Alicia Orea Giner is a Professor at the Faculty of Economics and Business Sciences of Rey Juan Carlos University, specializing in sustainable tourism and social justice. Her research focuses on Generation Z's sustainable consumption practices in food tourism, AI integration in hospitality, and ethical dimensions of tourism. She co-authored the award-winning article The way we live, the way we travel: generation Z and sustainable consumption in food tourism experiences , recognized with the 2024 Emerald Literati Outstanding Paper Award. Her work bridges sustainability, technology, and cultural studies. Key themes include feminist methodologies in tourism research, transformative travel through ecofeminism, and post-pandemic food tourism trends. She explores AI applications in service robots, wellness tourism's mental health connections, and marginalized communities' roles in culinary tourism. Recent studies address LGBTQ+ tourism challenges, stakeholder participation in World Heritage sites, and ghost tours' cultural narratives. Awards highlight her contributions to sustainability and social justice in tourism. Awards: 2024 Emerald Literati Outstanding Paper Award Research Foci: Food Tourism, AI Ethics, Feminist Tourism Studies, Cultural Heritage Management Labs/Teams: No specific lab mentioned; collaborates across interdisciplinary tourism research networks.
Amir Sufi is the Bruce Lindsay Distinguished Service Professor of Economics and Public Policy at the University of Chicago Booth School of Business, where he has been a faculty member since 2005. He serves as a Research Associate at the National Bureau of Economic Research and co-director of its Corporate Finance Program. Bachelor’s Degree, Walsh School of Foreign Service, Georgetown University (1999) PhD in Economics, Massachusetts Institute of Technology (2005) His research focuses on finance , macroeconomics , and corporate finance . Key areas include household debt dynamics , credit market structure , income inequality , and interest rate impacts on productivity growth . Recent work examines customer capital investment and low-interest rate effects on market concentration . Selected scientific awards include the 2017 Fischer Black Prize, Econometric Society Fellow (2022), and American Academy of Arts and Sciences Fellow (2024). His peer-reviewed publications and working papers span topics from syndicated loans to global household debt cycles , with notable contributions to understanding credit-driven business cycles and government-led consumer credit programs . He teaches courses in leveraged finance , private credit , and corporate restructuring .
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.
Leland Bybee is an Assistant Professor of Finance at the University of Chicago Booth School of Business . He leverages machine learning and natural language processing to address economic and financial questions, particularly focusing on belief measurement with applications to asset pricing and behavioral economics. Ph.D. in Financial Economics, Yale School of Management (2024) M.S. in Statistics, University of Michigan (2017) B.A. in Economics, University of Chicago (2013) His research integrates computational methods with economic theory to analyze: Textual analysis of business news for macroeconomic tracking Narrative-driven asset pricing models Memory-based belief formation using kernel methods Macroeconomic determinants of currency returns He has received multiple awards including: Dimension Fund Advisors Distinguished Paper Award BlackRock Applied Research Award HEC Top Finance Graduate Award The Brattle Group PhD Candidates Award EFA Engelbert Dockner Memorial Prize Bybee teaches Machine Learning in Finance and participates in finance seminars, contributing computational tools like regIPCA (Python) and changepointsHD (R) to the research community.
