The research of this group focuses on the development of machine learning algorithms, models, software, and applications. From an algorithmic/modeling perspective, the group pursues research in Probabilistic Graphical Models, Case-Base Reasoning, Transfer Learning, and Deep Learning. From the software and applications perspective the group concentrates on the application areas such as Social Networks, Music, Robotics, Multiagent Systems, Bioinformatics, and Healthcare.
Head of Department: Enric Plaza Cervera
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In Press
Daniel Pardo Navarro,
Mehmet Oguz Mulayim,
& Manuel Castillo
(In Press).
Decoding Cheese Ripening: A Deep Learning Approach to Non-Invasive Monitoring.
Artificial Intelligence Research and Development - Proceedings of the 27th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2025
.
[BibTeX]
2025
Daniel Pardo Navarro,
Manuel Castillo,
Mehmet Oguz Mulayim,
& Jesus Cerquides Bueno
(2025).
Machine Learning in Cheese-Making: Methods, Applications, and the Future.
Food Engineering Reviews.
https://doi.org/10.1007/s12393-025-09420-x.
[BibTeX]
Carla Martins,
Vânia Teófilo,
Marta Clemente,
Mariana Corda,
Jose Fermoso,
Alicia Aguado,
Sandra Rodriguez,
Hanns Moshammer,
Alexandra Kristian,
Mireia Ferri,
Belén Costa-Ruiz,
Leticia Pérez,
Wojciech Hanke,
Artur Badyda,
Piotr Kepa,
Katarzyna Affek,
Nina Doskocz,
Laura Martín-Torrijos,
Mehmet Oguz Mulayim,
Cesar Mediavilla Martinez,
Alba Gómez,
Ruben González,
Isaac Cano,
Josep Roca,
Simon deLeede,
& Susana Viegas
(2025).
Sources, levels, and determinants of indoor air pollutants in Europe: A systematic review.
Science of The Total Environment, 964, 178574.
https://doi.org/10.1016/j.scitotenv.2025.178574.
[BibTeX]
[PDF]
2024
Hafiz Budi Firmansyah,
Jose Luis Fernandez Marquez,
Oguz Mulayim,
Jorge Gomes,
& Valerio Lorini
(2024).
Accelerating Crisis Response: Automated Image Classification for Geolocating Social Media Content.
Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
(pp. 77–81).
Association for Computing Machinery.
https://doi.org/10.1145/3625007.3627831.
[BibTeX]
[PDF]
Gil-Gonzalez Sergi,
Velasco-Regúlez Borja,
Cerquides Jesus,
Hinarejos Pedro,
Monllau Joan Carles,
& Pelfort Xavier
(2024).
Antibiotic-loaded bone cement is associated with a reduction of the risk of revision of total knee arthroplasty: Analysis of the Catalan Arthroplasty Register.
Knee Surgery, Sports Traumatology, Arthroscopy, n/a.
https://doi.org/10.1002/ksa.12361.
[BibTeX]
[PDF]
David Gómez-Guillén,
Mireia Díaz,
Josep Lluís Arcos,
& Jesus Cerquides
(2024).
Bayesian Optimization with Additive Kernels for a Stepwise Calibration of Simulation Models for Cost-Effectiveness Analysis.
International Journal of Computational Intelligence Systems, 17, 249.
https://doi.org/10.1007/s44196-024-00646-x.
[BibTeX]
[PDF]
Dimitra Bourou,
Marco Schorlemmer,
Enric Plaza,
& Marcell Veiner
(2024).
Characterising cognitively useful blends: Formalising governing principles of conceptual blending.
Cognitive Systems Research, 86, 101245.
https://doi.org/10.1016/j.cogsys.2024.101245.
[BibTeX]
[PDF]
Rocco Ballester,
Yanis Labeyrie,
Oguz Mulayim,
Jose Luis Fernandez Marquez,
& Jesus Cerquides
(2024).
Crowdsourced geolocation: Detailed exploration of mathematical and computational modeling approaches.
Cognitive Systems Research, 88, 101266.
https://doi.org/10.1016/j.cogsys.2024.101266.
[BibTeX]
Hafiz Budi Firmansyah,
Jose Luis Fernandez Marquez,
Oguz Mulayim,
Jorge Gomes,
Joao Ribeiro,
& Valerio Lorini
(2024).
Empowering Crisis Response Efforts: A Novel Approach to Geolocating Social Media Images for Enhanced Situational Awareness.
ISCRAM Proceedings, 21.
https://ojs.iscram.org/index.php/Proceedings/article/view/21.
[BibTeX]
[PDF]
Nuria Correa,
Jesus Cerquides,
Rita Vassena,
Mina Popovic,
& Josep Lluis Arcos
(2024).
IDoser: Improving Individualized Dosing Policies with Clinical Practice and Machine Learning.
Expert Systems with Applications, 238, 121796.
https://doi.org/10.1016/j.eswa.2023.121796.
