2024
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Sala, A., Porcaro, L., Gómez, E., Social Media Use and adolescents' mental health and well-being: An umbrella review
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Frego, M., Consonni, C. Volume-Preserving Shear Transformation of an Elliptical Slant Cone to a Right Cone
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Hupont, I., Fernández Llorca, D., Baldassarri, S., Gómez, E., Use case cards: a use case reporting framework inspired by the European AI Act
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van Drunen, M.Z., Noroozian, A., How to design data access for researchers: A legal and software development perspective
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Lopes, D., Dong, J-D., Medeiros, P., Castro, D., Barradas, D., Portela, B., Vinagre, J., Ferreira, B., Christin, N., Santos, N., Flow Correlation Attacks on Tor Onion Service Sessions with Sliding Subset Sum
- Golightly, D., Altobelli, E., Bassi, N., Buchníček, P., Consonni, C., Juránková, P., Mitropoulos, L., Rizzi, G., Rossi, M., Scrocca, M., Rutanen, E., Kortsari, A., Niavis, H., Ride2Rail: integrating ridesharing to increase the attractiveness of rail travel
2023
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Martín Serrano, S., Izquierdo, R., García Daza, I., Sotelo, M. A., Fernández Llorca, D., Digital twin in virtual reality for human-vehicle interactions in the context of autonomous driving
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Izquierdo, R., Martín, S., Alonso, J, Parra, I., Sotelo, M. A., Fernández Llorca, D., Human-Vehicle Interaction for Autonomous Vehicles in Crosswalk Scenarios: Field Experiments with Pedestrians and Passengers
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Garcés, D., Santos, M., Fernández Llorca, D. Language Models for Automatic Distribution of Review Notes in Movie Production
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Gómez-González, E. and Gomez, E., Artificial intelligence for healthcare and well-being during exceptional times
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Carrasco Limeros, S., Majchrowska, S., Johnander, J., Petersson, C., Fernández Llorca, D. Towards explainable motion prediction using heterogeneous graph representations
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Porcaro, L., Vinagre, J., Frau, P., Hupont, I., Gómez, E. Behind Recommender Systems: the Geography of the ACM RecSys Community
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Garcés, D., Santos, M., Fernández Llorca, D. Text Classification for Automatic Distribution of Review Notes in Movie Production
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Martin S., Fernandez Llorca, D., García, I., Sotelo, M. A. Realistic Pedestrian Behaviour in the CARLA Simulator Using VR and Mocap
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Porcaro, L., Castillo, C., Gómez, E., Assessing the Impact of Music Recommendation Diversity on Listeners: A Longitudinal Study
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Porcaro, L., Castillo, C., Gómez, E., Vinagre, J. Fairness and Diversity in Information Access Systems
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Escobar-Planas, M., Charisi, V., Hupont, I. Martínez-Hinarejos, C-D, Gómez, E. Towards Children-Centred Trustworthy Conversational Agents
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Gómez, E., Hupont, I., Sanchez, I., Fernandez Llorca, D. Hacia un marco regulatorio holístico de la Inteligencia Artificial fiable en la Unión Europea: una perspectiva científico-técnica
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Quintanar, A., Izquierdo, R., Parra, I., Fernandez Llorca, D. Goal-Oriented Transformer to Predict Context-Aware Trajectories in Urban Scenarios
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Panigutti, C., Hamon, R., Hupont, I., Fernandez Llorca, D., Fano Yela, D., Junklewitz, H., Scalzo, S., Mazzini, G., Sanchez, I., Soler Garrido, J., Gomez, E., The role of explainable AI in the context of the AI Act
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Carrasco, S., Majchrowska, S., Johnander, J., Petersson, C., Sotelo, M. A., Fernandez Llorca, D., Towards trustworthy multi-modal motion prediction: Holistic evaluation and interpretability of outputs
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Behjati, P., Rodriguez, P., Fernández, C., Hupont, I., Mehri, A., Gonzàlez, J., Single image super-resolution based on directional variance attention network
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Raissa Silva, P., Vinagre, J., Gama, J., Towards federated learning: An overview of methods and applications
