Research areas: Social Media
Funder: EU
Start date: 01/09/2021
End date: 29/02/2024
Research areas: Social Media
Funder: Ministry of Science and Innovation
Start date: 01/09/2021
End date: 01/01/2024
Research areas: Space & AI
Funder: EU
Start date: 01/01/2019
End date: 31/12/2023
Research areas: Cybersecurity
Funder: Community of Madrid
Start date: 01/01/2019
End date: 31/12/2023
Research areas: Dynamic networks
Funder: EU
Start date: 04/10/2019
End date: 03/10/2023
Research areas: Social Media
Funder: BBVA
Start date: 10/10/2020
End date: 10/10/2022
Research areas: Planning, Aerospace
Funder: ENAIRE-COPAC
Start date: 01/09/2021
End date: 31/12/2021
Research areas: Education, Games
Funder: EU
Start date: 01/01/2019
End date: 31/12/2021
Research areas: Evolutionary Computation
Funder: MINECO
Start date: 01/01/2018
End date: 31/12/2021
Research areas: Industry (mining)
Funder: CHIST-ERA
Start date: 2019
End date: 2021
Research areas: Health
Funder: Comunidad de Madrid
Start date: 2020
End date: 2020
Research areas: Education, Games
Funder: EU
Start date: 2016
End date: 2018
Research areas: Social Media
Funder: EU
Start date: 2016
End date: 2018
Research areas: Cybersecurity
Funder: Community of Madrid
Start date: 2014
End date: 2018
Research areas: Evolutionary Computation
Funder: Ministerio de Economía y Competitividad
Start date: 2015
End date: 2018
Research areas: UAV/UAS
Funder: EADS–CASSIDIAN/Airbus Defence & Space
Start date: 2013
End date: 2017
Research areas: Semantic Data Retrieval
Funder: EU
Start date: 2014
End date: 2017
Research areas: Social Media
Funder: National Research Foundation, Korea
Start date: 2013
End date: 2015
Research areas: Education, Virtual Worlds
Funder: EU
Start date: 2012
End date: 2015
Research areas: Virtual Worlds
Funder: Ministerio de Ciencia
Start date: 2011
End date: 2013
Research areas: Recommender Systems
Funder: Jobssy
Start date: 2011
End date: 2012
Research areas: Recommender Systems
Funder: Jobssy
Start date: 2011
End date: 2011
Research areas: Education, Virtual Worlds
Funder: Ministerio de Ciencia
Start date: 2009
End date: 2011
Status: In progress Funder: EU (TENtec number 2020-EU-IA-0252: 29374659)
Start date: 01/09/2021 End date: 29/02/2024
Project Leaders: Ramón Salaverría (Coord./Univ. de Navarra), David Camacho (PI-UPM)
Partners: Universidad de Navarra (ES), Asociación Maldita contra la desinformación: periodismo, educación, investigación y datos en nuevos formatos (ES), Universidad Carlos III de Madrid (ES), Universidad de Granada (ES), Universidad de Santiago de Compostela (ES), Universitat Politècnica de València (ES), Universidad Politécnica de Madrid (ES), Universidad Miguel Hernández de Elche (ES), Associació Verificat (ES), Fundación Española para la Ciencia y la Tecnología (ES), Universitat de València (ES), Elcano Royal Institute (Real Instituto Elcano) (ES), Barcelona Supercomputing Center (BSC) (ES), Fundación Universitaria San Pablo CEU (ES), Universidad Rey Juan Carlos (ES), Agencia EFE SAU, SME (ES), Inevitável e Fundamental – Polígrafo (PT), Centro Protocolar de Formação Profissional para Jornalistas – Cenjor (PT), Instituto Universitário de Lisboa – Iscte (PT), OberCom – Observatório da Comunicação (PT), Universidade de Aveiro (PT), Lusa, Agência de Noticias de Portugal SA (PT), Associação Literacia Para os Media e Jornalismo (PT).
Description: IBERIFIER is an Iberian hub that aims to tackle disinformation in Spain and Portugal by bringing together a consortium of 23 partners, composed of 12 universities, 5 independent fact-checking organisations and publicly-owned news agencies, and 6 leading institutions on strategic analysis, computer and data science, and media research.
Status: In progress Funder: Ministerio de Ciencia e Innovación (PID2020-117263GB-100)
Start date: 01/09/2021 End date: 01/01/2024
Project Leaders: David Camacho, Gema Bello Orgaz
Partners: Universidad Politécnica de Madrid.
Description: The FightDIS project focuses on how information disorders spread in one of their most favourable environments: social platforms, such as Twitter or Telegram. Through the use of social network analysis techniques and artificial Intelligence algorithms (specifically machine learning), applied to actors or sets of actors where information disorders are transmitted, FightDIS aims to provide with three elements: a) a working environment that allows the application of algorithms and techniques from areas such as graph-based computing, SNA, deep learning, or natural language processing, among others, to the field of information disorders, b) the application of these techniques to real domains of study where information disorders are common, such as health, politics or extremist movements, and c) a closer approach between science and society, through the publication and dissemination of the results and new knowledge acquired for their use as Open-Science.
