Concha Bielza is a Full Professor with the Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid since 2010. She received the M.S. degree in Mathematics (statistics) from Universidad Complutense de Madrid, Spain, in 1989 and the Ph.D. degree in Computer Science from Universidad Politécnica de Madrid, in 1996 (extraordinary doctorate award).

She co-leads the Computational Intelligence Group (CIG) at UPM since its foundation in 2010 and co directed the ELLIS Unit Madrid (2022–2024). She has participated in 65 public research projects—including the EU’s 10-year Human Brain Project—and 41 industry contracts (Telefónica I+D, Abbott, Bank of Santander, Panda Security, Repsol, ArcelorMittal). She is co-inventor of a patent on lung adenocarcinoma. She has delivered 44 invited talks/seminars and 11 plenary talks in conferences, served on 91 program committees, and organized 19 scientific events—including Program Chair of CAEPIA-2013 and Journal Track Chair of ECML-PKDD 2015 and 2025. She has published 160+ journal papers, supervised 24 PhD and 76 Master theses. Her h-index is 36 (Web of Science) and 46 (Google Scholar) with 6,192 and 11,260 citations, respectively. During the last years she coauthors two books: “Data-Driven Computational Neuroscience” (2021, Cambridge University Press) and “Industrial Applications of Machine Learning” (2019, CRC Press), translated to Chinese in 2023. She is associate editor of Neuroinformatics and Frontiers in Computational Neuroscience. She co-leads the UPM- Machine Learning and Advanced Statistics Summerschool (18th edition in 2026) with more than 80 international students every year.

Her research interests are primarily in the areas of probabilistic graphical models, decision analysis, causality, interpretability, metaheuristics for optimization, machine learning, Bayesian networks, multi-label classification, clustering, spatial and directional statistics, and real applications, like biomedicine, bioinformatics, neuroscience, industry, agriculture, service quality and industry 4.0. She has been awarded the National Award of Statistics (2024), Fellow of the Asia-Pacific Artificial Intelligence Association (2024), ELLIS Fellow (2023), and UPM Research Award (2014). In 2021 she joined the Scientific Advisory Board of the Norwegian Research Center for AI Innovation (NorwAI) —as its only Spanish member—, chaired the NNF Grand AI Challenge 2025 (Novo Nordisk Foundation, Denmark), and in 2025 was appointed external expert for the selection of a new Max Planck School in Artificial Intelligence.

Dr. Laura Trinchera is a Professor of Statistics and Data Science at NEOMA Business School in France where she leads the research center (Area of Excellence) in AI, Data Science & Business.

She holds a Master’s degree in Business and Economics (2004) and a PhD in Statistics (2008) from the University of Naples Federico II, Italy. Her research focuses on Data Sciences and Statistical Learning methods, with a focus on Structural Equation Modeling, PLS Methods, classification algorithms and psychometric methods. Her research has been published in internationally recognized journals such as Structural Equation Modeling: A Multidisciplinary Journal, Journal of Production Economics, Journal of Organizational Behavior, Recherche et Applications en Marketing, International Journal of Information Management and Management Decision. Also contributed to the Handbook of Partial Least Squares: Concepts, Methods and Applications.

She has been a visiting researcher at several esteemed institutions, including the University of California, Santa Barbara, the University of Michigan, Ann Arbor, the University of Hamburg, Charles University in Prague, HEC School of Management in Paris, and has served as an external lecturer at ESSEC Business School, Sciences Po Paris, and Sorbonne University in Abu Dhabi.