Sergio Bermudo Navarrete is a Professor at the Department of Economics, Quantitative Methods and Economic History, Universidad Pablo de Olavide. His research spans combinatorics, graph theory, and operator theory. Education: PhD in Mathematics (2003, University of Seville) with thesis on functional models of operators in Hilbert spaces. Research Interests: Focus on graph theory, domination problems, topological indices, and operator theory. Publication Trends: Recent work includes vertex-degree-based indices for oriented graphs, domination parameters in product graphs, and differential analysis of line graphs. Keywords span Computer Science , Mathematical Chemistry , and Operations Research . Collaborations: Frequent co-authors: José María Sigarreta Almira, José Manuel Rodríguez García, Juan Alberto Rodríguez-Velazquez. Contact: Email sbernav@upo.es .
Carlos Alvarez Martinez is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture at the Barcelona School of Informatics (FIB). He is a key member of the Programming Models (PM) research group and collaborates closely with the Barcelona Supercomputing Center (BSC). His research focuses on high-performance computing, FPGA acceleration, task-based programming models like OmpSs, and hardware-software co-design for heterogeneous systems. His research interests center on advancing parallel computing through innovative programming models and hardware acceleration. He investigates efficient task scheduling, resource management in multicore and FPGA-based systems, and runtime support for dataflow models. His work enables high-performance execution of complex applications in domains such as scientific computing and cyber-physical systems. He actively contributes to European initiatives like TEXTAROSSA and AXIOM, aiming to develop next-generation exascale supercomputing technologies. The trend in his recent publications shows a strong focus on leveraging FPGAs for HPC, optimizing SpMV operations, improving task scheduling with hardware support, and developing frameworks for multi-FPGA clusters. His work consistently bridges theoretical models with practical implementations, emphasizing performance, scalability, and energy efficiency in heterogeneous computing environments. Scientific Awards: Premi UPC al Compromís Social 2019 Premi Disseny per al Reciclatge 2013 Alvarez Martinez has advised or collaborated with several doctoral students, including Jaume Bosch, Xubin Tan, and Fahimeh Yazdanpanah. He has been involved in numerous competitive R&D projects, often related to high-performance computing and parallel programming models. His work includes significant contributions to educational innovation, particularly in active learning methodologies and formative assessment using interactive systems. He leads and participates in research labs and teams focused on programming models and computer architecture, notably the PM group at UPC/BSC. These teams develop runtime systems, compilers, and hardware accelerators to push the boundaries of parallel computing efficiency and programmability.
Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.
Jacob D. Leshno is an Associate Professor of Economics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research employs game theory, applied mathematics, and microeconomic theory to study allocation mechanisms and marketplace design, with applications spanning school choice systems, patient assignments to nursing homes, and decentralized cryptocurrency protocols. Professor Leshno's academic background includes: PhD in Economics from Harvard University, completed under Nobel laureate Alvin Roth M.Sc. in Pure Mathematics from Tel Aviv University B.Sc. in Pure Mathematics from Tel Aviv University His research program centers on market design theory with two primary strands. The first focuses on matching markets, where he developed tractable cutoff characterizations that clarify market structures for college admissions and medical residency matching (NRMP). His work demonstrates how price discovery mechanisms can streamline inefficient processes like college applications and subsidized housing allocation. The second strand examines cryptocurrencies and blockchain technology, investigating how open-source computer code functions as market rules in decentralized systems. This research explores both the economic security of permissionless consensus and fundamental limitations of proof-of-work protocols. Professor Leshno's publications reveal a cohesive research trajectory applying economic theory to increasingly complex market structures. His work consistently bridges theoretical rigor with practical implementation, evolving from traditional matching markets to the frontier of decentralized digital systems. Publications in top journals like American Economic Review and Journal of Political Economy demonstrate both analytical depth and real-world relevance across education, healthcare, and financial technology sectors. Professor Leshno has received significant recognition for his contributions: ACM SIGecom Test of Time Award for foundational work in matching markets INFORMS Frederick W. Lanchester Prize for outstanding contributions to operations research Prior to Chicago Booth, Professor Leshno served as Assistant Professor at Columbia Business School and completed a postdoctoral fellowship at Microsoft Research New England, following industry experience at Yahoo! and IBM. He teaches MBA courses in Competitive Strategy and Market Design, and developed a PhD seminar bridging computer science theory with economic principles for distributed systems. His research continues to influence both academic theory and practical implementations of market mechanisms across multiple sectors. Professor Leshno maintains active collaborations with leading researchers including Itai Ashlagi, Irene Lo, and Gur Huberman, advancing the theoretical foundations of market design while addressing contemporary challenges in digital marketplaces and allocation systems.
Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.
Albert Atserias is a Professor in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Informatics of Barcelona (FIB) and the ALBCOM research group (Algorithms, Bioinformatics, Complexity, and Formal Methods). He is also associated with the Institut de Matemàtiques de la UPC-BarcelonaTech. His research is central to theoretical computer science, with a strong emphasis on logic and complexity. Atserias's research interests span Computational Complexity, Logic in Computer Science, Finite Model Theory, Proof Complexity, and Constraint Satisfaction Problems . His work explores the fundamental limits of computation, the expressive power of logical languages over finite structures, and the complexity of proving mathematical statements. He investigates the algebraic and combinatorial properties of proof systems, the limits of efficient algorithms for constraint solving, and the theoretical foundations of databases. His research often bridges logic, algebra, and combinatorics to provide deep insights into computational phenomena. The trends in his recent publications show a sustained focus on the logical and algebraic underpinnings of computational problems. Key themes include the consistency and complexity of database queries , the power and limitations of proof systems (like resolution and sum-of-squares), and the expressive power of homomorphism counts in graph theory. His work on the hardness of automating resolution and the development of circular proof systems are particularly significant contributions to proof complexity. The 2024 PODS Best Paper Award for work on relational consistency underscores the impact and timeliness of his research. Among his notable scientific awards are the prestigious ICREA Acadèmia , the PODS 2024 Best Paper Award , the Premi Extraordinari de Doctorat (Extraordinary Doctoral Prize), and the Kleene Award for Best Student Paper . These accolades reflect both the excellence of his early work and his continued leadership in the field. Atserias has been a principal investigator on numerous competitive research projects, including funding from the European Research Council (ERC) and the Spanish Ministry of Science. He has advised doctoral students, such as Toni Hakoniemi, whose thesis on proof complexity he supervised. His extensive collaborative network includes leading researchers like Phokion Kolaitis, Anuj Dawar, and Victor Dalmau. He has also served on the scientific committees of major conferences, contributing to the academic community. He is a core member of the ALBCOM research group , a leading team at UPC focused on theoretical aspects of computer science, which provides a vibrant environment for research in algorithms, complexity, and formal methods. His work is also connected to the broader Institut de Matemàtiques de la UPC, fostering interdisciplinary collaboration between computer science and mathematics.
Carles Padro Laimon is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mathematics and the School of Telecommunications Engineering. He is a leading researcher in cryptography and information security, focusing on secret sharing schemes, combinatorial structures, and cryptographic protocols. His work integrates discrete mathematics, coding theory, and algorithmic design to address security challenges in digital systems. Padro leads the MAK Research Group (Mathematics Applied to Cryptography) and the ISG-MAK Information Security Group. He has been involved in numerous competitive research projects, including initiatives on post-quantum cryptography and secure multi-user systems. His contributions span over 211 documented activities, including articles, theses, and conference participations. His research interests include the theoretical foundations of cryptography, with a focus on optimizing secret sharing schemes, analyzing matroid-based structures, and developing secure communication protocols. He has collaborated extensively with institutions like the UPC and European research networks, contributing to both academic and practical advancements in cybersecurity. Padro holds a PhD in Mathematics from UPC and has supervised doctoral theses and mentored researchers in his field. His work frequently appears in top journals like IEEE Transactions on Information Theory, Designs, Codes and Cryptography, and SIAM Journal on Discrete Mathematics.
