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Learning Systems

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:  Jesus Cerquides
Eva Armengol
Tenured Scientist
Phone Ext. 431851

Rocco Ballester Benito
Industrial PhD Student

Jesus Cerquides
Scientific Researcher
Phone Ext. 431859

Bjoern Komander
PhD Student

Ramon Lopez de Mantaras
Adjunct Professor Ad Honorem
Phone Ext. 431828

Oguz Mulayim
Contract Researcher
Phone Ext. 431845

Pau Olives Tarres
Contract Engineer

Enric Plaza
Research Professor
Phone Ext. 431852

Pol Rodriguez Farres
Masters Student

Alessia Sabia
PhD Student

Martí Sánchez Fibla
Tenured Scientist
Phone Ext. 431853

Borja Velasco
Industrial PhD Student
Phone Ext. 431866

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]
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. [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]
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]
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://doi.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]
Bjoern Komander,  Jesus Cerquides,  & Jaume Piera (2023). Developing and Validating Tools for the Automated Analysis and Enhancement of Online Discussions. HHAI 2023: Augmenting Human Intellect (pp 433--435). IOS Press. [BibTeX]  [PDF]
Hafiz Budi Firmansyah,  Jose Luis Fernandez-Marquez,  Jesus Cerquides,  Valerio Lorini,  Carlo Alberto Bono,  & Barbara Pernici (2023). Enhancing Disaster Response with Automated Text Information Extraction from Social Media Images. 2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (BigDataService) (pp. 71--78). [BibTeX]
Georgios Athanasiou,  Josep Lluis Arcos,  & Jesus Cerquides (2023). Enhancing Medical Image Segmentation: Ground Truth Optimization through Evaluating Uncertainty in Expert Annotations. Mathematics, 11. https://doi.org/10.3390/math11173771. [BibTeX]  [PDF]
Bjoern Komander,  Jesus Cerquides,  Jaume Piera,  Jeffrey Chan,  & Azadeh Alavi (2023). Expert Finding for Citizen Science. Artificial Intelligence Research and Development (pp 59--69). IOS Press. https://doi.org/10.3233/FAIA230659. [BibTeX]  [PDF]
Borja Velasco-Regulez,  & Jesus Cerquides (2023). Hydranet: A Neural Network for the Estimation of Multi-Valued Treatment Effects. Artificial Intelligence Research and Development (pp 16--27). IOS Press. https://doi.org/10.3233/FAIA230655. [BibTeX]  [PDF]
Carlo Bono,  Oguz Mulayim,  & Barbara Pernici (2023). Learning Early Detection of Emergencies from Word Usage Patterns on Social Media. Terje Gjøsæter, Jaziar Radianti, & Yuko Murayama (Eds.), Information Technology in Disaster Risk Reduction (pp. 308--323). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-34207-3_20. [BibTeX]  [PDF]
Rocco Ballester,  Yanis Labeyrie,  Oguz Mulayim,  Jose Luis Fernandez Marquez,  & Jesus Cerquides (2023). Mathematical and Computational Models for Crowdsourced Geolocation. Ismael Sanz, Raquel Ros, & Jordi Nin (Eds.), Frontiers in Artificial Intelligence and Applications, Vol. 375: Artificial Intelligence Research and Development (pp 301--310). IOS Press. https://doi.org/10.3233/FAIA230699. [BibTeX]  [PDF]
A. Raes,  N. Azari-Dolatabad,  G. Athanasiou,  J.L. Arcos,  J. Cerquides,  G. Opsomer,  K. Smits,  D. Angel-Velez,  & A. {Van Soom} (2023). Measuring cumulus expansion of bovine cumulus-oocyte complexes: comparing the reliability of three methods. Animal - science proceedings, 14, 449-450. https://doi.org/10.1016/j.anscip.2023.03.032. [BibTeX]  [PDF]
Joel Arweiler,  Cihan Ates,  Jesus Cerquides,  Rainer Koch,  & Hans-Jörg Bauer (2023). Similarity-Based Framework for Unsupervised Domain Adaptation: Peer Reviewing Policy for Pseudo-Labeling. Machine Learning and Knowledge Extraction, 5, 1474--1492. https://doi.org/10.3390/make5040074. [BibTeX]  [PDF]
Hafiz Budi Firmansyah,  Jose Luis Fernandez-Marquez,  Jesus Cerquides,  & Giovanna Di Marzo Serugendo (2023). Single or Ensemble Model ? A Study on Social Media Images Classification in Disaster Response. The 10th Multidisciplinary International Social Networks Conference (pp. 48--54). Association for Computing Machinery. https://doi.org/10.1145/3624875.3624884. [BibTeX]  [PDF]