Oguz
Mulayim
Contract Researcher
Learning Systems
(+34) 93 580 9570 ext.
431845
oguz@iiia.csic.es
Research areas:
- Deep Learning
- Machine Learning
- Citizen Science
- Probabilistic Graphical Models
- Probabilistic Learning
- Federated Learning
- Case-Based Reasoning
Impact areas:
- Healthcare
- Smart Cities
- Social Networking
SDGs:
- GOAL 03: Good Health and Well-being
- GOAL 11: Sustainable Cities and Communities
- GOAL 13: Climate Action
- SDGs: General
- GOAL 16: Peace, Justice and Strong Institutions
- GOAL 06: Clean Water and Sanitation
2025
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,
Oguz Mulayim,
Cesar Mediavilla Martinez,
Alba Gómez,
Ruben González,
Isaac Cano,
Josep Roca,
& Simon 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]
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]
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]
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]
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]
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]
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]
Jesus Cerquides
(2022).
crowdnalysis: A software library to help analyze crowdsourcing results.
https://doi.org/10.5281/zenodo.5898579.
[BibTeX]
Barbara Pernici,
Carlo Bono,
Jose Luis Fernandez Marquez,
& Oguz Mulayim
(2022).
The Challenge of Collecting and Analyzing Information from Citizens and Social Media in Emergencies: The Crowd4SDG Experience and Tools.
Renata Guizzardi, Jolita Ralyté, & Xavier Franch (Eds.),
Research Challenges in Information Science: 16th International Conference, RCIS 2022, Proceedings
(pp. 823-824).
Springer.
[BibTeX]
[PDF]
Carlo Bono,
Barbara Pernici,
Jose Luis Fernandez Marquez,
Amudha Ravi Shankar,
Oguz Mulayim,
& Edoardo Nemni
(2022).
TriggerCit: Early Flood Alerting using Twitter and Geolocation - a comparison with alternative sources.
Rob Grace, & Hossein Baharmand (Eds.),
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management
(pp. 674--686).
[BibTeX]
[PDF]
2021
Jesus Cerquides,
Oguz Mulayim,
Jeronimo Hernandez-Gonzalez,
Amudha Ravi Shankar,
& Jose Luis Fernandez Marquez
(2021).
A Conceptual Probabilistic Framework for Annotation Aggregation of Citizen Science Data.
Mathematics, 9.
https://doi.org/10.3390/math9080875.
[BibTeX]
[PDF]
2020
Oguz Mulayim
(2020).
Anytime Lazy kNN (ALK): A fast anytime kNN search algorithm.
https://doi.org/10.5281/zenodo.4472641.
[BibTeX]
Oguz Mulayim,
& Josep Lluis Arcos
(2020).
Fast anytime retrieval with confidence in large-scale temporal case bases.
Knowledge-Based Systems, 206, 106374.
https://doi.org/10.1016/j.knosys.2020.106374.
[BibTeX]
[PDF]
2019
David Sanchez-Pinsach,
Oguz Mulayim,
Jennifer Grau-Sánchez,
Emma Segura,
Berta Juan-Corbella,
Josep Lluis Arcos,
Jesus Cerquides,
Monique Messaggi-Sartor,
Esther Duarte,
& Antoni Rodriguez-Fornells
(2019).
Design of an AI Platform to Support Home-Based Self-Training Music Interventions for Chronic Stroke Patients.
Jordi Sabater-Mir, Vicenç Torra, Isabel Aguilo, & Manuel González-Hidalgo (Eds.),
Frontiers in Artificial Intelligence and Applications (pp 170--175).
IOS Press.
https://doi.org/10.3233/FAIA190120.
[BibTeX]
2018
Oguz Mulayim,
& Josep Lluis Arcos
(2018).
Perks of Being Lazy: Boosting Retrieval Performance.
Twenty-Sixth International Conference on Case-Based Reasoning
.
https://doi.org/10.1007/978-3-030-01081-2_21.
[BibTeX]
2011
Josep Lluis Arcos,
Oguz Mulayim,
& David Leake
(2011).
Using introspective reasoning to improve CBR system performance.
M. T. Cox, & A. Raja (Eds.),
Metareasoning: Thinking about Thinking (pp 167-182).
MIT Press.
https://doi.org/10.7551/mitpress/9780262014809.003.0011.
[BibTeX]
2010
Oguz Mulayim,
& Josep Lluis Arcos
(2010).
Predicting Dubiosity in CBR Systems.
Expert UPDATE, 10, 1-8.
http://www.expertupdate.org/papers/10-2/1.pdf.
[BibTeX]
[PDF]
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