This session showcases success stories where artificial intelligence delivers tangible value across diverse sectors. We’ll explore innovative projects that enhance processes, drive business growth, and open up new creative perspectives. A space to get inspired by real-world solutions that demonstrate the transformative potential of AI.

Presenter:

• Sergi Masip, Coordinator of AI, Quantum and Blockchain strategies at the Secretariat of Digital Policies, Government of Catalonia

Speakers:

• Ángel Cañete, Senior Computer Engineer and researcher in Centro Andaluz de
  Investigaciones del Agua, CETAQUA

• Luis Lebron,  Senior Machine Learning Engineer, i2CAT

• Xavier Guillem Moltó, CEO, OneCareAI, Spin Off del Barcelona Supercomputing Center

• Nick Van der Graaf, Senior Data Scientist, Novartis

https://politiquesdigitals.gencat.cat

Sergi Masip is a technical engineer in telecommunications, has a master’s degree in mobile communications and a master’s degree in project management. After 9 years of experience in the telco sector at Amena/Orange, he made the leap to consulting at Altran, Deloitte and Capgemini, accumulating more than 12 years of experience as a project manager, both in the private and public sectors. He currently works at the Secretariat for Digital Policies of the Government of Catalonia, from where he coordinates strategies to promote advanced digital technologies such as AI, Quantum and Blockchain.

Cetaqua

Ángel Cañete holds a PhD in Information Technologies and is a Senior Computer Engineer and IT Project Manager. He earned his degree in Computer Science
from the University of Málaga in 2017 and completed his PhD in 2024 as a researcher in Universidad de Málaga (2017–2022). Since 2022, he has worked at Cetaqua, co-leading the Digital Services and AI Applications team, contributing to innovative water cycle projects. His research areas include AI, energy efficiency, sustainable software, Edge Computing, IoT, Industry 4.0, and self-adaptive systems. He has participated in national and international projects and has 14 publications, including four in high-impact journals.

ZeroVision applies advanced Computer Vision to optimize wastewater treatment processes, addressing challenges such as blockages, spills, and sludge bulking. By applying deep learning models specifically adapted to the unique visual characteristics of wastewater environments, it ensures accurate real-time monitoring and early detection of critical events. The project enhances operational efficiency, promotes environmental sustainability, and supports the circular economy by enabling better analysis of wastewater by-products. With its modular and scalable design, ZeroVision integrates seamlessly into existing systems, offering a practical and innovative solution for smarter, more sustainable urban infrastructures.

i2cat.net | LinkedIN

Luis Lebron Casas completed his PhD in Computer Vision at Insight, Dublin City University, in 2024, with a pioneering research in the Evaluation of Video Description Generation. His doctoral career included a valuable stay in the Satoh lab at the National Institute of Informatics in Tokyo. He previously consolidated his training with a Master’s degree in Machine Learning and a Bachelor’s degree in Software Engineering from the Autonomous University of Barcelona.

After obtaining his PhD, he spent a year at the VICOMTECH Foundation as a Research Associate, leading large-scale projects at both the industrial and European levels. His research experience dates back to his collaboration on European projects at the United Research Center Ireland, complemented by professional experience as a software engineer.

Creating profiles of missing or criminal persons from descriptions is a complex and highly specialised work.
This project aims to offer complementary tools based on generative artificial intelligence, capable of bringing efficiency and precision to police guidelines by integrating natural text and voice interaction.
This aims to streamline law enforcement operations, prevent the re-victimization of witnesses and victims, and ultimately significantly increase the likelihood of identification through realistic and constantly updated representations.

onecareai.com

Law graduate, with a degree in Administration and Finance and a Master’s in Telecommunications. He has led several health-tech startups (three of them ranked in the 95th percentile on CrunchBase), raised over 10 million euros in funding, and has extensive experience in clinical validation and compliance with ISO 13485 standards. In parallel, he has developed a teaching career focused on youth entrepreneurship. He currently leads OneCareAI, a spin-off from the Barcelona Supercomputing Center that is redefining stroke prevention through AI-based digital biomarkers derived from electrocardiograms.

OneCareAI applies artificial intelligence models to electrocardiogram signals to detect molecular alterations associated with stroke risk, without the need for invasive genomic analysis. This solution enables the early detection of cerebrovascular events in a cost-effective manner, with a significant impact on public health. In this session, we will present how we validated the approach with real-world data, our hospital collaborations, and the next steps toward global commercialization.

Novartis | LinkedIN

Nick van der Graaf holds a degree in Multimedia Engineering from La Salle and a Master’s in Artificial Intelligence from KU Leuven. His professional background includes roles in consulting and the pharmaceutical sector as a computer vision engineer and data scientist, contributing and leading projects in areas such as medicine, sensors, imaging, and finance. He is currently a Senior Data Scientist at Novartis, where he applies data science to support global corporate financial decision-making.

Given limited resources, companies must allocate them as effectively as possible. AI is playing an increasingly pivotal role in supporting the decision process through in-depth market analysis and the identification of the true impact of investments. Novartis has developed a causal machine learning tool to quantify the effectiveness of field representatives’ promotional efforts. The solution, based on Bayesian learning, provides a scientific assessment to guide commercial strategy and portfolio management.