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Luo Mai is an Assistant Professor at the University of Edinburgh's School of Informatics , with an upcoming promotion to Associate Professor (UK Reader) in August 2025. He leads the Large-Scale Machine Learning Systems Group and co-leads the UK EPSRC Centre for Doctoral Training in Machine Learning Systems and an ARIA Project on Scaling AI Compute by 1000X . PhD in Computer Science (Imperial College London, 2018) MRes in Advanced Computing (Imperial College London, 2012) His research focuses on the intersection of computer systems , machine learning , and data management . Key contributions include award-winning systems like WaferLLM (wafer-scale LLM inference), Tenplex (elastic ML), and ServerlessLLM (serverless LLM serving), published at top venues (OSDI, SOSP, ICML, NeurIPS, JMLR). Recent publications demonstrate trends in GPU-based distributed systems , LLM optimization , and adaptive machine learning . His team has developed groundbreaking open-source projects including TensorLayer , TorchOpt , and ServerlessLLM . Awarded Microsoft Research StarTrack Scholar (2024) , secured ARIA grant (2024) with Imperial College & Cambridge University, and received Google Fellowship during PhD (2012-2016). As an educator, he designed Edinburgh's popular Machine Learning Systems course (150+ students). His group supervises multiple PhD students including Yao Fu (recognized as 2024 Rising Star in ML & Systems) and Leyang Xue .

• Computer Systems
• Machine Learning Systems
• Data Management
• +3 more

Miriam Lorente Rodriguez is a Professor in the Department of Comparative Education at the Faculty of Philosophy and Educational Sciences, University of Valencia, Spain. She is an active researcher in the GRECIA Comparative Education Research Group, focusing on global citizenship, educational rights, and policy in Latin America and Central America. Research Interests: Her work spans Comparative Education , Global Citizenship Education , Education as a Human Right , Teacher Induction , and SDG4 (Quality Education) . She critically examines educational policies, digital transformation in higher education, and teacher professional development, particularly in Latin American contexts. Her recent publications (2021–2025) reflect a strong trend toward analyzing UNESCO’s global citizenship agenda, the impact of digital tools during the pandemic, teacher coordination roles, and educational equity in Latin America. These works demonstrate a consistent focus on policy critique, comparative methodologies, and sustainable development in education. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While no formal list of advisees or grants is provided, she completed her PhD on children's rights and education in Central America under the supervision of Dr. Luis Miguel Lázaro Lorente. Her research suggests active involvement in academic mentoring and collaborative projects, particularly within the GRECIA group. Labs and Teams: She is a key member of the GRECIA Comparative Education Research Group , contributing to collective research on international and comparative educational policies, with a focus on Latin America and global frameworks.

• Comparative Education
• Global Citizenship Education
• Education Policy
• +7 more

Montserrat Cachero Vinuesa is a Full Professor in the Department of Economics, Quantitative Methods and Economic History at Pablo de Olavide University in Spain. She specializes in Economic History and Institutions, with a particular focus on applying network analysis to historical research. Her work bridges the fields of economic history, early modern studies, and digital humanities. Her research interests center on the application of network theory to historical contexts, particularly examining merchant networks in the Atlantic world during the early modern period. She investigates how social and economic networks facilitated trade, colonization, and cultural exchange between Europe and the Americas. Her work spans multiple dimensions including gender dynamics in commerce, book trade networks, risk management in pre-industrial trade, and the institutional frameworks that enabled transatlantic economic integration. Her scholarly output demonstrates a consistent trajectory of applying network analysis to historical questions, with increasing methodological sophistication over time. Recent work has focused on gender dimensions of commercial networks, particularly women's roles in the book trade, alongside continued exploration of Basque merchant networks, Atlantic trade routes, and colonial economic structures. Her research combines traditional archival methods with innovative network visualization and analysis techniques. Dr. Cachero Vinuesa is the creator of RedLab, an academic space dedicated to the application of network analysis to historical research. This initiative reflects her commitment to methodological innovation and interdisciplinary collaboration. She is actively involved in doctoral education through the History and Humanistic Studies program at her institution, with emphasis on European, American, and geographical approaches to historical research.

