Héctor Chinchero Villacis is an Assistant Professor in the Department of Electronics at the University of Alcalá. His research focuses on smart lighting systems, IoT integration in buildings, and energy management solutions. He is a member of the GEINTRA research group, which specializes in Electronic Engineering applications for intelligent spaces and transport. Chinchero holds a PhD from the University of Oviedo (2021), where his thesis addressed LED driver development for smart buildings using controllable reactive elements. Education: PhD in Electronics Engineering, Universidad de Oviedo (2021) Research Interests: His work combines power electronics innovation with IoT technologies to enhance energy efficiency in smart infrastructure. Key areas include: Magnetic control of DC-DC converters for LED applications Energy management systems for public lighting and microgrids IoT-based precision agriculture and home energy monitoring Human-centered lighting parameters for wellbeing optimization Recent Contributions: Recent publications highlight advancements in low-cost emergency lighting solutions, magnetic control techniques for power electronics, and distributed energy systems for Amazonian regions in Ecuador. His work bridges theoretical power electronics with practical smart infrastructure implementations. Labs/Teams: Active contributor to the GEINTRA research group, focusing on applied electronic engineering innovations for smart environments.
Javier Verdu Mula is a Professor at the Departament d'Arquitectura de Computadors (Universitat Politècnica de Catalunya - UPC) and a key researcher at the CRAAX - Centre de Recerca d'Arquitectures Avançades de Xarxes . His work focuses on computer architecture, parallel processing, and networking systems. Fields of Research include RISC-V virtualization, multithreaded processor optimization, and performance analysis of stateful networking applications. Scientific Awards include the BDigital Global Congress (2015) and Wayra Barcelona (2012) recognitions. Collaborations span institutions like Barcelona Supercomputing Center and researchers such as Manuel Alejandro Pajuelo, Mateo Valero Cortes, and Mario Nemirovsky. His recent publications address RISC-V hypervisor extensions, deep packet processing in parallel architectures, and statistical thread assignment models. He also holds patents in hardware virtualization and resource control systems.
Llaberia Griño, Jose M. is a faculty member in the Department of Computer Architecture at the Faculty of Computer Science of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC). He has been actively involved in research and academic activities for several decades, contributing significantly to the field of computer architecture. His research interests lie primarily in computer architecture, with a focus on high-performance computing, memory systems, cache management, interconnection networks, and parallel processing. He has made notable contributions to the design and optimization of cache hierarchies, particularly in multicore and non-volatile memory systems, and has explored innovative techniques such as reuse detection, data compression, and systolic array implementations. The trends in his recent publications indicate a sustained focus on improving the performance, efficiency, and reliability of memory systems, especially last-level caches using emerging non-volatile technologies like STT-RAM. His work often combines architectural innovation with practical modeling and forecasting techniques to evaluate system behavior. Among his scientific recognitions is participation in The 2nd Cache Replacement Championship (CRC-2) , highlighting his expertise in cache algorithms. Llaberia has advised doctoral students such as Ana Bosque Arbiol and Rubén Gran Tejero. He has been a key participant in numerous competitive R&D projects, including 'Computación de Altas Prestaciones' and 'HIPEAC 3 - European Network of Excellence', demonstrating sustained funding and collaborative research efforts. He is a member of the CAP - Grup de Computació d'Altes Prestacions (High-Performance Computing Group) at UPC, a leading research group in computer architecture and high-performance systems.
Roger Espasa Sans is a senior academic and researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Informatics of Barcelona (FIB) and the Department of Computer Architecture. He has made significant contributions to computer architecture, particularly in vector processing, GPU design, and performance optimization. Universitat Politècnica de Catalunya (UPC) Faculty of Informatics of Barcelona (FIB) Department of Computer Architecture His research focuses on advanced computer architecture, including vector and superscalar processors, memory systems, instruction-level and data-level parallelism, GPU microarchitecture, and performance modeling. His work bridges theoretical design and practical implementation, especially in high-performance and embedded systems. The recent articles highlight a strong trend in GPU and shader optimization, memory redundancy elimination, and performance modeling. His publications span prestigious venues such as IEEE Microarchitecture Symposium, IEEE HPCA, and The Visual Computer, indicating sustained impact in the field of computer systems and architecture. Premiada (Awarded activity) Roger Espasa Sans has advised several doctoral students, including Manel Fernandez Gomez and Francisca Quintana Domínguez, contributing to the next generation of computer architects. His collaborative network is extensive, involving key figures like Mateo Valero and international institutions. While specific grants are not listed, his prolific output suggests sustained funding. He has contributed to major research groups such as CAP (High Performance Computing Group). He is a core member of the CAP - Grup de Computació d'Altes Prestacions (High Performance Computing Group), and has also been associated with PM - Programming Models and ARCO - Microarchitecture and Compilers. His work often involves simulation frameworks like JINKS and Asim, indicating a strong focus on performance evaluation and modeling.