Seth Blumsack is a Professor at the Pennsylvania State University in the Department of Energy and Mineral Engineering and serves as Director of the Center for Energy Law and Policy . He holds an Adjunct Research Professor position at the Carnegie Mellon Electricity Industry Center and is affiliated with the Santa Fe Institute as an External Faculty member. His research spans energy economics , power grid reliability , and complex infrastructure networks . Key projects include: Interdependent natural gas and electricity systems analysis Governance of regional transmission organizations Smart grid consumer behavior studies Power grid reliability tools development He has secured funding from the U.S. National Science Foundation , Department of Energy , Environmental Protection Agency , and private industry. His Best paper award at Hawai’i International Conference on System Sciences (2011) and John T. Ryan, Jr. Fellowship (2011-17) highlight his scientific recognition. Publications emphasize electricity market deregulation , energy infrastructure resilience , and consumer response to smart grid technologies . His work has been cited in major media outlets like The New York Times and The Los Angeles Times , and he has consulted for National Renewable Energy Laboratory , U.S. Department of Energy , and other industry stakeholders.
Gil Serrancoli Masferrer is an Associate Professor in the Department of Mechanical Engineering at the School of Engineering of East Barcelona (EEBE), part of the Polytechnic University of Catalonia (UPC). He is affiliated with the InSup - Research Group in Surface Interaction in Bioengineering and Materials Science and the LAM - Multimedia Applications and ICT Laboratory. His work focuses on biomechanics, computational modeling, and telerehabilitation systems development for clinical applications. Dr. Serrancoli's research spans multisolid dynamics, dynamic optimization, movement simulation, and telerehabilitation systems. His expertise lies in applying computational techniques to solve complex problems in orthopedics, gait analysis, and rehabilitation engineering. His work bridges mechanical engineering with biomedical applications, particularly in musculoskeletal modeling and simulation of orthopedic procedures. He has developed novel computational frameworks for estimating internal musculoskeletal loading and muscle adaptation in various conditions, including hypogravity environments. His recent publications demonstrate a strong focus on in-silico modeling of orthopedic procedures, particularly knee osteotomies (proximal fibular osteotomy versus high tibial osteotomy), with detailed analysis of joint pressure redistribution. He has also pioneered the application of machine learning techniques, particularly recurrent neural networks, to biomechanical problems including cycling biomechanics and running dynamics prediction. His work consistently integrates computational efficiency with clinical relevance. Technical Award - OpenSim+ Advanced Workshop March 2024 Accésit del XLV Congreso de la Sociedad Ibérica de Biomecánica y Biomateriales European Society of Biomechanics Travel Award OpenSim Virtual Workshop - Technical Award OpenSim Visiting Scholar 2017 Enginyers BCN 2018 Dr. Serrancoli leads several competitive R&D projects including 'Muvity: a novel physical telerehabilitation system' for vulnerable populations and 'Simulaciones predictivas in silico para cirugías ortopédicas' (Predictive in-silico simulations for orthopedic surgeries). He collaborates extensively with researchers across Europe, particularly with Jordi Torner, Josep Maria Font Llagunes, and Joan Carles Monllau, and has secured funding from national and regional programs including Plan Estatal de Investigación Científica y Técnica y de Innovación. He is actively involved in the BIOMEC - Biomechanical Engineering Lab and the TecSalut - Research Group in Health Technologies, where he contributes to the development of innovative solutions for healthcare challenges, particularly in the areas of telerehabilitation and computational biomechanics for orthopedic applications.