• Economic History
• Early Modern History
• Network Analysis
• +5 more

Lluís Codina Bonilla is an Associate Professor at Pompeu Fabra University's Faculty of Communication, specializing in Journalism and Audiovisual Communication. As a founding member of the DigiDoc Research Group (SGR-01103) and Director of the Cybermedia Observatory, he bridges Information Science and Digital Communication through research on SEO, content curation, and digital media systems. PhD in Information Science (Universitat Autónoma de Barcelona) Co-founder of academic journal Hipertext.net Principal Investigator for multiple Spanish national R&D projects Research Interests: His work focuses on Search Engine Optimization (SEO) for news media, Semantic Web applications in journalism, and content curation systems. Recent studies explore AI applications in content creation and academic research. Academic Contributions: With over 200 articles and 6 books (including Design and SEO for Content-Intensive Websites ), his publications analyze digital media quality assessment, information architecture, and media verification. His 21 doctoral theses (all cum laude) highlight his role as a mentor in digital communication. Premio Roblón 2021 for Investigator of the Year Multiple UPF Social Council Awards for Teaching Quality Nominated Scimago Best Scientific Article Recognized Researcher Tranches (CNEAI/AQU) Academic Infrastructure: Leads the Cybermedia Observatory and contributes to UPF's SEO Media Lab, while maintaining affiliations with the Catalan Society of Communication and Institute of Catalan Studies. His teaching spans Journalism, Audiovisual Communication, and Research Master's programs.

• Web Positioning
• Semantic Web
• Information Systems
• +7 more

Pablo Calleja is a Research Fellow at the Faculty of Computer Science, Polytechnic University of Madrid (UPM), where he has been a member of the Ontology Engineering Group (OEG) since March 2014. His research focuses on Natural Language Processing (NLP), medical terminology mapping, and legal domain applications. He holds a degree in Computer Engineering from San Pablo CEU University (2013) and has prior industry experience as a software developer at IECISA (2008–2011) and a collaboration grant at the Open Access Classroom, San Pablo CEU University (2011–2013). Key contributions include projects like Drugs4covid for pandemic drug discovery, TermitUp for terminological enrichment, and esT5s , a Spanish text summarization model. His work spans legal knowledge graphs, multilingual compliance systems, and NER techniques for academic content analysis. He has also explored accessibility multimedia services and semantic graph applications in tourism ( DBtravel ). Professional roles include collaboration grants at UPM and active participation in interdisciplinary projects such as SNOMED-CT annotation for medical technical sheets. Research trends emphasize cross-domain adaptation (e.g., K-Flares), data augmentation (Widaug), and multilingual NLP solutions. Advising and grants: His current position is supported by a collaboration grant at OEG. Earlier grants include work at San Pablo CEU University. No formal advisees are listed, but he contributes to collaborative research teams. Labs and teams: Core member of the Ontology Engineering Group (OEG), focusing on knowledge representation, NLP, and applied informatics in healthcare and law domains.

• Natural Language Processing
• Medical Informatics
• Legal Informatics
• +5 more

Juan Carlos Torres Zafra is a Visiting Professor at Universidad Carlos III de Madrid. His research focuses on optoelectronics, liquid crystal technologies, visible light communication (VLC), and sensor systems. His work spans interdisciplinary areas including energy-harvesting IoT nodes, indoor positioning systems, and optical communication interfaces for high-definition media transmission. Torres Zafra has contributed to advancements in semiconductor materials (e.g., perovskites), low-cost sensor networks, and hybrid RF-VLC positioning systems. His research also extends to educational technology, exploring tools like Telegram and Google Workspace for improving student engagement in cybersecurity engineering programs. Notable projects include the GUTI group's work on optical vortices using liquid crystal devices and the development of tunable resonators based on liquid crystal capacitance. His publications from 2020–2025 highlight trends in VLC system optimization, AI-driven disinformation detection (SmartVote-AI initiative), and medical studies on amyloidosis therapy outcomes. Torres Zafra’s work often emphasizes practical applications in robotics, automotive systems, and sustainable energy solutions. While no formal awards are listed, his extensive publication record (over 80 entries from 2004–2025) reflects sustained contributions to photonics, sensor engineering, and liquid crystal device innovation. His research integrates hardware design, algorithm development, and material science to address challenges in modern communication systems and assistive technologies for visually impaired patients.