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
Ana Edelmira Pasarella Sanchez is a Professor in the Department of Computer Sciences at the Faculty of Mathematics and Statistics, Universitat Politècnica de Catalunya (UPC). She is a member of the ALBCOM research group, focusing on algorithms, bioinformatics, complexity, and formal methods. Her work bridges theoretical computer science with practical data systems. PhD in Computer Science, Universitat Politècnica de Catalunya Her research centers on logic programming, knowledge representation, and graph databases. She explores how formal methods can enhance data processing, particularly through dynamic pipelines and trust-aware access control. Her work integrates Datalog, semantic reasoning, and big data frameworks to improve scalability and correctness in knowledge systems. She has contributed to foundational semantics of logic programs and their applications in security and data integration. Her recent publications highlight a trend toward efficient, adaptive data processing systems, especially for graph analytics and knowledge graphs. She compares paradigms like MapReduce and pipelining, advocating for dynamic, functional approaches to big data. Her work increasingly addresses real-world challenges in federated knowledge graphs and access control. SACMAT 2017 Best Paper Award Pasarella has been involved in multiple competitive R&D+i projects, such as 'Modelos y Técnicas para el Procesamiento de Información a Gran Escala' and 'Modelos y métodos basados en grafos para la computación en gran escala,' indicating sustained funding and collaborative leadership. She advises on research direction within her group and mentors through collaborative publications. She has served on the scientific committee of the Latin American Informatics Conference (CLEI), contributing to the broader academic community. She is part of the ALBCOM research group and collaborates extensively with researchers like Fernando Orejas, Maria-Esther Vidal, and Elvira Pino, working on logic-based frameworks for data and security systems.
Rosa Maria Badia Sala is a Research Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament d'Arquitectura de Computadors and the Barcelona Supercomputing Center (BSC-CNS). She specializes in distributed computing, heterogeneous systems, and task-based programming models. Her work focuses on advancing high-performance computing (HPC), cloud computing, and workflow management for large-scale scientific applications. She holds a Doctorat en Informàtica and has been actively involved in numerous research projects, including contributions to the COMPSs programming framework and the optimization of HPC workflows. Her collaborations span institutions like BSC-CNS and international initiatives such as JLESC. Recent research includes GPU-accelerated computing, quantum optimization algorithms, and digital twins for power networks. Badia's publications span journals like Future Generation Computer Systems and IEEE Transactions on Parallel and Distributed Systems, reflecting her expertise in parallel computing, distributed systems, and real-time data analysis. She has supervised multiple doctoral theses and contributes to research grants focused on HPC and AI integration.
Jose Manuel Dominguez Alonso is a researcher at the University of Vigo , affiliated with the Faculty of Sciences and the Marine Research Center . His work focuses on Earth Physics and Smoothed Particle Hydrodynamics (SPH) applications in marine and renewable energy systems. He is part of the FA9 EphysLab research group at the Ourense campus. Education: PhD in Applied Physics from the University of Vigo (2014) under advisors Dr. Moncho Gómez Gesteira and Dr. Alejandro Jacobo Cabrera Crespo. His research explores fluid dynamics , off-shore wind turbines , wave energy converters , and fluid-structure interaction . He has developed DualSPHPhysics for high-performance computing in marine environments. His recent articles (2024-2025) emphasize teaching numerical modeling to students, 3D hydrodynamic analysis , and coupled simulation techniques . His work bridges computational methods with real-world marine engineering challenges like coastal protection and renewable energy optimization.
Fritz Henglein is a Professor at the Department of Computer Science, University of Copenhagen (DIKU), with affiliations also at Deon Digital. His career spans over three decades, with notable roles including Head of the Algorithms and Programming Languages (TOPPS) research group and Director of the HIPERFIT research center. Research interests include Programming languages and type systems Functional programming and DSLs High-performance computing Contracts and distributed ledger technology Algorithmic logic and formal semantics His work often bridges theoretical rigor with practical applications, particularly in financial information technology and compiler design. Collaborations include leadership in conferences like POPL, ICFP, and PEPM, with a focus on mentoring through academic events and community-building initiatives.
