equations (PDEs) with dynamic boundary conditions, including Schrödinger and parabolic equations. Recent studies involve discrete Carleman estimates, multi-objective optimization for decentralized learning, and numerical methods for PDE control. Publications His publications span top journals like SIAM Journal on Control and Optimization and Journal of Differential Equations , with a trend toward controllability analysis and inverse problems in PDEs. Key collaborations include U. Biccari and J. Dardé.

• Control Theory
• Inverse Problems
• Partial Differential Equations
• +۱ مورد دیگر