Karina Gibert is a Full Professor at Universitat Politècnica de Catalunya (UPC), specifically at the Faculty of Computer Science of Barcelona (FIB) in the Department of Statistics and Operations Research. With a permanent teaching position since 1990, she contributes to research and education with a focus on Data Science, Artificial Intelligence, Explainable AI, and Ethics in AI. Full Professor, UPC (since 1990) PhD in Informatics Engineering Postgraduate in Higher Education Teaching Director and co-founder of IDEAI research center Dean of the Official Professional College on Informatics Engineering of Catalonia Active in bridging the gender gap in STEAM through multiple initiatives Her research focuses on extracting strategic knowledge from data and intelligent systems with ethical and explainable perspectives. She has led various projects including Diet4You for personalized diets, INSESS-COVID19 for social vulnerability analysis, Top Rosies Talent for female AI development, and ciutadanIA for AI culture promotion. Her work spans health, environment, sustainability, tourism, and social technology applications. As an editor of Environmental Modeling and Software journal and active academic, she contributes to international conferences, working groups, and research collaborations. Her service includes membership on various ethics and AI strategy committees and advisory boards. Women Tech Award 2023 National Informatics Engineering Award in Digital Dissemination 2022 Ada Byron Award 2022 Honorific Mention of Creu Casas award 2021 donaTIC 2018 Award Finalist at AMETIC Awards 2021 Finalist of European Social Services Awards 2021
Pere-Pau Vázquez is an Assistant Professor in AI for Visual Computing at the Computer Vision Lab, TU Wien, Austria . Previously, he held academic positions at the ViRVIG Group and Facultat d'Informàtica de Barcelona (UPC) , where he taught courses in Programming, Computer Graphics, and Visualization for over 20 years. His research focuses on Information Visualization, Scientific Visualization, Medical Data Visualization, Molecular Visualization, and AI applications to Visual Computing . Current Teaching : Data Visualization, Fast Realistic Rendering, Information Visualization, Medical Images, Scientific Visualization, Virtual Reality, and 3D Medical Visualization. Former PhD Students : Elena Molina, Alexandra Cortez, Jesús Díaz, Pedro Hermosilla, Eva Monclús. His scientific awards include the Best PhD Thesis Award (UPC, 2003), Best Student Paper Award (SPIE, 2012), and Best Paper Award (International Conference on Computer Graphics Theory and Applications, 2013). Recent publications explore AI integration in biomedical visualization, molecular data analysis, and interactive techniques for volume rendering. He serves on the EuroGraphics Executive Board as Secretary and is active in steering committees for EuroVis and Visual Computing for Biology and Medicine . His work bridges Computer Graphics, Artificial Intelligence, and Human-Computer Interaction , with applications in medical and molecular data analysis.
Andrea Ianiro is a Full Professor in the Aerospace Engineering Department at Universidad Carlos III de Madrid (UC3M), where he leads research in fluid dynamics, turbulence, and heat transfer. His work bridges experimental techniques and machine learning applications for flow analysis and control. He serves as Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) and directs the EFM Lab (Experimental Fluid Mechanics Laboratory) at UC3M. Professor Ianiro's research focuses on turbulence characterization, boundary layer flows, and the application of machine learning to fluid mechanics problems. His work spans experimental techniques including Particle Image Velocimetry (PIV), infrared thermography, and advanced data processing methods. Recent research emphasizes data-driven approaches for flow field reconstruction, turbulence control, and heat transfer optimization in wall-bounded flows. His projects often combine theoretical, experimental, and computational approaches to address complex fluid mechanics challenges. The analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional fluid mechanics. His work increasingly focuses on using deep learning techniques (particularly CNNs and GANs) for flow field prediction from limited measurements, developing meshless computational methods for flow analysis, and applying optimization techniques (including genetic algorithms) to heat transfer enhancement. His research maintains a strong experimental foundation while embracing data-driven approaches to tackle turbulence modeling challenges. Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) Professor Ianiro leads multiple significant research projects including SPANDRELS (SParse AND paRsimonious Event-based fLow Sensing, 2025-2030), HumanIC (Human-Centric Indoor Climate for Healthcare Facilities, 2024-2027), and EXCALIBUR (Extraction of machine learning strategies for turbulent flow control, 2023-2026). His work has attracted funding from the European Commission, Spanish National Research Agency, and industry partners including Airbus. He has supervised numerous theses on topics including AI-based sensing of turbulent flows, convective heat transfer control, and turbulent boundary layers. At UC3M, Professor Ianiro directs the Experimental Fluid Mechanics Laboratory (EFM Lab), which focuses on advanced measurement techniques for fluid flow and heat transfer characterization. The lab specializes in PIV/PTV techniques, infrared thermography, and the development of novel experimental approaches for turbulence research. Current research directions include machine learning applications for flow field reconstruction, plasma-based flow control, and heat transfer optimization in complex flow configurations.