Alejandro F. Villaverde is a Ramón y Cajal research fellow in the Department of Systems & Control Engineering at the School of Industrial Engineering, University of Vigo, Spain. He also serves as a Research fellow at CITMAga since 2022. Previously, he worked as a postdoctoral researcher at IIM-CSIC from 2016-2020. His research focuses on the modeling of dynamical systems with particular emphasis on biological applications. Villaverde earned his PhD in Systems and Control Engineering from University of Vigo between 2005 and 2009. His academic career has centered at Spanish institutions with a strong interdisciplinary approach bridging engineering, mathematics, and biology. His primary research interests include systems biology, control theory, and mathematical modeling, with specialized expertise in structural identifiability, observability analysis, and computational tools for dynamic modeling of biological systems. Villaverde's work addresses fundamental challenges in building reliable mathematical models of complex biological processes, with applications spanning immunology to microbial communities. His theoretical contributions have practical implications for improving model reliability and predictive power in biological research. Villaverde has published extensively in top journals including PLOS Computational Biology, Bioinformatics, and IEEE/ACM Transactions on Computational Biology. His recent publications (2023-2025) reveal a consistent research trajectory focused on developing theoretical frameworks for biological model analysis, creating practical software tools, and applying these methods to cutting-edge problems. His work shows particular strength in identifying and addressing fundamental limitations in modeling approaches, especially regarding parameter identifiability and model observability constraints. Among the top 2% Scientists Worldwide 2024 (Stanford University list) Recognition as one of the EEI's top valued instructors at University of Vigo's School of Industrial Engineering Villaverde leads multiple significant research projects including DYNAMO-bio (funded by Ministry of Science, Innovation and Universities), SICOMORO (focusing on symmetries in biological communities), and PREDYCTBIO. His group actively develops open-source software tools such as STRIKE-GOLDD for structural identifiability and observability analysis. The laboratory, part of the BICO research group, includes several researchers and students working on various aspects of dynamic modeling in biology, with recent additions including Mahmoud Shams Falavarjani, Adriana González Vázquez, and multiple interns working on specialized projects.
Sonia Machause López is a Lecturer in the Department of Prehistory and Archaeology at the Faculty of Geography and History, University of Valencia. She is a member of the GRAM Archaeological Research Group on the Mediterranean and holds a PhD from the University of Valencia (2017) on ritual caves in the Iberian Iron Age. Her work bridges archaeological theory, landscape analysis, and sensory studies, focusing on ritual practices in natural spaces. PhD in Mediterranean Prehistory and Archaeology, University of Valencia (2017) Thesis: Caves as ritual spaces in Iberian Iron Ages: the cases of Kelin, Edeta and Arse Supervisors: Dr. Consuelo Mata Parreño, Dr. Carmen Aranegui Gascó Her research centers on Iberian Iron Age ritual practices, particularly the use of caves as sacred spaces. She integrates GIS, archaeoastronomy, and sensory archaeology to explore ritual landscapes, territoriality, and embodied experiences. Her work emphasizes multisensory dimensions, ritual journeys, and the symbolic role of water and darkness in underground spaces. She has published extensively on sites such as Cueva del Sapo, Sima de l'Aigua, and Cova de les Dones. Her recent publications reveal a strong trend toward interdisciplinary methodologies, combining material analysis with spatial and sensory modeling. She frequently collaborates with experts in archaeozoology, geophysics, and ethnography. Her work challenges elite-centric models of ritual, emphasizing community participation and variability in religious experiences. Enduring Sacred Places: The Astronomical Orientation of the Iberian Cave-Sanctuary of Cueva Santa del Cabriel in Spain (2019) Caves, Senses, and Ritual Flows in the Iberian Iron Age: The Territory of Edeta (2022) Delving into the Iberian rituality of the Sima de l'Aigua (2024) Sonia Machause López actively mentors early-career researchers and participates in academic dissemination, including public talks and gender studies in archaeology. She has contributed to projects on women in universities and archaeological outreach. While no specific grants are listed, her sustained research output suggests active funding support. She is affiliated with the GRAM research group, which focuses on Mediterranean archaeological dynamics, ritual landscapes, and material culture. Her work often involves field prospection, laboratory analysis, and collaborative interpretation across disciplines.
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.
