جستجوی استاد راهنمای دانشگاهی

Gonzalo Manzano Paule is a Ramón y Cajal tenure-track researcher at IFISC (Instituto de Física Interdisciplinar y Sistemas Complejos), a joint research institute of CSIC (Consejo Superior de Investigaciones Científicas) and UIB (University of the Balearic Islands), where he has been working since January 2023. He previously held a Juan de la Cierva Incorporation fellowship (2021-2023), was an ESQ Postdoc at IQOQI Vienna (2020-2021), and a Postdoc at ICTP Trieste (2018-2020) funded by Scuola Normale Superiore. He obtained his PhD in Physics from Universidad Complutense de Madrid in July 2017, followed by a short Postdoc at IFISC (2017-2018). His research interests focus on quantum and stochastic thermodynamics, open quantum systems, information theory, and the foundations of nonequilibrium statistical physics and quantum mechanics. He is particularly interested in applying concepts from nonequilibrium thermodynamics to understand classical and quantum complex systems. While his work is primarily theoretical, he actively seeks collaborations with experimentalists. His research has been featured in popular science journals including Physics, Quanta Magazine, and Diario de Mallorca. He has also collaborated with artist Evarist Torres to merge art and science and has written a popular science article for Investigación y Ciencia (Scientific American). Manzano Paule's recent publications demonstrate a strong focus on quantum thermodynamics, fluctuation theorems, and quantum information processing. His work spans theoretical foundations of quantum thermodynamics to applications in quantum heat engines and molecular motors. A notable pattern in his research is the exploration of how quantum effects can enhance thermodynamic processes and the relationship between information theory and thermodynamics. His scientific achievements have been recognized through prestigious fellowships including the Ramón y Cajal program, Juan de la Cierva Incorporation fellowship, and ESQ Postdoc fellowship. His work has also garnered attention in popular science media, indicating its broader impact beyond academic circles. As an educator, Manzano Paule supervises Master's students and teaches advanced courses including Open Quantum Systems for the Master's Degree in Advanced Physics and Applied Mathematics and the Master's Degree in Physics of Complex Systems. His teaching portfolio also includes Quantum Collective Phenomena, Quantum and Nonlinear Optics, Thermodynamics, and Atomic and Molecular Physics. He currently leads the research project 'QTD-InFlexity Quantum thermodynamics: information, fluctuations and complexity' and participates in the 'CoQuSy Complex Quantum Systems' project. He is also part of the María de Maeztu Unit of Excellence at IFISC, which has received continuous funding since 2008.

• Quantum Thermodynamics
• Stochastic Thermodynamics
• Open Quantum Systems
• +۵ مورد دیگر

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
• +۹ مورد دیگر

Maria Elena Martin Cañadas is an Associate Professor at the Department of Electrical Engineering within the Barcelona East School of Engineering (EEBE) at Universitat Politècnica de Catalunya (UPC). She leads research at the SEPIC group (Power Electronics and Control Systems), focusing on renewable energy integration and power systems optimization. Research Interests: Her work spans power electronics, microgrid design, energy policy analysis, and control systems for distributed generation. Key research areas include: Regulatory frameworks for renewable energy adoption Uncertainty modeling in energy systems High-temperature heat pump technologies Economic optimization of microgrids Solar energy integration and policy analysis Publication Trends: Recent articles (2020-2025) demonstrate strong focus on regulatory impacts in energy systems, with methodologies addressing uncertainty through stochastic modeling and probabilistic analysis. Dominant themes include microgrid optimization, solar policy evolution, and decarbonization strategies for industrial applications. Student Advising & Projects: Supervised doctoral candidates include Alonso (microgrid design), Coronas (distributed generation), and El Mariachet (power quality). Actively leads competitive R&D projects such as: Decarbonization of energy-intensive industries Power quality improvement in remote systems Regulatory framework development for Latin American biogas projects Research Group: Core member of SEPIC laboratory specializing in power electronics applications for sustainable energy systems, collaborating with industrial and international partners.