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Kriston, A., Hamon, R., Fernandez Llorca, D. et al., Toward explainable, robust and fair AI in automated and autonomous vehicles
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Fernández Llorca, D., Charisi, V., Hamon, R., Sanchez, I., Gomez, E., Liability Regimes in the Age of AI: a Use-Case Driven Analysis of the Burden of Proof
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Schedl, M., Gómez, E., Lex, E., Trustworthy Algorithmic Ranking Systems
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Hupont, I., Tolan, S., Frau, P., Porcaro, L., Gómez, E., Measuring and fostering diversity in Affective Computing research
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Hupont, I. Micheli, M., Delipetrev, B., Gómez E., Soler Garrido, J., Documenting High-Risk AI: A European Regulatory Perspective
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Fernandez Llorca, D. and Gomez, E., Trustworthy Artificial Intelligence Requirements in the Autonomous Driving Domain
- Soler Garrido, J. et al., AI Watch: Artificial Intelligence Standardisation Landscape Update
2022
- Sanchez-Martinez et al., Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging
- Duch-Brown et al., New Publication in Research Policy: Market power and artificial intelligence work on online labour markets
- Hupont et al., Monitoring diversity of AI conferences: lessons learnt and future challenges in the DivinAI project
- Fernandez Llorca, D. and Gomez Gutierrez, E., Artificial Intelligence in Autonomous Vehicles: towards trustworthy systems
- Hamon et al., Artificial Intelligence in Automated Driving: an analysis of safety and cybersecurity challenges
- Biparva et al., Video action recognition for lane-change classification and prediction of surrounding vehicles
- Martinez Plumed et al., AI Watch: Revisiting Technology Readiness Levels for relevant Artificial Intelligence technologies
- Izquierdo Gonzalo et al., Testing Predictive Automated Driving Systems: Lessons Learned and Future Recommendations
- Hupont et al., The landscape of facial processing applications in the context of the European AI Act and the development of trustworthy systems
- Charisi et al., Artificial Intelligence and the Rights of the Child: Towards an Integrated Agenda for Research and Policy
- Grunert et al., HumaniTies and Artificial Intelligence
- Escobar-Planas, Towards Trustworthy Conversational Agents for Children
- Izquierdo et al., Vehicle trajectory prediction on highways using bird eye view representations and deep learning
- Chraibi Kaadoud et al., Explaining Aha! moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI
- Behjati et al., Single Image Super-Resolution Based on Directional Variance Attention Network
- Estevez Almenzar et al., Glossary of human-centric artificial intelligence
- Escobar-Planas et al., Guidelines to Develop Trustworthy Conversational Agents for Children
- Garcia Daza et al., Sim-to-real transfer and reality gap modeling in model predictive control for autonomous driving
- Hernández Martínez et al., Towards view-invariant vehicle speed detection from driving simulator images
- Martín Serrano et al., Insertion of real agents behaviors in CARLA autonomous driving simulator
- Escobar-Planas et al., “That Robot Played with Us!” Children’s Perceptions of a Robot after a Child-Robot Group Interaction
- Escobar-Planas et al., Enhancing the Design of a Conversational Agent for an Ethical Interaction with Children
- Charisi et al., Exploring the Concept of Fairness in Everyday, Imaginary and Robot Scenarios: A Cross-Cultural Study With Children in Japan and Uganda
- Lemaignan et al., UNICEF Guidance on AI for Children: Application to the Design of a Social Robot For and With Autistic Children
- Gomez, R. and Charisi, V., UNICEF Pilot study on Policy Guidance for AI for Children
- Davison et al., Words of encouragement: how praise delivered by a social robot changes children’s mindset for learning
- Portela et al., A Comparative User Study of Human Predictions in Algorithm-Supported Recidivism Risk Assessment
2021
- Grubanov-Boskovic et al., Health and long-term care workforce: demographic challenges and the potential contribution of migration and digital technology
- Charisi et al., The Effects of Robot Cognitive Reliability and Social Positioning on Child-Robot Team Dynamics
- Fernández Llorca et al., Vision-based vehicle speed estimation: A survey
- Tolan et al., Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks
- Charisi et al., What future for European robotics?
- Gomez-Gonzalez et al., Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
- Lorenzo et al., CAPformer: Pedestrian Crossing Action Prediction Using Transformer
- Corrales Sánchez et al., Are We Ready for Accurate and Unbiased Fine-Grained Vehicle Classification in Realistic Environments?
