The Basque Center for Applied Mathematics (BCAM, Bilbao, Spain) is a world-class interdisciplinary research center on Applied Mathematics. The center was founded in 2008 by the Basque Government, the UPV/EHU and Ikerbasque. Bizkaia Regional Government, and Innobasque are also members of BCAM Steering Board. BCAM is part of the BERC (Basque Excellence Research Centres) network and it has been accredited as a “Severo Ochoa” center of excellence three times in a row by the State Research Agency. This distinction is granted to the best research institutions in the world in their field.

Judit Muñoz-Matute (IN-DEEP PI at BCAM) is a postdoctoral researcher at the Basque Center for Applied Mathematics (BCAM). Since January 2021 she is a visiting postdoctoral researcher at the Oden Institute for Computational Engineering and Sciences (OICES) at the University of Texas in Austin, USA. During her scientific career she has worked on numerical methods for solving transient Partial Differential Equations including advection-dominated-diffusion and wave propagation problems. Recently, she started working on Deep Learning algorithms for solving PDEs based on minimum residual methods. She has published 13 JCR articles and has participated in 6 research projects, including two European Union’s H2020 research and innovation programmes. Since January 2022, she is the PI of a H2020 Marie-Curie Global Fellowship: GEODPG.

 The AGH University of Sciences and Technology (AGH, Krakow, Poland) is a modern university that actively participates in fostering a knowledge-based society and creating innovative technologies. AGH has a well-established position in the country and is recognized abroad. Experienced staff, advanced laboratories, a unique campus, and, above all, the bonds that connect the AGH UST community are our greatest assets. The university has concluded nearly 300 general agreements on cooperation with universities worldwide. AGH has partners in more than 60 countries. The university has 600 student exchange agreements and 31 double degree agreements (including 1 concluded within the framework of the prestigious T.I.M.E. programme).

Maciej Paszynski (IN-DEEP PI at AGH) is a Full Professor of Computer Science at the Institute of Computer Science, AGH University of Science and Technology at Krakow, Poland. During his scientific career he has worked on numerical methods for solving stationary and transient Partial Differential Equations including advection-dominated-diffusion and wave propagation problems. He developed fast solvers for hp adaptive finite element and isogeometric analysis methods.  Recently, he started working on Deep Learning algorithms for solving PDEs using hp adaptive finite elements and isogeometric analysis. He promoted 7 Ph.D. students with distinctions .With 12 other Polish researchers, He was nominated for Heisig Prize (the so-called Polish Nobel Prize) in 2021. He co-authored 86 JCR articles and delivered over 100 presentations at international conferences and 50 seminars. 

Tecnalia Research & Innovation (Tecnalia, Bilbao, Spain) is a private, not-for-profit, applied research center of international excellence with a strong market orientation aiming at achieving a major impact in economic terms, through innovation and technological development. TECNALIA is the leading private and independent research and technology organization in Spain and one of the largest in Europe, employing around 1,381 people (272 PhDs) and with an income of 117 Million € in 2021. The whole team at TECNALIA has one GOAL: to transform technology into GDP, meaning wealth to improve people’s quality of life through the generation of business opportunities for the industry. TECNALIA is committed to generating major impacts in economic terms, by means of research and innovation in several main scopes of action: smart manufacturing, digital transformation, energy transition, sustainable mobility,  personalized health, and urban ecosystems.

Javier Del Ser (IN-DEEP PI at Tecnalia) is a Research Professor within the Core in Artificial Intelligence of TECNALIA RESEARCH & INNOVATION. His research activity focuses on Artificial Intelligence, neural computing, and machine learning for solving practical problems in industry, health, telecommunications, transportation, and smart mobility, among many others. In these fields, he has published more than 400 scientific-technical publications, edited 8 books, directed 13 doctoral theses, and participated in more than 50 research projects. He has recently been included in the list of the 2% most influential researchers in Artificial Intelligence worldwide made by Stanford University, with a citation rate received for his works of more than 2,900 annual citations (2022). 

Sergio Gil López is a senior researcher in OPTIMA (Optimization, Modelling, and Analytics) business area at TECNALIA RESEARCH & INNOVATION. He has co-authored more than 40 international journal papers and more than 45 conference contributions, four filed patents, and 2 supervised PhDs. He has also been involved in the organization of various national and international conferences, either in charge for chairing positions. His current interests deal with tackling Smart Analytics, NP-hard optimization problems through the application of heuristic and evolutionary algorithms, parallel algorithms search, local search methods, multi-objective cost functions problems, clustering/grouping, neural networks, fuzzy logic, among others.

