We are pleased to announce that the GTS Research Group from Universidad Carlos III de Madrid (UC3M) has been included in the provisional resolution of the Sinérgicos R&D grants awarded by the Community of Madrid. These highly competitive grants are designed to support disruptive, frontier research projects carried out jointly by two research groups from…
Dr. Alejandro Lancho, along with students Rodrigo Oliver Coimbra and Ricardo Vázquez Álvarez from Universidad Carlos III de Madrid, took part in this year’s Wireless Wanderlust Data to Information (D2I) Competition at IEEE ISIT 2025, held from June 22 to 27 in Ann Arbor, Michigan. The team obtained first place in this international competition. The…
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…
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…
Title: Uncertainty propagation methods for collision avoidance in autonomous navigation Ref.: N629092412095 Principal Investigator: Javier López Santiago Starting Date: 01/08/2024 Ending Date: 31/07/2027 Budget: 315.198,57 € Background:
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…
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…
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)…
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…
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…
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…
Antonio Artés Rodríguez and Pablo Martínez Olmos have recieved funding for two collaborative research projects within the call «Medicina Personalizada de Precisión» granted by Instituto de Salud Carlos III de Madrid. Antonio Artés Rodríguez Title: Integrating longitudinal patient-generated data and multi-omic profiling for comprehensive precision oncology in womens’ cancers Ref.: PMP22/00032 Principal Investigator: Quintela, Miguel…
Title: Deep Attentive Time Series Modelling for Quantitative Finance Author: Fernando Moreno Pino Supervisors: Antonio Artés Rodríguez, Pablo M. Olmos Abstract: Time series modelling and forecasting is a persistent problem with extensive implications in scientific, business, industrial, and economic areas. This thesis’ contribution is twofold. Firstly, we propose a novel probabilistic time series forecasting methodology that introduces…
Title Regularizing transformers with deep probabilistic layers Authors Aurora Cobo Aguilera, Pablo M. Olmos, Antonio Artés-Rodríguez and Fernando Pérez-Cruz Abstract Language models (LM) have grown non-stop in the last decade, from sequence-to-sequence architectures to attention-based Transformers. However, regularization is not deeply studied in those structures. In this work, we use a Gaussian Mixture Variational Autoencoder…
“Inteligencia Artificial para la medición de PROs en pacientes Oncológicos”, I Edición Farmaimpulso OncoHematologia 2023.