[BibTeX]
[PDF]
Pol Rodríguez-Farrés,
Rocco Ballester,
Carlos Ansótegui,
Jordi Levy,
& Jesus Cerquides
(2024).
Implementing 3-SAT Gadgets for Quantum Annealers with Random Instances.
Leonardo Franco, Clélia Mulatier, Maciej Paszynski, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, & Peter M. A. Sloot (Eds.),
Computational Science -- ICCS 2024
(pp. 277--291).
Springer Nature Switzerland.
[BibTeX]
[PDF]
Hafiz Budi Firmansyah,
Valerio Lorini,
Oguz Mulayim,
Jorge Gomes,
& Jose Luis Fernandez Marquez
(2024).
Improving Social Media Geolocation for Disaster Response by Using Text From Images and ChatGPT.
Proceedings of the 2024 11th Multidisciplinary International Social Networks Conference
(pp. 67–72).
Association for Computing Machinery.
https://doi.org/10.1145/3675669.3675696.
[BibTeX]
[PDF]
Annelies Raes,
Georgios Athanasiou,
Nima Azari-Dolatabad,
Hafez Sadeghi,
Sebastian Gonzalez Andueza,
Josep Lluis Arcos,
Jesus Cerquides,
Krishna Chaitanya Pavani,
Geert Opsomer,
Osvaldo Bogado Pascottini,
Katrien Smits,
Daniel Angel-Velez,
& Ann Van Soom
(2024).
Manual versus deep learning measurements to evaluate cumulus expansion of bovine oocytes and its relationship with embryo development in vitro.
Computers in Biology and Medicine, 168, 107785.
https://doi.org/10.1016/j.compbiomed.2023.107785.
[BibTeX]
[PDF]
Nuria Correa,
Jesus Cerquides,
Josep Lluis Arcos,
Rita Vassena,
& Mina Popovic
(2024).
Personalizing the First Dose of FSH for IVF/ICSI Patients through Machine Learning: A Non-Inferiority Study Protocol for a Multi-Center Randomized Controlled Trial.
Trials, 25, 38.
https://doi.org/10.1186/s13063-024-07907-2.
[BibTeX]
[PDF]
Gennaro Junior Pezzullo,
Beniamino Di Martino,
Oguz Mulayim,
& Eva Armengol
(2024).
Time Series Analysis and Modeling with Federated Learning Techniques in Cloud Edge Scenario: A Case Study on Environmental Air Quality in Homes.
Leonard Barolli (Eds.),
Advances on P2P, Parallel, Grid, Cloud and Internet Computing
(pp. 25--34).
Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-76462-2_3.
[BibTeX]
2023
Carlo Bono,
Oguz Mulayim,
Cinzia Cappiello,
Mark James Carman,
Jesus Cerquides,
Jose Luis Fernandez Marquez,
Maria Rosa Mondardini,
Edoardo Ramalli,
& Barbara Pernici
(2023).
A Citizen Science Approach for Analyzing Social Media With Crowdsourcing.
IEEE Access, 11, 15329-15347.
https://doi.org/10.1109/ACCESS.2023.3243791.
[BibTeX]
[PDF]
N Correa Mañas,
J Cerquides,
J L Arcos,
R Vassena,
& M Popovic
(2023).
A clinically robust machine learning model for selecting the first FSH dose during controlled ovarian hyperstimulation: incorporating clinical knowledge to the learning process.
Human Reproduction, 38, dead093.226.
https://doi.org/10.1093/humrep/dead093.226.
[BibTeX]
[PDF]
Dimitra Bourou,
Marco Schorlemmer,
& Enric Plaza
(2023).
An Image-Schematic Analysis of Hasse and Euler Diagrams.
Maria M. Hedblom, & Oliver Kutz (Eds.),
Proceedings of The Seventh Image Schema Day co-located with The 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023), Rhodes, Greece, September 2nd, 2023
.
CEUR-WS.org.
https://ceur-ws.org/Vol-3511/paper\_05.pdf.
[BibTeX]
Jon Perez-Cerrolaza,
Jaume Abella,
Markus Borg,
Carlo Donzella,
Jesús Cerquides,
Francisco J. Cazorla,
Cristofer Englund,
Markus Tauber,
George Nikolakopoulos,
& Jose Luis Flores
(2023).
Artificial Intelligence for Safety-Critical Systems in Industrial and Transportation Domains: A Survey.
ACM Computing Surveys.
https://doi.org/10.1145/3626314.
[BibTeX]
[PDF]
David Gómez-Guillén,
Mireia Díaz,
Josep Lluis Arcos,
& Jesus Cerquides
(2023).
Bayesian Optimization with Additive Kernels for the Calibration of Simulation Models to Perform Cost-Effectiveness Analysis.
Artificial Intelligence Research and Development (pp 143--152).
IOS Press.
https://doi.org/10.3233/FAIA230677.
[BibTeX]
[PDF]
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