• Power Electronics
• Renewable Energy Systems
• Microgrids
• +۳ مورد دیگر

Lorenzo Steccanella is a Postdoctoral Researcher at Universitat Pompeu Fabra in Barcelona, Spain, specializing in Reinforcement Learning and Artificial Intelligence. He holds a Ph.D. in Reinforcement Learning from the same institution (2023), focusing on Hierarchical Reinforcement Learning and Representation Learning. His research emphasizes long-horizon decision-making, generative vision models, and applications in autonomous systems. **Education**: Ph.D. in Reinforcement Learning (Universitat Pompeu Fabra, 2023). **Research Interests**: Hierarchical Reinforcement Learning, Representation Learning, Computer Vision for Robotics, Multi-Agent Systems, and Autonomous Navigation. He has contributed to projects such as obstacle detection for autonomous boats (Blue Brain Project/EPFL) and localization algorithms for mobile robots (University of Verona). **Articles Trends**: His work spans Reinforcement Learning theory, computer vision applications in robotics, and multi-agent coordination. Recent publications emphasize hierarchical methods and representation learning, while earlier work includes path planning for articulated vehicles and Petri net-based multi-robot systems. **Awards**: No scientific awards explicitly mentioned. **Labs/Teams**: Current affiliation with Universitat Pompeu Fabra's AI/ML group. Previously contributed to the Blue Brain Project (EPFL) and the Intcatch Project at the University of Verona.

• Reinforcement Learning
• Artificial Intelligence
• Computer Vision
• +۵ مورد دیگر

Jesús Martínez Frutos is a Professor specializing in computational mechanics and soft robotics, with a strong focus on integrating machine learning with multiphysics simulations. His research bridges constitutive modeling, topology optimization, and electroactive polymers to advance soft robotic systems and smart material design. His primary research domains include: Computational Mechanics (finite strain electromechanics, hyperelasticity) Physics-Informed Machine Learning (neural networks, Gaussian processes) Topology Optimization (lattice structures, band gap engineering) Soft Robotics (shape-morphing actuators, dielectric elastomers) Multiphysics Simulation (thermo-electro-mechanics, flexoelectricity) He pioneers methods for embedding physical constraints into data-driven models, particularly for nonlinear material behavior under large deformations. Analysis of his 15 most recent publications (2022-2025) reveals three dominant trends: (1) Physics-augmented neural networks for constitutive modeling that enforce thermodynamic consistency; (2) Multi-material topology optimization for programmable electroactive structures; (3) Gradient-enhanced machine learning frameworks that capture material uncertainties. His work consistently targets real-world applications in soft robotics and energy-efficient actuation systems. Professor Martínez Frutos actively supervises graduate theses as indicated by his profile's dedicated section, though specific student names aren't listed. His research is supported by institutional funding referenced in the profile's funding section, with emphasis on computational methods for next-generation soft robotic systems. Current projects focus on 3D-printed dielectric elastomer actuators and probability-based optimization for safety-critical applications.

• Computational Mechanics
• Soft Robotics
• Topology Optimization
• +۵ مورد دیگر

Francisco Jurado Melguizo is a Professor in the Department of Electrical Engineering at Universidad de Jaén. His research focuses on power systems, renewable energy integration, and optimization algorithms, with over 520 JCR-indexed publications and 260 conference papers. He has led projects funded by Spanish Ministries and the European Commission and authored 8 books. PhD: Universidad Nacional de Educación a Distancia (UNED), 1999 His work spans distributed generation, energy storage, smart grids, and techno-economic analysis, often incorporating AI and metaheuristic optimization techniques. Recent projects include hybrid renewable systems, EV charging infrastructure, and grid resilience under climate uncertainties. He has received recognition as one of the most influential researchers globally by Stanford University and contributes to research groups focused on electrical technology and energy systems.

• Power Systems
• Renewable Energy
• Energy Storage
• +۳ مورد دیگر

Prof. Vicente Perez Muñuzuri is a University Professor at the Department of Particle Physics in the Faculty of Physics at the University of Santiago de Compostela. He holds a PhD from the same institution (1992) with a thesis on reaction-diffusion systems and super-spiral waves. His research focuses on nonlinear physics, fluid dynamics, and interdisciplinary environmental technologies. Key affiliations include the GFNL Nonlinear Physics Group and the Center for Interdisciplinary Research in Environmental Technologies (CRETUS). He has published extensively on topics like wave energy resource assessment using HF radars, spatiotemporal chaos, chemical reaction dynamics, and atmospheric modeling. Notable works include studies on spiral wave behavior in Chua's circuits, noise-enhanced wave propagation, and advective transport impacting plankton blooms. His research integrates experimental, numerical, and theoretical methods across physics, chemistry, and engineering. Vicente has collaborated on projects involving oceanographic modeling, pollutant transport forecasting (e.g., Prestige oil spill), and atmospheric studies using cosmic-ray detectors. His work bridges fundamental physics with applied challenges in renewable energy, environmental monitoring, and biophysical systems.

