Research groups

There is a wide range of research groups affiliated with the School of Computer Systems Engineering, the School of Computer Engineering, the School of Telecommunications Engineering and the University Institute for Automotive Research (INSIA). Researchers from these groups are actively involved in supervising students in the PhD Programme in Computer Science and Technologies:

• Applied Intelligence and Data Analysis (AIDA)
  • Short description: AIDA is a multidisciplinary research group located at the Technical University of Madrid. Our main research areas are: Machine Learning (Deep Learning, Classification, Clustering, Hidden Markov Models), Decision Support Systems, Computational Intelligence, Evolutionary Computation, Data Mining & Social Network Analysis, Big Data, and Intelligent Systems for Industry. The group has published more than 400 publications and 50 competitive research and industrial projects, the group has an outstanding experience in both research cooperation and partnership consortium.
  • Research lines:
    • Machine Learning
    • Deep Learning
    • Natural Language Processing
    • Bio-inspired Computing (Evolutionary Computation, Swarm Intelligence)
    • Social Network Analysis
    • Disinformation & Misinformation
    • AI Applications for Cybersecurity and Industry 4.0
  • Contact: aida@upm.es
  • Head: David Camacho (camacho@upm.es)
• Engineering education for a sustainable world, based on IoT (REFERENT)
  • Short description: REFERENT is a multidisciplinary research group of the Universidad Politécnica de Madrid formed in 2021. Their research areas combine the principles of education with emerging technologies to create innovative solutions that address sustainability challenges facing our Society. Here, Internet of Things (IoT) can enable students to design, build, and operate systems that are efficient, environmentally friendly, and socially responsible. The aim of the group is to investigate and to train students to develop practical solutions that promote sustainable development, such as reducing energy consumption, conserving resources, and improving the quality of life for people in various communities. This requires a multidisciplinary approach that integrates educational technology, computer science, environmental science, and social sciences. REFERENT is participating in several national and international projects.
  • Research lines:
    • Smart green cities
    • Emprendimiento de base tecnológica y social
    • Internet of things y tecnología ubicua
    • Modelos y tecnologías de aprendizaje en educación: e-learning y en abierto
    • Mecatrónica
  • Contact: referent@upm.es
  • Head: Edmundo Tovar Caro (tovar@upm.es)
• Grupo de Ingeniería de Redes y Servicios Avanzados de Telecomunicación (GISAI)
  • Short description: GISAI has extensive experience in designing digitalisation services and solutions (sensorisation, Industry 4.0, information capture and deployment, etc.), Blockchain-based systems, next-generation secure networks (5G and 6G), and prosumer environments and platforms. GISAI technologies have been successfully deployed in various scenarios, including the agricultural and livestock sectors (with projects such as VACADENA, funded by the Ministry of Economy), industrial sectors (mainly agri-food, with projects like DEMETER -H2020-), retail (supermarkets and small establishments, in projects like INPAINK, also granted by the Ministry of Economy), communication infrastructures (TOSS project, by the European organisation EIT), public works (in the PERIMETER project by CDTI), and local or regional administration (CITIES2030 project, H2020).
  • Research lines:
    • 5G and 6G mobile secure technologies
    • Industry 4.0 systems and cyber-physical environments
    • Blockchain networks and services
    • Geospatial processing
    • Architectures, protocols, and services for the Internet of Things
    • Environments for creating and providing prosumer services
  • Contact: robles@upm.es
  • Head: Tomas Enrique Robles Valladares (robles@upm.es)
• Mathematical Modeling and Biocomputation (MMB)
  • Short description: The MMB (Mathematical Modeling and Biocomputation) research group focuses on a wide range of areas of study. This includes developing combinatorial algorithms for finite and infinite sequences, as well as data-intensive algorithms and computations. Additionally, they explore applied Deep Learning in different areas as telecommunication networks, cybersecurity, Industry 4.0, Intelligent Water Decision Making and Plant Sensing and Monitoring among others. The group also investigates discrete quantum computing and its complexity along with conventional and unconventional models of computation.