Marco Raiola is an Associate Professor at the Department of Aerospace Engineering , Universidad Carlos III de Madrid (UC3M). His research focuses on fluid dynamics, turbulence, and aerodynamics, with applications in flow diagnostics, heat transfer, and control systems. Research Interests: Turbulent flows, data-driven modeling, particle image velocimetry (PIV), convective heat transfer, and bio-inspired aerodynamics. Projects: Principal researcher in INFLUENTIA-CM-UC3M (2024-2026) and Diagnóstico del ruido de chorro (2022-2025). Collaborator in EU-funded initiatives like HumanIC and ODE4HERA . Contact: Email mraiola@ing.uc3m.es | ORCID: 0000-0003-2744-6347
Silverio Juan Martinez Fernandez is a Professor at the Universitat Politècnica de Catalunya (UPC) , affiliated with the Barcelona School of Informatics (FIB) and the Department of Service and Information Systems Engineering . He is a core member of the inSSIDE and GESSI research groups. His expertise spans Empirical Software Engineering , Green AI , MLOps , and Software Analytics . Education: Bachelor's in Computer Engineering PhD from UPC in Software Engineering Master's in Computing Research Interests: Focuses on sustainable AI practices, energy-efficient ML systems, and MLOps education. He investigates architectural design for green AI, energy labeling tools for ML models, and agile software development methodologies. His work bridges theoretical research and industrial applications, emphasizing data-driven decision-making. Grants & Collaborations: Leads projects like Green AI-Based Systems Architecture and Q-Rapids , funded by national and EU programs. Collaborates with institutions like Softeam and industry partners to apply software analytics in real-world scenarios. Labs & Teams: Coordinates the inSSIDE group, focusing on integrated software and data engineering. Active in organizing conferences like GREENS and ESEM , and co-develops tools like Skuld for technical debt management.
Carlos Lopezosa is a Visiting Professor at the University of Barcelona (UB) under a Margarita Salas postdoctoral fellowship. Previously, he held an Associate Professor position at the Pompeu Fabra University (UPF), where he taught across the Faculty of Communication, including Journalism, Advertising, and Audiovisual Communication. He also coordinated the Online Master's in SEO/SEM at the Barcelona School of Management (UPF). His research focuses on web visibility strategies (SEO, voice search, social media curation), qualitative methodologies (systematic reviews, semi-structured interviews), and AI applications in digital journalism. He is affiliated with the UB's Faculty of Information and Audiovisual Media, contributing to research groups like Professorat GIDD. His work bridges academic research with practical media strategies, emphasizing ethical AI integration and algorithmic transparency. Key research areas include news curation, AI-driven data analysis, and digital media ethics. Lopezosa has published extensively in journals like Future Internet , DOXA Comunicación , and El Profesional de la Información , with over 50 peer-reviewed articles since 2018. His current projects explore AI's role in newsrooms, Google News algorithms, and multidimensional journal evaluation frameworks. Education: Doctor in Information Sciences Research Interests: SEO strategies, content curation, AI in media, systematic reviews Grants: Margarita Salas Postdoctoral Fellowship (UB) His work often addresses challenges in digital media visibility, ethical AI implementation, and the evolving role of algorithms in news dissemination. Lopezosa collaborates with institutions like the CRICC research center and frequently presents at international conferences on digital media trends.
Cristobal Pagan Canovas is a Permanent Professor (tenure-track) at the Department of English Philology, University of Murcia, where he co-directs the Daedalus Lab and the Murcia Center for Cognition, Communication, and Creativity. He is also a member of the international consortium Red Hen Lab, focusing on multimodal communication research. Education includes: PhD in Ancient and Modern Greek Literature from University of Murcia BA+MA in Classics and BA+MA in English from University of Murcia MA in Classics from University College London His research explores human cognition and communication through interdisciplinary approaches combining humanities and sciences. Primary interests include: Conceptual integration networks in emotional expression Multimodal communication patterns across language, gesture, and prosody Temporal representation in creative artifacts Cognitive foundations of poetic metaphor and verbal art Cultural evolution of integrative patterns in social interactions Recent publications demonstrate consistent focus on temporal cognition, multimodal communication, and creativity across domains including poetry, music, and gesture. Research employs corpus analysis, big data approaches, and cognitive modeling to examine how humans integrate perceptions into meaningful wholes. Scientific awards and fellowships: Ramón y Cajal Grant (elite national scheme) Alexander von Humboldt Fellowship in Quantitative Linguistics EURIAS Fellowship at Netherlands Institute for Advanced Studies FBBVA Leonardo Fellowship Marie Curie Fellowship ENSAYA'10 Award for scientific essay He leads multiple research grants including ERASMUS PLUS KA220-HED (MULTIDATA) and national grants MULTIFLOW and CREATIME. Supervised trainees include postdoctoral researchers (Marie Curie, Juan de la Cierva), MA students, undergraduates, and data scientists. The Daedalus Lab develops interdisciplinary methods to study cognition and communication, while Red Hen Lab enables large-scale multimodal dataset analysis through international collaboration.