• Nonlinear Physics
• Reaction-Diffusion Systems
• Fluid Dynamics
• +۷ مورد دیگر

Álvaro Rodríguez Rivas is a Researcher at the Department of Physical, Chemical and Natural Systems at the University of Pablo de Olavide . He is affiliated with the Centro de Nanociencia y Tecnologías Sostenibles (CNATS) and part of the FISICA ESTADISTICA DE LIQUIDOS research group. His work focuses on statistical physics of liquids, phase transitions, and granular dynamics. 2008: BSc in Physics, University of Seville 2016: PhD in Colloid and Interface Science, University of Pablo de Olavide Dr. Rodríguez-Rivas specializes in Statistical Physics of Liquids , Phase Transitions , and Granular Media . His research spans simple fluid adsorption, critical phenomena, and active matter dynamics, with a strong computational focus on Monte Carlo and molecular dynamics simulations. Recent work examines biofilm growth and chiral flows in two-dimensional systems. The 15 most recent articles reflect trends in biofilm simulation , phase transitions in fluids , active matter , and granular convection . Key topics include computational modeling of bacterial interactions, critical point analysis in attractive fluids, and chiral symmetry in active disk mixtures. He has undertaken research stays at Imperial College London , Johannes Gutemberg University of Mainz , and Carlos III University of Madrid , and collaborates on projects related to soft matter and sustainable nanoscience.

• Statistical Physics of Liquids
• Simple and Complex Liquids
• Phase Transitions
• +۵ مورد دیگر

Gonzalo Manzano is a Ramón y Cajal tenure-track researcher at IFISC (CSIC-UIB) since January 2023, holding an Assistant Professor equivalent position at the University of the Balearic Islands. Previously, he was a Juan de la Cierva Incorporation fellow (2021-2023), ESQ Postdoc at IQOQI Vienna (2020-2021), and Postdoc at ICTP Trieste (2018-2020) funded by Scuola Normale Superiore. He earned his PhD in Physics from Universidad Complutense de Madrid in July 2017, followed by a Postdoc at IFISC (2017-2018). His research spans quantum thermodynamics, stochastic thermodynamics, open quantum systems, information theory, and foundations of nonequilibrium statistical physics. He's particularly interested in applying nonequilibrium thermodynamics concepts to understand classical and quantum complex systems. His work is primarily theoretical but includes collaborations with experimentalists. He leads the QTD-InFlexity project on quantum thermodynamics and co-leads the CoQuSy project on complex quantum systems. Analysis of his recent publications reveals a strong focus on quantum thermodynamic frameworks, fluctuation theorems, quantum information processing, and applications to molecular motors and quantum devices. His work bridges theoretical foundations with potential applications in quantum technologies and biological systems, showing consistent output with 15+ publications annually through 2025. Scientific Recognition: Recipient of prestigious Ramón y Cajal Fellowship Featured in Physics, Quanta Magazine, and Diario de Mallorca Published popular science article in Investigación y Ciencia Collaborated with artist Evarist Torres merging art and science Manzano actively supervises master's students, with four documented theses completed between 2022-2024 on topics including quantum absorption refrigerators, molecular motor thermodynamics, and energy conversion in thermal machines. His research profile shows strong international collaboration across European institutions and theoretical physics centers.

• Quantum Thermodynamics
• Stochastic Thermodynamics
• Open Quantum Systems
• +۴ مورد دیگر

Aniello Lampo is an Assistant Professor in the Department of Mathematics at Carlos III University of Madrid, where he researches complex systems within the Complex Systems Interdisciplinary Group (GISC). His work spans theoretical biology, statistical physics, and network science. His research investigates emergent phenomena in biological and urban systems, including microbial community dynamics, plant-pollinator networks, and urban congestion patterns. Recent publications reveal new macroecological patterns beyond Taylor's law and analyze structural dynamics in mutualistic ecological networks. Publications demonstrate consistent interdisciplinary approaches, combining theoretical physics with biological applications. Earlier quantum physics research includes polaron dynamics, quantum thermometry, and non-Markovian systems, showing broad theoretical expertise. No scientific awards or advised students are documented. He contributes to understanding complex adaptive systems through mathematical modeling and computational approaches at the physics-biology interface.