  • Research lines:
    • Discrete Quantum Computing and Complexity
    • Machine Learning and Deep Learning Applied to 5G/6G networks and cybersecurity
    • Generative models and Large Language Models applications
    • AI Applications for Environmental Resource Management
    • Intelligent Sensing and Monitoring for Precision Agriculture
    • Machine Learning applications for Energy Optimization
    • Models of conventional and unconventional computing
  • Contact: mozo@upm.es
  • Head: Alberto Mozo (mozo@upm.es)
• Grupo de Tecnología del Software y Sistemas
  • Short description: The Systems and Software Technology Group (SYST) research is focused on studying how Cyber Physical Systems / IoT Systems design and architecture impact the final product, and process characteristics that would lead to the”right”product, early and within the budget. SYST considers People, their activity, sentiments and emotions, a key part of the system under design; sustainability is a cross-cutting concern. Examples of domains where SYST has been active are Smart Grids, Smart Campuses, Smart Cities, and Space Engineering. In collaboration with industrial partners, SYST devised and implemented a Global Software Factory to foster New Product Design and Innovation making extensive use of Agile approaches. The SYST group has been closely collaborating with Industry and Academic partners for years within national, European Union, European Space Agency and ITEA projects.
  • Research lines:
    • Cyber Physical Systems Modelling and Architecture Architecture
    • Agile and Innovation
    • Innovación en Ingeniería de Software
    • Smart Grids, Smart Campuses, and Smart Cities
    • Collective Intelligence
  • Contact: garbajosa@upm.es
  • Head: Juan Garbajosa (garbajosa@upm.es)
• KNOwledge Discovery and Information Systems (KNODIS)
  • Short description: KNOwledge Discovery & Information Systems (KNODIS) is a research group located at the Universidad Politécnica de Madrid. Our area of research focuses on machine learning and data science. More specifically, our research focuses on the sub-areas of recommender systems, deep learning and combinatorial optimization. In addition, given the teaching nature of the university, we are involved in various educational innovation projects. We have a proven research background with dozens of publications in leading international scientific journals and we work actively with industry to transfer the knowledge resulting from our research to society.
  • Research lines:
    • Recommendation Systems
    • Deep Learning Models
    • Combinatorial Optimisation
  • Contact: knodis@upm.es
  • Head: Fernando Ortega Requena (ortega@upm.es)
• Tecnologías de la GeoInformación y Sistemas Inteligentes (MERCATOR)
  • Short description: multidisciplinary research group in intelligent systems applied to geo-information field and real industry problems, including deep learning and bio-inspired optimization systems.
  • Research lines:
    • Safety in the collective transport of persons and in the transport of goods. PMF vehicles, protection systems and mobility.
    • Investigation of traffic accidents. Analysis of causes and consequences.
    • Biomechanics of impact applied to the improvement of passive safety of vehicles.
    • Driver Assistance Systems (ADAS).
    • Assessment and prediction of the impacts of road transport on safety and the environment. Development and application of models.
    • Alternative propulsion systems and the environmental impact of motor vehicles.
    • Computational mechanics applied to the study of vehicle dynamic behaviour.
  • Contact: serradilla@upm.es
  • Head: Miguel Ángel Manso Callejo (manso@upm.es)
• Next Generation Internet Group (GING)
  • Short description: GING is a multidisciplinary research group located at the Technical University of Madrid. Our main research areas are Internet and Web technologies, technology-enhanced learning, videoconferencing systems, and social networks. The group has participated in many public and private national and international research projects and has extensive experience in software development, research cooperation and partnership consortium.
  • Research lines:
    • Internet and Web technologies
    • Technology-enhanced learning
    • Video Conferencing systems
    • Social networks
  • Contact: internetng@upm.es / a.gordillo@upm.es
  • Head: Juan Quemada (quemada@upm.es)