- Izquierdo et al., Vehicle Lane Change Prediction on Highways Using Efficient Environment Representation and Deep Learning
- Hupont et al., How diverse is the ACII community? Analysing gender, geographical and business diversity of Affective Computing research
- Gómez et al., Evaluating recommender systems with and for children: towards a multi-perspective framework
- Hernández Martínez et al., Data-driven vehicle speed detection from synthetic driving simulator images
- Gómez-Cañón et al., Music Emotion Recognition: Toward new, robust standards in personalized and context-sensitive applications
- Quintanar et al., Predicting Vehicles Trajectories in Urban Scenarios with Transformer Networks and Augmented Information
- Carrasco et al., SCOUT: Socially-COnsistent and UndersTandable Graph Attention Network for Trajectory Prediction of Vehicles and VRUs
- Fernandez Llorca et al., Trustworthy Autonomous Vehicles
- Charisi et al., Designing and Developing Better Robots for Children: A Fundamental Human Rights Approach
- Charisi et al., The Effects of Robot Cognitive Reliability and Social Positioning on Child-Robot Team Dynamics
2020
- Freire et al., Measuring Diversity of Artificial Intelligence Conferences
- Gómez-González et al., Artificial intelligence in medicine and healthcare: a review and classification of current and near-future applications and their ethical and social Impact
- Samoili et al., AI Watch: Defining Artificial Intelligence
- Charisi et al., Child-Robot Collaborative Problem-Solving and the Importance of Child's Voluntary Interaction: A Developmental Perspective
- Miron et al., Addressing multiple metrics of group fairness in data-driven decision making
- Martínez-Plumed et al., Does AI Qualify for the Job? A Bidirectional Model Mapping Labour and AI Intensities
- Tolan, S., Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges
- Tolan et al., Measuring the Occupational Impactof AI: Tasks, Cognitive Abilitiesand AI Benchmarks
- Gómez-González, E., Artificial Intelligence in Medicine and Healthcare: applications, availability and societal impact
- Miron et al., Evaluating causes of algorithmic bias in juvenile criminal recidivism
- De Nigris et al., Artificial Intelligence and Digital Transformation: early lessons from the COVID-19 crisis
- Shakespeare et al., Exploring Artist Gender Bias in Music Recommendation
- Samoili et al., Setting the Boundaries of the AI Landscape: An Operational Definition for the European Commission’s AI Watch
- Fabra-Boluda et al., Family and Prejudice: A Behavioural Taxonomy of Machine Learning Techniques
- Hernández-Orallo et al., AI Paradigms and AI Safety: Mapping Artefacts and Techniques to Safety Issues
- Martínez-Plumed et al., Tracking AI: The Capability is (Not) Near
- Martínez-Plumed et al., CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories
- Martínez-Plumed et al., AI Watch: Assessing Technology Readiness Levels for Artificial Intelligence
- Martínez-Plumed et al., Futures of Artificial Intelligence through Technology Readiness Levels, Telematics and Informatics
2019
- Tolan, S., Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges
- Martens, Bertin and Tolan, Songül, Will This Time Be Different? A Review of the Literature on the Impact of Artificial Intelligence on Employment, Incomes and Growth
- Paniagua, E., El dilema de la tecnología ética – The dilemma of ethical technologies
- Martens, B., The impact of data access regimes on artificial intelligence and machine learning
- Tolan et al., Why Machine Learning May Lead to Unfairness: Evidence from Risk Assessment for Juvenile Justice in Catalonia
- Mathioudakis et al., Affirmative Action Policies for Top-k Candidates Selection, With an Application to the Design of Policies for University Admissions
- Paniagua, E., The dismissed cancer tech assessment
- Porcaro L. and Gomez E., 20 Years of Playlists: A Statistical Analysis on Popularity and Diversity
- Porcaro L. and Gomez E., A Model for Evaluating Popularity and Semantic Information Variations in Radio Listening Sessions
- Sturm et al., Artificial Intelligence and Music: Open Questions of Copyright Law and Engineering Praxis
- Sanchez-Martinez et al., Machine Learning for Clinical Decision-Making: Challenges and Opportunities
- Knees et al., Proceedings of the 1st Workshop on Human-Centric Music Information Research Systems
- Gomez et al., Fairness, Accountability and Transparency in Music Information Research (FAT-MIR)
- Meeting Report: PHRP Expert Meeting on Predictive Policing Report
- Alcorn et al., Educators’ views on using humanoid robots with autistic learners in special education settings in England
- Wijnen et al., Now we’re talking: Learning by explaining your reasoning to a social robot
- Workshop report: AI and child rights policy (UNICEF)
2018
- Martens et al., The digital transformation of news media and the rise of fake news
- Gómez et al., Assessing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour
- Charisi et al., The Near Future of Children's Robotics
- Charisi et al., Novelty-based cognitive processes in early childhood in music-making settings
- Gómez et al., Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners
- Fernández-Macías et al., A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work
- Hernández-Orallo et al., Surveying Safety-relevant AI Characteristics
- La Vanguardia: ¿Es deseable que los robots imiten la voz humana?