• Complex Systems
• Theoretical Biology
• Statistical Physics
• +۱ مورد دیگر

Cristina Brandle Cerqueira is an Associate Professor in the Department of Mathematics at the University Carlos III of Madrid, serving as Assistant Vice-Rector for Teaching and Research Staff. Her research focuses on nonlinear partial differential equations, with a particular emphasis on nonlocal equations, fractional Laplacian, and ergodic problems. She has contributed to studies on phase transitions, Hamilton-Jacobi equations, and blow-up phenomena in parabolic systems. Her work integrates theoretical analysis and applications in areas such as population models and material science. Brandle Cerqueira holds a position in the academic leadership, overseeing research and teaching policies. She has been involved in significant research projects funded by institutions like the Ministry of Economy, Trade, and Industry (Spain) and the State Agency for Research. Her collaborations include international stays at the University of Tours (France) to study nonlocal Hamilton-Jacobi equations and numerical methods for Stefan problems. Her publications span high-impact journals like Nonlinear Analysis, SIAM Journal on Mathematical Analysis, and Transactions of the American Mathematical Society. Key areas of her research include nonlocal diffusion processes, ergodic control, and the mathematical modeling of phase transitions with mid-range interactions. She has also explored numerical methods for handling blow-up in parabolic systems and contributed to the theoretical foundations of nonlocal heat equations.

• Nonlinear Partial Differential Equations
• Fractional Laplacian
• Nonlocal Diffusion
• +۵ مورد دیگر

Dr. Emanuel Gastón Mompó Pavesi is an Assistant Professor in the Institute for Research in Technology (IIT) at Comillas Pontifical University, School of Engineering (ICAI), Madrid, Spain. He joined the institution in January 2023 and is affiliated with the Intelligent Systems research area. His academic background includes a Ph.D. in Mathematical Engineering from Universidad Carlos III de Madrid (2019), where he also served as a lecturer until 2022, and a B.Sc./M.Sc. in Mathematics from Universitat de València (2014). Ph.D. in Mathematical Engineering, Universidad Carlos III de Madrid (2019) B.Sc. & M.Sc. in Mathematics, Universitat de València (2014) His research spans nonlinear dynamical systems and nonequilibrium statistical mechanics, with emphasis on chaotic behavior, noise effects, memory, and anomalous relaxation in physical systems. He also explores applied mathematics topics such as numerical methods, optimization, inverse problems, and machine learning. His recent publications in journals like Physical Review Letters , Physical Review E , and Entropy reveal a strong focus on semiconductor superlattices, geometric diffusion, and relaxation dynamics in many-body systems. These works often intersect chaos, noise, and memory to develop novel physical insights and potential applications. Dr. Mompó is an active reviewer for Physical Review Letters and Physical Review E since 2018. He has delivered multiple invited seminars and organized scientific events, including the Junior Seminars at the Gregorio Millán Barbany Institute. He has also contributed to science communication through media appearances, such as the podcast "Casting the Future." While no formal students are listed, his involvement in mentoring through seminars and conference organization suggests academic leadership. He has not received explicitly mentioned scientific awards, but his publication record in top-tier journals indicates strong recognition in his field. He is involved in research dissemination and education, including upcoming training on AI for teaching and assessment at Comillas. His work is grounded in theoretical and applied physics, with potential applications in random number generation, signal processing, and complex system modeling.

• Non-linear dynamical systems
• Statistical mechanics out of equilibrium
• Complex systems
• +۱۱ مورد دیگر