Dr. José Miguel Morales Asencio is a University Professor in the Department of Nursing at the University of Málaga (UMA) since 2010. He served as Department Director from 2010 to 2018 and currently holds the roles of Vice Dean of Research and Postgraduate Studies and Coordinator of the Doctoral Program in Health Sciences (since 2020). He is a visiting professor at several universities, including the University of Hertfordshire (UK) and Coimbra (Portugal). Research Interests : His work focuses on Health service models for chronic and dependent populations Gender inequalities in chronic disease Clinical safety and risk management Knowledge translation in healthcare Advanced nursing practice He leads the CTS-970 research group on "Chronicity, Dependency, Care, and Health Services" under the Biomedical Research Institute of Málaga (IBIMA) and is a member of the European Academy of Nursing Science. Article Trends : His recent publications address evidence-based nursing, chronic disease management, and clinical safety. Key areas include multimorbidity prediction, caregiver health economics, and transcultural validation of assessment tools. Grants & Projects : He has led 13 funded projects, including the 2023-2025 Spanish Cancer Association-funded Cui-DAR Cudeca Plan validation study (€133,412) and the 2020-2023 Ministry of Health-funded clinical prediction rule study (€55,535). His work spans randomized trials, longitudinal cohort studies, and systematic reviews. Advising : He has directed 45+ PhD theses, such as "Effectiveness of hydrophobic dressings in vascular ulcers" and "Impact of socioeconomic factors on caregiver burden." Labs & Teams : Collaborates with the European Academy of Nursing Science and IBIMA, integrating healthcare policy and clinical research.
Ignacio Insua López is a Ramón y Cajal researcher at the University of Santiago de Compostela (Spain), affiliated with the Department of Pharmacology, Pharmacy and Pharmaceutical Technology within the Faculty of Pharmacy. He leads research in the ID-FARMA group, focusing on drug delivery systems and supramolecular peptide nanomaterials. His work is conducted at the Research Center in Biological Chemistry and Molecular Materials (CIQUS) and the Strategic Grouping in Materials (AEMAT). Dr. Insua López holds a PhD from the University of Birmingham (UK), awarded in 2017 for his thesis on polyion complex nanoparticles for antimicrobial delivery. His research interests span peptide-based nanomaterials, self-assembly processes, and biomimetic systems, with applications in antimicrobial materials and drug delivery. His lab (insualab.com) explores supramolecular chemistry, coacervates, and functional nanostructures. His recent publications highlight advancements in peptide amphiphile design, fluorescent nanoparticles, and biomaterials with environmental responsiveness. Collaborations include studies on fungal symbionts and enzyme-responsive drug carriers. Despite no explicit awards listed, his prolific output reflects recognition in supramolecular and pharmaceutical research.
Dr. Elisabet Romero is a Group Leader at the Institute of Chemical Research of Catalonia (ICIQ) , where she leads research in bio-inspired solar energy conversion . Her work focuses on designing chromophore-protein assemblies capable of efficiently converting sunlight into electrochemical energy, mimicking natural photosynthesis. She is supported by prestigious grants, including an ERC Starting Grant and a Marie Curie Fellowship . Education: PhD in Biophysics, VU Amsterdam (2011) Master’s in Chemistry, Institute of Advanced Chemistry of Catalonia BSc in Chemistry (Physical Chemistry specialization), University of Barcelona (2003) Research Interests: Dr. Romero’s research lies at the intersection of physical chemistry, photophysics, and sustainable energy . She investigates the quantum mechanical principles underlying energy and electron transfer in photosynthetic systems, applying this knowledge to engineer artificial systems for solar fuel production. Her group uses ultrafast spectroscopy techniques like transient absorption and 2D electronic spectroscopy to probe femtosecond-scale dynamics. Publications & Research Trends: Her recent publications reflect a strong trend in de novo protein design for artificial light harvesting , excitonic coupling in chromophore systems , and quantum effects in biological energy transfer . Collaborative work with leading institutions highlights her role in advancing synthetic biology and quantum bio-inspired materials. Scientific Awards: European Research Council (ERC) Starting Grant Marie Curie Fellowship Advising and Grants: Dr. Romero mentors a dynamic team of PhD students, postdoctoral researchers, and master’s students . Her group has secured competitive funding from the ERC, Severo Ochoa Programme, and Marie Skłodowska-Curie Actions , supporting innovative research in renewable energy technologies. Labs and Teams: Her laboratory at ICIQ is equipped with state-of-the-art ultrafast spectroscopy facilities. The team fosters a collaborative and inclusive environment, combining rigorous scientific inquiry with social engagement and cultural exchange.
