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Jesus
Jesus
 
Cerquides
Cerquides

Scientific Researcher
Scientific Researcher


Jesus
Jesus
 
Cerquides
Cerquides
Scientific Researcher
Scientific Researcher
Head of the Learning Systems Group
Head of the Learning Systems Group

Learning Systems
Learning Systems
(+34) 93 580 9570 ext.
431859
431859
cerquide@iiia.csic.es
cerquide@iiia.csic.es
Research areas:
  • Causal Inference
  • Machine Learning
  • Optimisation
  • Deep Learning
  • Citizen Science
  • Probabilistic Graphical Models
  • Probabilistic Learning
  • Combinatorial Optimisation
  • Natural Language Processing
  • Image Segmentation
  • Multiagent Systems
  • Swarn Computing
  • Approximate Reasoning and Soft computing
  • Causal Inference
  • Machine Learning
  • Optimisation
  • Deep Learning
  • Citizen Science
  • Probabilistic Graphical Models
  • Probabilistic Learning
  • Combinatorial Optimisation
  • Natural Language Processing
  • Image Segmentation
  • Multiagent Systems
  • Swarn Computing
  • Approximate Reasoning and Soft computing
Impact areas:
  • Healthcare
  • Industry
  • Smart Cities
  • Social Networking
  • Transport / Automotive
  • Healthcare
  • Industry
  • Smart Cities
  • Social Networking
  • Transport / Automotive
SDGs:
  • GOAL 03: Good Health and Well-being
  • GOAL 09: Industry, Innovation & Infrastructure
  • GOAL 13: Climate Action
  • SDGs: General
  • GOAL 16: Peace, Justice and Strong Institutions
  • GOAL 11: Sustainable Cities and Communities
  • GOAL 10: Reduced Inequality
  • GOAL 06: Clean Water and Sanitation
  • GOAL 03: Good Health and Well-being
  • GOAL 09: Industry, Innovation & Infrastructure
  • GOAL 13: Climate Action
  • SDGs: General
  • GOAL 16: Peace, Justice and Strong Institutions
  • GOAL 11: Sustainable Cities and Communities
  • GOAL 10: Reduced Inequality
  • GOAL 06: Clean Water and Sanitation
2024
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]
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]
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]
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]
Becky White,  Arnault Gombert,  Tim Nguyen,  Brian Yau,  Atsuyoshi Ishizumi,  Laura Kirchner,  Alicia Leon,  Harry Wilson,  Giovanna Jaramillo-Gutierrez,  Jesus Cerquides,  & others (2023). Using artificial intelligence to inform infodemic insights: The development of the who ears platform. APHA 2023 Annual Meeting and Expo . [BibTeX]
Becky K. White,  Arnault Gombert,  Tim Nguyen,  Brian Yau,  Atsuyoshi Ishizumi,  Laura Kirchner,  Alicia León,  Harry Wilson,  Giovanna Jaramillo-Gutierrez,  Jesus Cerquides,  Marcelo D'Agostino,  Cristiana Salvi,  Ravi Shankar Sreenath,  Kimberly Rambaud,  Dalia Samhouri,  Sylvie Briand,  & Tina D. Purnat (2023). Using Machine Learning Technology (Early Artificial Intelligence-Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study. JMIR Infodemiology, 3, e47317. https://doi.org/10.2196/47317. [BibTeX]  [PDF]
2022
Fabio Murgese,  Gerard Alcaina,  Oguz Mulayim,  Jesus Cerquides,  & Jose Luis Fernandez Marquez (2022). Automatic Outdoor Image Geolocation with Focal Modulation Networks. Atia Cortés, Francisco Grimaldo, & Tommaso Flaminio (Eds.), Frontiers in Artificial Intelligence and Applications, Vol. 356: Artificial Intelligence Research and Development (pp 279--288). IOS Press. https://doi.org/10.3233/FAIA220349. [BibTeX]  [PDF]