Antonio Fernández-Ramos is a Full Professor in the Department of Physical Chemistry at the University of Santiago de Compostela (USC), where he leads the Fernández-Ramos Research Group specializing in theoretical and computational chemistry. His research focuses on chemical reaction dynamics with particular expertise in proton transfer reactions, quantum tunneling effects, and computational methods development. His research interests span chemical reaction dynamics, proton transfer reactions, computational chemistry methods, quantum tunneling, thermochemistry of flexible molecules, combustion chemistry, and ultra-low temperature chemistry. He has pioneered the development of the Approximated Instanton Method (AIM) for simulating multidimensional proton transfer reactions and created several computational tools including Pilgrim, Q2DTor, and Torsiflex that form part of the Cathedral software package under MIT license. His recent publications reveal a strong focus on computational reaction dynamics applied to combustion systems and interstellar chemistry, with particular emphasis on biofuel decomposition, hydrogen transfer reactions, and quantum effects at cryogenic temperatures. His work bridges theoretical chemistry with practical applications in energy and astrochemistry. Prize of the Royal Spanish Society of Chemistry to Young Researchers (2003) Professor Fernández-Ramos has supervised two PhD theses and maintains active collaborations with international researchers including Donald Truhlar at the University of Minnesota and scientists at the National Research Council of Canada. His research group has secured multiple projects focused on integrated computational protocols for chemical kinetics, with applications ranging from organometallic catalysis to atmospheric chemistry. The Fernández-Ramos Research Group operates within USC's Theoretical and Computational Chemistry framework, developing and applying advanced computational methods through their Cathedral software suite. Their work integrates quantum chemistry calculations with kinetic modeling to address complex chemical systems, particularly focusing on reactions involving flexible molecules and quantum tunneling phenomena across extreme temperature ranges.

• Chemical Reaction Dynamics
• Proton Transfer Reactions
• Computational Chemistry
• +۵ مورد دیگر

Batet Miracle, Lluis is a Professor of Nuclear Engineering at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Physics and the Advanced Nuclear Technologies Research Group (ANT). His research focuses on nuclear energy systems, thermalhydraulics, reactor safety, and fusion technology. He leads projects on liquid metal systems, hydrogen permeation in fusion materials, and nuclear education initiatives. His work involves computational modeling, experimental validation, and policy analysis to advance sustainable energy solutions. Lluis has authored over 267 publications and actively collaborates with international organizations like EURATOM. He directs the Master's Degree in Nuclear Engineering and contributes to the development of next-generation nuclear technologies. Education: Advanced academic background in Physics and Nuclear Engineering (details inferred from professional role). Affiliations: ANT Research Group, UPC Faculty of Engineering, Multiple EU-funded projects. Research Interests: Nuclear energy policy, reactor safety systems, liquid metal coolants, fusion technology, and energy sustainability. His work bridges fundamental physics with applied engineering challenges in nuclear systems. Articles Trends: Recent work emphasizes helium behavior in lead-lithium alloys, nanobubble dynamics in liquid metals, and computational modeling for fusion applications. These studies address critical issues in material compatibility and safety for advanced reactors.

• Nuclear Engineering
• Thermalhydraulics
• Reactor Safety
• +۴ مورد دیگر

Michel Frising is a Postdoctoral Researcher at the Autonomous University of Madrid (UAM), affiliated with the Nanophotonics Group within the Faculty of Sciences. His primary appointment is in the Department of Theoretical Condensed Matter Physics. He completed his PhD in 2022 at UAM, focusing on machine learning applications in nanophotonics, under co-advisors Ferry Prins and Jorge Bravo Abad. Prior to UAM, he conducted MSc research at ETH Zurich and the University of Wisconsin-Madison. His research interests center on developing generative modeling techniques using neural networks to enable inverse design of photonic structures and explore complex parameter spaces. Education: PhD in Condensed Matter Physics, Nanoscience, and Biophysics (UAM, 2022) MSc in Micro and Nanosystems (ETH Zurich, focus: photonics/nano-optics) MSc thesis at University of Wisconsin-Madison with Prof. Mikhail Kats on color vision enhancement devices Research Trends: His publications highlight advancements in machine learning for photonic design, exciton dynamics in perovskites, and biomedical optics innovations. Key areas include invertible neural networks for multimodal device optimization, hyperspectral imaging of biomaterials, and passive frequency conversion using nanocrystals. Awards: Cum Laude distinction for PhD thesis LaCaixa INPhINIT Fellowship Advising/Grants: No formal advisees listed. His work is supported through institutional funding and collaborations within IFIMAC and EU projects like MIRAQLS. Labs/Teams: Core member of the Nanophotonics Group, contributing to interdisciplinary projects at the interface of materials science and computational photonics.

• Nanophotonics
• Machine Learning
• Inverse Design
• +۳ مورد دیگر