The Arts et Métiers Institute of Technology (ENSAM, Paris, France) was founded in 1780. Since then, it has been committed to meeting constantly evolving industrial challenges and societal issues. Its primary task is to train multi-disciplinary engineers in the field of sustainable technology: engineers capable not only of designing environmentally friendly products and systems but also of overseeing an industrial organization by controlling the risks and costs. The PIMM (Processes and Engineering in Mechanics and Materials) laboratory brings together a wide range of specialists from mechanics of materials and structures to polymer chemistry.  From the advanced modeling viewpoint, PIMM develops advanced model order reduction technologies and physics-informed artificial intelligence able to proceed online and in the few-data limit, both integrated in the concept of Hybrid Twin, in close collaboration with ESI Group through the common research chair CRETATE-ID.

Francisco Chinesta (IN-DEEP PI at ENSAM) is a Full Professor of computational physics at ENSAM Institute of Technology (Paris, France), an Honorary Fellow of the “Institut Universitaire de France” – IUF- and Fellow of the Spanish Royal Academy of Engineering. He is the president of the ESI Group scientific committee and director of its scientific department. He was (2008-2012) AIRBUS Group chair professor, and since 2013 he has been the ESI Group chair professor on advanced modeling and simulation of materials, structures, processes, and systems. He received many scientific awards (including the IACM Fellow award, then the IACM Zienkiewicz award -New York, 2018). He is the author of more than 350 papers in peer-reviewed international journals and more than 1000 conference contributions. He was president of the French association of computational mechanics (CSMA) for 8 years, and chair of the WCCM in Paris (2020). He is the director of the DESCARTES project on Hybrid Artificial Intelligence that the CNRS develops in its hub in Singapore (35 M€, five years and more than 160 researchers).

Founded in 1425, Katholieke Universiteit Leuven (KU Leuven) is one of Europe's oldest universities. Driven by a relentless pursuit of knowledge, the institution has cultivated a culture of inquiry, resulting in cutting-edge research that draws the brightest minds in academia. This research not only engages a diverse student body but also fosters partnerships with industry, aiming to contribute to the betterment of society. With 15 faculties offering numerous degree programs, KU Leuven provides a fertile ground for exploration in various fields. Across nine key research areas, the institution's multidisciplinary approach ensures a breadth of knowledge and expertise, reflecting its commitment to inspiring excellence and driving progress.

Bert Pluymers (IN-DEEP PI at KU Leuven), an IOF Fellowship Holder within the Industrial Research Fund, brings a wealth of expertise as the Head of the Division Dynamics. Engaged in the academic community, he serves as a member of Leuven.AM – KU Leuven Institute for Additive Manufacturing and holds a pivotal role as a Research Manager Level 3 within the Mechanical Engineering Department Council. At the forefront of the Mecha(tro)nic System Dynamics unit (LMSD), his research spans Vibro-acoustics, Structural Reliability, Monitoring & Uncertainty, Multi-body Dynamics, Smart System Dynamics, Aero-acoustics, Virtual Sensing, Metamaterials, and the MUTANT Gear Simulation Platform. He has published over 100 research articles.

The University of Florence (UNIFI) is is one of the largest research and higher education organisations in Italy, with 1,800 structured lecturers and researchers, around 1,600 technical and administrative staff, and over 1,600 doctoral and post-doctoral students. It fosters cooperation with academic and research institutions all over the world and welcomes foreign teaching staff, researchers and students to promote cultural and scientific internationalization. It traditionally devotes particular attention to the development of collaborative relationships with foreign universities and to the process of internationalization, which has become a strategic and dominant aspect of the life of the university in research, teaching, the organization of study programmes, mobility of teachers, researchers and students. For these reasons, the University of Florence qualifies itself as one of the privileged destinations for international guests.

Carlotta Giannelli (IN-DEEP PI at UNIFI) is an Associate Professor at the Department of Mathematics and Computer Science and a key member of the Florence Center for Data Science at UNIFI. She is an expert in geometric and mathematical modeling. Her research interests encompass Computer Aided Geometric Design (CAGD), Isogeometric analysis, and Approximation theory, reflecting her commitment to advancing computational techniques in mathematical sciences. With a strong dedication to mentorship, she has supervised numerous students and postdoctoral fellows, nurturing the next generation of scholars. Her supervisory roles range from guiding Master and PhD students to overseeing postdoctoral research projects across top institutions. Her publication record comprises over 70 research articles.