KC Sivaramakrishnan serves as an Adjunct Professor at the Indian Institute of Technology, Madras and CTO of Tarides, bridging academic research and industrial application in programming languages and systems. His dual roles reflect a commitment to advancing both theoretical foundations and practical implementations in computer science. His research spans Functional Programming, Language Runtimes, Concurrency/Parallelism/Distribution, and Weak Memory/Consistency models, with particular focus on the OCaml programming language. Sivaramakrishnan's work addresses fundamental challenges in concurrent and distributed systems through innovative language design and runtime techniques. Analysis of his publication record reveals a consistent trajectory from foundational work on effect handlers and concurrency models (2015-2020) to more recent contributions in verified systems, multicore programming, and distributed data types (2021-2025). His research demonstrates strong continuity in exploring how programming language principles can solve real-world systems challenges. Sivaramakrishnan actively contributes to the academic community through program committee memberships across major PL conferences including POPL, PLDI, ICFP, and SPLASH. His service spans multiple roles from committee member to track chair and diversity co-chair. As CTO of Tarides, he leads industrial efforts in OCaml compiler development and systems programming, maintaining a productive synergy between his academic research and industry leadership. His work with the OCaml community includes significant contributions to multicore support and effect handler implementations.
Carlos Molina Clemente is an Associate Professor of Computer Architecture at Rovira i Virgili University in Tarragona, Spain. He holds a M.Sc. in Computer Engineering (Universitat Politècnica de Catalunya, 1996) and a Ph.D. in Computer Science (UPC, 2005). His research focuses on Computer Architecture, Mobile/Sensor Networks, and Cloud Computing. He leads the Cloudlab research group and coordinates initiatives like GTDAWIN and BIOGEI. Key research areas include multicore scheduling, LoRaWAN protocols, LIDAR data analysis, and serverless computing. He has published over 50 articles in top-tier conferences/journals and supervised three doctoral theses. His work spans projects on cache architectures, real-time systems, and educational multicomputing solutions. Affiliations include the Department of Computer Engineering and Mathematics (DEIM) at URV, with offices at Campus Sescelades (Avinguda Països Catalans 26, Tarragona). Research highlights include contributions to non-uniform cache policies, predictive mobile network algorithms, and energy-efficient sensor networks.
Eliseo García García is a Professor at the University of Alcalá, affiliated with the Department of Automatic Control and Systems Engineering. He holds a Ph.D. from the University of Alcalá, awarded in 2005 for his thesis on computational electromagnetics. His primary research focuses on computational methods for electromagnetic analysis, including the development of efficient algorithms like the Characteristic Basis Function Method (CBFM) and hybrid techniques with the Multilevel Fast Multipole Algorithm (MLFMA). He is a core member of the GEC (Computational Electromagnetic Group), where he explores geophysical applications, antenna design, and high-frequency electromagnetic problems. His research interests bridge theoretical and applied electromagnetics, with particular emphasis on reducing computational costs in solving large-scale EM problems. Notable contributions include advancements in radar cross-section (RCS) computation, radome structure analysis, and geothermal exploration frameworks using hydrogeophysical methods. He has also published extensively on numerical techniques for antenna trajectory simulations and sparse matrix preconditioning. Eliseo’s work spans multiple disciplines, including aerospace engineering, environmental science, and software development, as evidenced by his contributions to Altair Feko 2023 updates. Despite no listed awards, his prolific publication record (over 70 articles from 2013–2024) underscores his active role in advancing computational electromagnetics and its interdisciplinary applications. His advising and grants section remains unreported, but his involvement in collaborative projects is implied through frequent co-authorships and institutional affiliations. He leads the GEC lab, focusing on cutting-edge computational tools and their practical deployment in real-world engineering challenges.
