IDEA-CM project funded by Comunidad de Madrid

Title: Artificial Intelligence for Industry 4.0 (IDEA-CM) Ref.: TEC-2024/COM-89 Principal Investigator: Antonio Artés Rodríguez Starting Date: 01/01/2025 Ending Date: 31/12/2027 Budget: 1.026.000 € Background: The competitiveness of European industry is deeply linked to its ability to adopt and develop cutting-edge and innovative technologies. In this context, the integration of artificial intelligence (AI) into industrial processes is…

Doctoral Thesis Defense of María Martínez García

Title: Machine Learning in Personalized Medicine and Genomics. Author: María Martínez García. Abstract: Personalized medicine, also known as precision medicine, aims to use an individual’s genetic profile to guide decisions on disease prevention, diagnosis, and treatment. Unlike traditional medicine’s one-fits-all approach, personalized medicine considers individual variations that can influence disease risk, severity, treatment response, and susceptibility to…

Pablo Martinez Olmos Awarded 2024 Leonardo Grant from the BBVA Foundation

Title: THAI: Towards Humble and Discoverable AI Principal Investigator: Pablo Martínez Olmos Starting Date: 30/09/2024 Ending Date: 30/03/2026 Budget: 40.000,00 Abstract: This project addresses concerns about overconfidence and reliability in generative AI. As AI technologies continue to reshape various sectors, the project’s primary motivation lies in mitigating the risks associated with AI’s persuasive capabilities, particularly…

Smartcrisis 2.0 research project Funded by “La Caixa” Foundation

Title: Multisite Smartphone-based Ecological Momentary Intervention for suicide prevention Ref.: HR23-00421 Principal Investigator: Antonio Artés Rodríguez Starting Date: 01/03/2024 Ending Date: 28/02/2027 Budget: 999.955,00 € Background: Suicide is a major public health issue that represents a leading cause of years of life lost and entails substantial costs for health and welfare systems. Prevention of suicide…

Doctoral Thesis Defense of Ignacio Peis Aznarte

Title: Advanced Inference and Representation Learning Methods in Variational Autoencoders. Author: Ignacio Peis Aznarte Abstract: Deep Generative Models have gained significant popularity in the Machine Learning research community since the early 2010s. These models allow to generate realistic data by leveraging the power of Deep Neural Networks. The field experienced a signficant breakthrough when Variational Autoencoders (VAEs)…

Doctoral Thesis Defense of Daniel Barrejon Moreno

Title: How can humans leverage machine learning? From Medical Data Wrangling to Learning to Defer to Multiple Experts. Author: Daniel Barrejon Moreno. Abstract:The irruption of the smartphone into everyone’s life and the ease with which we digitise or record any data supposed an explosion of quantities of data. Smartphones, equipped with advanced cameras and sensors, have empowered…

Article published in Internet Interventions

Title Automatic patient functionality assessment from multimodal data using deep learning techniques – Development and feasibility evaluation Authors Emese Sukei, Santiago de Leon Martinez, Pablo M. Olmos and Antonio Artés-Rodríguez Abstract Wearable devices and mobile sensors enable the real-time collection of an abundant source of physiological and behavioural data unobtrusively. Unlike traditional in-person evaluation or…

Article accepted for publication in Jmir

Title One-week suicide risk prediction using real-time smartphone monitoring Authors Maria Luisa Barrigon; Lorena Romero-Medrano; Pablo Moreno-Muñoz; Alejandro Porras-Segovia; Jorge Lopez-Castroman; Philippe Courtet; Antonio Artés-Rodríguez; Enrique Baca-Garcia Abstract Background: Suicide is a major global public health issue becoming increasingly common despite preventive efforts. Though current methods for predicting suicide risk are not sufficiently accurate, technological…