Jesus
Cerquides
Scientific Researcher
Head of the Learning Systems Group
Learning Systems
(+34) 93 580 9570 ext.
431816
cerquide@iiia.csic.es
Research areas:
- Causal Inference
- Machine Learning
- Citizen Science
- Deep Learning
- Probabilistic Graphical Models
- Probabilistic Learning
- Optimisation
- Natural Language Processing
- Image Segmentation
- Combinatorial Optimisation
- Multiagent Systems
- Swarn Computing
- Approximate Reasoning and Soft computing
Impact areas:
- Healthcare
- Industry
- Smart Cities
- Social Networking
- Transport / Automotive
SDGs:
- GOAL 03: Good Health and Well-being
- GOAL 13: Climate Action
- SDGs: General
- GOAL 09: Industry, Innovation & Infrastructure
- 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]
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]
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]
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]
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}}\textendash{{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]
Georgios Athanasiou,
Jesus Cerquides,
Annelies Raes,
Nima Azari-Dolatabad,
Daniel Angel-Velez,
Ann Van Soom,
& Josep Lluis Arcos
(2022).
Detecting the Area of Bovine Cumulus Oocyte Complexes Using Deep Learning and Semantic Segmentation.
A. Cortés al. (Eds.),
Frontiers in Artificial Intelligence and Applications (pp 249-258).
IOS Press.
https://doi.org/10.3233/FAIA220346.
[BibTeX]
Borja Velasco,
Jesus Cerquides,
& Josep Lluis Arcos
(2022).
Hydranet: A Neural Network for the estimation of Multi-valued Treatment Effects.
NeurIPS 2022 Workshop on Causality for Real-world Impact
.
[BibTeX]
[PDF]
Borja Velasco,
Jose L Fernandez-Marquez,
Nerea Luqui,
Jesus Cerquides,
Josep Lluis Arcos,
Analia Fukelman,
& Josep Perelló
(2022).
Is the phase of the menstrual cycle relevant when getting the covid-19 vaccine?.
American Journal of Obstetrics & Gynecology.
[BibTeX]
[PDF]
Jerónimo Hernández-González,
Olga Valls,
Adrián Torres-Martín,
& Jesús Cerquides
(2022).
Modeling three sources of uncertainty in assisted reproductive technologies with probabilistic graphical models.
Computers in Biology and Medicine, 150, 106160.
https://doi.org/10.1016/j.compbiomed.2022.106160.
[BibTeX]
[PDF]
Nuria Correa,
Jesús Cerquides,
Josep Lluis Arcos,
& Rita Vassena
(2022).
Supporting first FSH dosage for ovarian stimulation with machine learning.
Reproductive Biomedicine Online.
https://doi.org/10.1016/j.rbmo.2022.06.010.
[BibTeX]
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