• Optoelectronics
• Liquid Crystal Technologies
• Visible Light Communication (VLC)
• +4 more

Carlos Iván Del Valle Morales is an Adjunct Professor at Carlos III University of Madrid. His research focuses on visible light communication (VLC), Li-Fi systems, and energy-harvesting technologies. He leads projects in the Grupo Universitario de Tecnologías de Identificación (GUTI), developing optical communication interfaces for IoT, high-power LED characterization, and indoor positioning systems using trilateration and angular diversity. Recent work emphasizes perovskite photovoltaic applications for self-powered IoT nodes and hybrid RF-VLC positioning systems. His publications span 2020–2024, addressing energy efficiency, bandwidth optimization, and hardware design for VLC systems in automotive and multimedia contexts.

• Optoelectronics
• Visible Light Communication (VLC)
• Internet of Things (IoT)
• +3 more

Pere Millán Marco is an Associate Professor in the Department of Computer Engineering and Mathematics (DEIM) at Universitat Rovira i Virgili (URV), Tarragona, Spain. He serves as coordinator for Non-permanent lecturers. His research focuses on computer communications, mobile/sensor networks, and IoT, with emphasis on quality prediction and performance optimization in wireless environments. Education: M.Sc. in Computer Engineering (Polytechnic University of Catalonia, 1992); PhD in Computer Engineering (URV, 2018). Research Interests : Specializes in mobile and sensor network architectures, underwater acoustic networks, real-time communication protocols, and low-cost hardware solutions for educational and environmental applications. His work integrates time series analysis, predictive modeling, and social behavior patterns to enhance network efficiency. Publications Trends : Recent work emphasizes IoT applications in environmental monitoring (e.g., deep aquifer pumping systems), optimization of underwater acoustic networks, and low-cost multicomputer systems for teaching. Consistently explores predictive techniques for network topology and quality-of-service improvements in ad hoc and community networks. Awards & Recognition : Holds a granted US patent related to location-based information systems. Advising & Infrastructure : Involved in DEIM's teaching laboratory development. Active in organizing international conferences like UCAmI and VISIGRAPP. Member of the CloudLab research group, advancing cloud and distributed computing solutions.

• Computer Communications
• Mobile and Sensor Networks
• Internet of Things
• +3 more

Lluís Vicent Safont is a Senior Lecturer and Director of the Postgraduate Program in Data Management at the UPF Barcelona School of Management. He has held prominent roles such as Rector of Universitat Oberta La Salle (2008–2012) and academic leadership positions at institutions like Universitat Ramon Llull and Universidad La Salle. His research focuses on data science, education technology, and innovative teaching methodologies, with over 70 publications and 50 projects as Principal Investigator. He specializes in curriculum design, educational assessment, and the integration of technology in higher education, including hybrid learning systems and adaptive learning tools. Education background includes a Doctorate in Engineering and Architecture, alongside master’s and technical engineering qualifications. His work emphasizes bridging education and technology, addressing challenges like early school leaving and digital education readiness. He has contributed to international conferences (IEEE, Erasmus+) and authored books on topics like fuzzy logic in assessment and multimedia in education. As a leader, he has directed postgraduate programs, research groups, and institutional initiatives, focusing on innovation, internationalization, and educational policy. His projects often involve collaboration across universities and institutions to enhance educational quality and accessibility. Recent work includes the H2O Learn project on hybrid education analytics and initiatives reinforcing engineering leadership in societal contexts.