Status: In progress Funder: EU (813644-H2020-MSCA-ITN-2018)
Start date: 01/01/2019 End date: 31/12/2023
Project Leaders: Massimiliano Vasile (UNIVERSITY OF STRATHCLYDE), David Camacho (PI-UPM)
Partners: UNIVERSITY OF STRATHCLYDE (UK), UNIVERSITA DEGLI STUDI DI ROMA TOR VERGATA (IT), UNIVERSITATEA ALEXANDRU IOAN CUZA DIN IASI (RO), DEIMOS SPACE SOCIEDAD LIMITADA UNIPERSONAL (ES), POLITECNICO DI MILANO (IT), UNIVERSITA DI PISA (IT), DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH (DE), UNIVERSIDAD POLITÉCNICA DE MADRID (ES), ACADEMY OF ATHENS (EL), CENTRE NATIONAL D’ETUDES SPATIALES – CNES (FR), AIRBUS DEFENCE AND SPACE LTD (UK), EUROPEAN SPACE AGENCY (FR), Kyoto University (JP), DEUTSCHES ZENTRUM FUER LUFT – UND RAUMFAHRT EV (DE), Arizona Board of Regents (US), Faculty of Mathematics, University of Belgrade (RS), TECHNISCHE UNIVERSITEIT DELFT (NL), Hyperion Technologies B.V. (NL), UNIVERSIDAD CARLOS III DE MADRID (ES), THE UNIVERSITY OF TEXAS SYSTEM (US), UNIVERSITAET BREMEN (DE), ARISTOTELIO PANEPISTIMIO THESSALONIKIS (EL)
Description: A European research project to explore and exploit asteroids and make the use of space sustainable.
The Stardust Reloaded project, led by Professor Massimiliano Vasile of the University of Strathclyde, was awarded 4 million Euros through the European Commission’s Horizon 2020 programme.
Status: In progress Funder: Comunidad de Madrid (P2018/TCS-4566)
Start date: 01/01/2019 End date: 31/12/2023
Project Leaders: Juan Antonio Estevez Tapiador (UC3M, Coordinador), David Camacho Fernández (IP nodo-UAM)
Partners: Universidad Carlos III de Madrid, Universidad Autónoma de Madrid, Centro Superior de Investigaciones Científicas, Universidad Rey Juan Carlos.
Description: The scientific program proposed in this project aims at contributing to a more secure cyberspace in our current and future technological context. Our approach identifies three paradigms, each with a varying degree of maturity, that will reshape cybersecurity in the coming years. These are: the processing of massive amounts of information (big data), including those generated by citizens and devices; the embedding of computers in essentially all reallife objects (cyberphysical systems) and their connection to the Internet (IoT, Internet of Things); and the challenges and opportunities associated with the rise of quantum computing. To address these challenges we propose an interdisciplinary work program involving five research groups with proven expertise in the areas of system and application security, data analysis, next generation communication systems, and cryptography.
Status: In progress Funder: EU (COST Action, OC-2018-2 CA18232)
Start date: 04/10/2019 End date: 03/10/2023
Project Leaders: Prof Marjeta Kramar Fijavz, David Camacho (MC Substitute)
Partners: Università di Modena e Reggio, Universidad Politécnica de Madrid & Universities from more than 40 countries
Description: The main aim and objective of the Action is to bring together leading groups in Europe working on analytical and numerical approaches to a range of issues connected with modelling and analysing mathematical models for dynamical systems on networks (DSN), in order to be able to address its research challenges at a European level.
Status: In progress Funder: Código OTT-UPM: PCAI2061220327
Start date: 10/10/2020 End date: 10/10/2022
Project Leaders: Alejandro Martín García
Partners: Universidad Politécnica de Madrid.
Description: The goal of this project is to combine the knowledge of experts in communication and journalism with experts in Artificial Intelligence techniques in order to implement a tool for the general public aimed at characterising automatically information related to COVID-19.
Status: In progress Funder: ENAIRE-COPAC (FUPM 43814840001)
Start date: 01/09/2021 End date: 31/12/2021
Project Leaders: David Camacho
Partners: Universidad Politécnica de Madrid.
Description: The goal of this project is to use artificial intelligence and data analysis to outperform the take-off and landing of commercial flights in airports, in order to reduce gas emisions and noises.
Status: In progress Funder: EU (823701-ISFP-2017-AG-RAD)
Start date: 01/01/2019 End date: 31/12/2021
Project Leaders: David Camacho (Coordinador)
Partners: Universidad Politécnica de Madrid (Spain); Oulu University (Finland), Fundacion Altum (Spain), MILITOS SYMVOULEUTIKI A.E. (Greece)
Description: This project aims to overcome the acknowledged difficulty of efficient interaction with youth and vulnerable population at risk of radicalization or polarization. To do so, YoungRes advocates a new innovative approach based on digital technologies to overcome this barrier, built on previous achievements by project partners in game technology, social media analytics, and eLearning (e.g. SAVEit, RiskTrack, CrisisTracker, Clutler, E-genius, SmaCC).
Status: In progress Funder: Ministerio de Economía, Industria y Competitividad (Excelencia). TIN2017-85727-C4-3-P
Start date: 01/01/2018 End date: 31/12/2021
Project Leaders: Carlos Cotta (Univ. Málaga, Coordinador), David Camacho Fernández (IP nodo-UPM)
Partners: Universidad de Málaga, Universidad de Extremadura, Universidad de Granada, Universidad Politécnica de Madrid.
Description: This project revolves around the idea of massively complex environments, and the deployment of bioinspired algorithms onto them. We will use this umbrella term to encompass both the complexity of the underlying computational substrate on which the bioinspired algorithms are executed, and the complexity of the problem/data environment the algorithm is tackling. In both cases, complexity is to be understood as the intricate (non-random yet non-regular either) relationships among the components of the corresponding system (be it a computational environment or a system under scrutiny) giving rise to emergent properties of the latter, as well as the sheer difficulty for coping with the system due to its size or its dynamic nature, just to mention a couple of features.