Horacio Saggion is the Chair in Computer Science and Artificial Intelligence at the Department of Information and Communication Technologies, Universitat Pompeu Fabra. He leads the TALN Group and the Large Scale Text Understanding Systems Lab. His research focuses on Computational Linguistics, with specialties in Text Summarization, Information Extraction, and Semantic Analysis. He coordinates the Horizon Europe iDEM project on inclusive democratic spaces and previously led the SignON project for Sign Language Translation. Key technologies include the SUMMA Summarization system and the Dr Inventor Text Mining Library. Education: PhD, MSc, and Licenciatura in Computer Science. Research Interests: Text simplification for accessibility, sign language translation, misinformation detection, and ethical AI applications. His work bridges natural language processing with societal needs such as clear communication in public administration. Grants & Projects: Coordinator of iDEM (Horizon Europe), PI of SignON, Simplext, and Able to Include. Involved in BEA shared tasks and CLEF labs. Active in organizing workshops like TSAR at EMNLP. Labs & Teams: Head of TALN Group and Text Understanding Lab. Collaborations include Universitat Pompeu Fabra's interdisciplinary initiatives and industry partnerships for technology commercialization.
Elena Fatima Perez Carrillo is a Professor in the Department of Private and Corporate Law at the Faculty of Law, University of León. Her research focuses on commercial law, corporate governance, cybersecurity, and the intersection of technology with legal frameworks. Academic Rank: Professor Department: Private and Corporate Law School: Faculty of Law University: University of León Email: eperc@unileon.es Research Group: DERMER-E (Commercial Law) Her work explores corporate governance challenges in the digital era, including cybersecurity, AI integration in business, and financial regulation. She has contributed extensively to EU policy analysis, risk management frameworks, and sustainability in corporate law. Recent publications highlight trends in cybersecurity governance, AI applications in education, and financial regulation reforms. She has authored studies on digital resilience, corporate liability, and legal aspects of emerging technologies. Key Research Areas: Commercial Law, Corporate Governance, Cybersecurity Law, Financial Regulation, AI Governance Notable Contributions: Analysis of EU cybersecurity directives, AI in legal education, D&O insurance frameworks
Maria Cristina Marinescu is a Professor in the Department of Mathematics and Data Analytics at IQS School of Engineering , with a focus on Applied Data Analytics and Modeling . She has an active research profile in interdisciplinary domains connecting computational methods with public health, social sciences, and medical applications.
Luis Antonio Azpicueta Ruiz is an Associate Professor in the Department of Signal Theory and Communications at Carlos III University of Madrid. He leads research in the Signal Processing and Learning Group (GTSA) and Machine Learning for Data Science (ML4DS) group, focusing on interdisciplinary applications spanning acoustics, telecommunications, and machine learning. Research Interests: His work bridges signal processing theory with practical applications in environmental acoustics, adaptive filtering systems, and machine learning. Key research themes include: Advanced adaptive filtering architectures for nonlinear systems Distributed estimation in sensor networks Acoustic echo cancellation and room equalization Psychoacoustic evaluation methods Machine learning applications in noise monitoring and sound analysis Research Projects: Principal investigator for multiple funded projects including: Diagnóstico del ruido de chorro en aeronaves (AEI, 2022-2025) LearnINg FLow and Noise Dynamics via AI (COMUNIDAD DE MADRID, 2024-2026) BODYinTRANSIT - Sensory-driven Body Transformation (EUROPEAN COMMISSION, 2022-2026) Aprendizaje Automático para análisis Big Data (MINISTERIO DE ECONOMÍA, 2018-2021)