• Education Technology
• Data Science
• Educational Assessment
• +3 more

Ruben Tolosana is a researcher at the Biometrics and Data Pattern Analytics Lab (BiDA Lab) in the School of Engineering at Universidad Autónoma de Madrid. His work centers on biometrics, with emphasis on behavioral and mobile authentication, face recognition, privacy-enhancing technologies, and deep learning applications in human-computer interaction. He actively contributes to major research initiatives such as the FRCSyn-onGoing challenge and the ChildCI framework. PhD in Computer Science or related field (inferred from publication volume and role) Advanced training in machine learning, computer vision, and biometrics His research interests include behavioral biometrics, mobile device security, synthetic data for AI training, privacy in biometric systems, and the application of Transformer models to user authentication. Tolosana's work often involves the development of novel datasets and benchmarking platforms to advance the field. He has co-authored influential surveys on privacy vulnerabilities in mobile sensors and privacy-preserving techniques in biometric recognition. The most recent articles highlight trends in using synthetic data for face recognition, applying Transformers to behavioral biometrics (keystroke, touchscreen, gait), and developing frameworks for child age detection via interaction patterns. His work consistently addresses real-world challenges such as privacy, bias, and system generalization. Publications in journals like Information Fusion , Pattern Recognition , and ACM Computing Surveys reflect the high impact and interdisciplinary nature of his research. Second FRCSyn-onGoing: Winning solutions and post-challenge analysis to improve face recognition with synthetic data (2025) ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection (2024) FRCSyn-onGoing: Benchmarking and comprehensive evaluation of real and synthetic data to improve face recognition systems (2024) SwipeFormer: Transformers for mobile touchscreen biometrics (2024) An Overview of Privacy-Enhancing Technologies in Biometric Recognition (2024) Ruben Tolosana collaborates extensively with researchers in the BiDA Lab, including Rubén Vera-Rodríguez, Aythami Morales, Julian Fierrez, and others. He has contributed to the development of public databases such as mEBAL and ChildCIdb, supporting open science. His work is supported by ongoing research grants (inferred from project scope and publications), and he plays a key role in organizing workshops such as WAMWB to advance the mobile and wearable biometrics community. He is a core member of the Biometrics and Data Pattern Analytics Lab (BiDA Lab), a leading research group in biometric technologies, where he contributes to multiple projects involving mobile authentication, face recognition, and privacy-preserving AI systems.

• Biometrics
• Behavioral Biometrics
• Mobile Authentication
• +12 more

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

• Computational Social Science
• Educational Technology
• Cyberdefence
• +3 more

José Ignacio Olmeda Martos is a Professor at the Computer Science Department of the University of Alcalá, Spain. His research focuses on artificial intelligence, neural networks, financial modeling, and applications in tourism and e-learning. He leads the CSRG-UAH Cognitive Science Research Group and the AUDITAI Group for AI Software Development. He earned his Ph.D. in 1996 with a thesis on nonlinear financial models under Dr. Sergio Barba-Romero. His work bridges computational methods with real-world challenges in finance, tourism, and education. Research interests include predictive analytics, algorithmic optimization (genetic algorithms, SOMs), and accessibility in digital systems. His contributions span hybrid models in credit scoring, volatility forecasting using neural networks, and e-commerce adoption analysis. Over 25 years, he has published extensively on topics like tourism demand prediction (PLAZA project), web accessibility metrics, and financial market predictability. Key projects include developing internet-based tourism reservation systems for Castilla-La Mancha and applying wavelet filtering in financial time series. His research emphasizes interdisciplinary applications, integrating AI with tourism management and financial engineering. Education: Ph.D., Universidad de Alcalá, 1996 Publications reflect his expertise in computational finance, tourism technology, and machine learning. Despite no listed awards, his work demonstrates sustained impact in both academic and applied domains. Advising and grant activities are not detailed in the provided texts.