Pedro Galeano San Miguel is an Associate Professor at the Department of Statistics, Universidad Carlos III de Madrid. He is affiliated with the Nonparametric Inference for Complex Data and its Applications (NICDA) research group and contributes to the Flores de Lemus Institute and UC3M-Santander Big Data Institute. His work bridges statistics, computer science, and economics with a focus on financial and high-dimensional data. Research Interests: Functional data analysis and outlier detection Bayesian nonparametric methods and stochastic volatility models Copula models for systemic risk and portfolio selection High-dimensional statistical inference and dynamic correlation Big data applications in economics and finance Publication Trends: His recent work (2024–2016) emphasizes copula models for financial risk, functional regression techniques with missing data, and Bayesian inference for high-dimensional time series. He explores systemic banking risks, volatility prediction, and correlation structure changes across economic and financial domains. Grants & Projects: He leads or contributes to projects on computational statistics for complex dependencies, big data customer network analysis, and multivariate asymmetric GARCH modeling, funded by institutions like the State Research Agency (AEI) and Banco Santander.
Dr. Eugenio Miguel Isern Riutort serves as a Senior Lecturer in the Department of Electronic Technology within the School of Industrial Engineering and Construction at the University of the Balearic Islands (UIB). His academic profile shows active engagement across multiple degree programs including Automation and Industrial Electronic Engineering, Telematics Engineering, and the Master's Degree in Industrial Engineering, where he teaches core courses in Analogue Electronics, Electronic Instrumentation, and related subjects. Beginning his research career in January 1991 with a pre-doctoral scholarship from the Ministry of Education and Science at the Polytechnic University of Catalonia, Dr. Isern Riutort has established three primary research domains. His foundational work focuses on test and verification methodologies for integrated circuits, where he has developed techniques for fault detection through current consumption analysis (both static IDDQ and dynamic IDDT). This research has evolved to address challenges posed by technological parameter variations in modern microelectronics, leading to innovations in predictive testing, oscillation-based testing, and auto-tuning techniques. A second research stream involves designing radiation sensors using standard MOS integrated circuits, with recent work focusing on floating gate MOS transistors that produce outputs proportional to total ionizing dose. Most recently, he has been developing non-conventional computing methodologies accelerated in hardware to enable artificial intelligence applications for massive and highly complex problems. His publication record demonstrates consistent scholarly output across these domains, with particular emphasis on practical applications of theoretical concepts in microelectronics testing and sensor design. The articles reflect a progression from fundamental circuit testing techniques to specialized applications in radiation detection and, most recently, hardware acceleration for AI systems. His work bridges theoretical foundations with experimental validation, as evidenced by his focus on both fault modeling and sensor design with experimental measurements. Dr. Isern Riutort actively supervises Final Degree Projects and Master's Theses in Automation and Industrial Electronic Engineering while teaching across multiple programs. His teaching portfolio spans from foundational Analogue Electronics courses to advanced Electronic Instrumentation Systems, demonstrating comprehensive expertise across the electronics curriculum. He maintains a personal academic website (personal.uib.eu/eugeni.isern) and has established research profiles across major academic networks including ORCID, ResearcherID, Scopus, and Dialnet. As a member of the Electronic Engineering (GEE) Consolidated R+D+I Group at UIB, he participates in a collaborative research framework that supports his work in electronics and related technologies. His office is located in room F107 on the first floor of the Mateu Orfila i Rotger building (Physics building) at the university.
Alvaro Ordoñez Iglesias is an Assistant Professor at the University of Santiago de Compostela, affiliated with the Higher Technical School of Engineering and the Department of Electronics and Computing. He is a member of the ARQCOMP research group (Computer Architecture) and the CiTIUS research center. His research focuses on high-performance computing techniques for processing multi/hyperspectral remote sensing images, leveraging GPUs, multi-core CPUs, and cluster systems. He holds a PhD in 'Research in Information Technologies' (2021) from the University of Santiago de Compostela, with a thesis titled Efficient Registration of Multi and Hyperspectral Remote Sensing Images on GPU , supervised by Dra. Dora Blanco Heras and Dr. Francisco Argüello Pedreira. Prior to his current role, he was a Juan de la Cierva postdoctoral researcher at the University of A Coruña. His work emphasizes developing accurate image registration algorithms through spectral information exploitation and parallel/distributed computing. Key contributions include the HSI-MSER and HSI-KAZE algorithms, GPU-accelerated registration frameworks, and open-source tools like HypeRvieW for hyperspectral data processing. His publications span topics such as real-time registration on heterogeneous platforms, feature-based vs. area-based methods, and anomaly detection in river basins. Research collaborations involve multi-device algorithm implementations and benchmarking across diverse hardware architectures.