• Artificial Intelligence
• Computer Science
• Financial Modeling
• +4 more

Dr. Juan Manuel Sáez Martínez is a full professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante's Higher Polytechnic School II. With a PhD in Computer Engineering and over two decades of academic experience since 2000, he specializes in Computer Vision and Mobile Device Applications for accessibility, particularly for the blind and visually impaired. His groundbreaking NaviLens project—a digital signage system patented internationally by the University of Alicante and licensed to Neosistec SL—represents a significant contribution to assistive technology. Teaching experience across 15+ years in programming fundamentals, computer systems, and internships for telecommunications and multimedia engineering Supervised one PhD thesis on structural similarity in object recognition Active in public research projects including airport navigation systems and airborne obstacle detection for the visually impaired His research interests focus on computer vision algorithms , stereo-based wearable devices , and ultra-efficient artificial vision systems for mobile platforms . Recent work includes biomedical informatics applications like 3D obstacle detection and accessibility-oriented UI design. He has participated in 10+ competitive public research projects (2016-2021) while contributing to technology transfer initiatives. Teaching contributions include 4 quinquennials (five-year terms) and 14+ years of instruction in Programming Fundamentals I for Telecommunication Sound and Image Engineering. Notable collaborations include co-authorship with Dr. F. Escolano on entropy-based SLAM algorithms and Gaussian mixture models for image processing. Current research emphasizes practical applications through the Mobile Vision Research Laboratory (MVRLab) .

• Computer Vision
• Mobile Devices
• Assistive Technology
• +3 more

Roberto Rodriguez-Echeverria is an Associate Professor at the Computer Languages and Systems Department of the Universidad de Extremadura (Spain). He leads the Applied Informatic Technology Institute and co-founded MetrikaMedia, a SaaS company for multimedia content measurement. His research focuses on software engineering, model-driven engineering, machine learning, and legacy system modernization. Education: Bachelor and Master in Computer Science (2000), Universidad de Extremadura Master on Education and IT (2012), Universitat Oberta de Catalunya PhD in Computer Science (2014), Universidad de Extremadura Research interests include data-driven software development, medical image segmentation using SAM models, and educational technology applications like chatbot performance analysis in exams. He explores reproducible data science workflows and hybrid recommendation systems for media. Recent work highlights include advancing loss function analysis for COVID-19 lung scans and developing cost-efficient medical image segmentation techniques leveraging SAM's zero-shot capabilities. He also studies the impact of AI tools like ChatGPT on academic assessment methods. His contributions span over 50 publications since 2004, with recent focus on smart city applications, cloud cost estimation, and cooperative social process modeling. Rodriguez-Echeverria's work bridges theoretical computer science with practical industry solutions through his lab's applied research initiatives. Labs/Teams: Applied Informatic Technology Institute (Director) i3 Lab (Affiliated)

• Software Engineering
• Model-Driven Engineering
• Machine Learning
• +5 more

Mari Carmen Suárez-Figueroa is an Associate Professor at the Artificial Intelligence Department, School of Computer Science, Universidad Politécnica de Madrid (UPM). She is also a senior researcher at the Ontology Engineering Group (OEG). Her research focuses on Ontology Engineering, Semantic Web, and Linked Data, with emphasis on ontology networks, evaluation, and design patterns. She holds a PhD in Artificial Intelligence from UPM (2010) and has been recognized with an Outstanding Award from UPM's Graduate Doctorate Commission. Her work includes contributions to methodologies like the NeOn Framework, tools such as OOPS! for ontology validation, and participation in projects like NeOn, SEEMP, and Ready4SmartCities. She has organized conferences and workshops, including TKE 2012 and WOP 2012. Over 88+ publications span journals like International Journal of Information Technology & Decision Making and Data & Knowledge Engineering . Key achievements include co-editing Ontology Engineering in a Networked World (Springer, 2012) and leading interdisciplinary initiatives on inclusive consumer testing and semantic metadata standards. Ongoing projects address social inclusion via machine learning and educational service-learning programs.

• Ontology Engineering
• Semantic Web
• Linked Data
• +3 more