Francisco Escolano

Associate Scientist

Francisco Escolano [BD in Computer Science - Polytecnical University of Valencia (Spain)-1992, PhD in Computer Science - University of Alicante (Spain) - 1997] is Full Professor of Computer Science and AI in the University of Alicante. His research started in the domain of medical imaging for Computer Vision, followed by work in Bayesian inference and information theory with Prof. Alan Yuille

In 2001, all these experiences crystallized in the creation of the Robot Vision Group that he led (2001-2011). See part of these efforts in http://videolectures.net/francisco_escolano/.

In 2012 he co-funded the Mobile Vision Research Lab (MVRLab) of the University of Alicante, whose main objective is to endow the Visually Impaired with artificial vision capabilities using smartphones. This work obtained twice the Vodafone “Mobile Application for Good” award in 2014 and 2017. The most important development to date is Navilens (a color QR quaternary code that captures the attention of the mobile phone’s camera).

More recently, he joined the Data Science against COVID-19 Taskforce led by Dr. Nuria Oliver. The team participated and won the first prize of the XPRIZE Pandemic Response Challenge. This new dimension of his research will grow by tutoring two ELLIS PhD students at the ELLIs Unit Alicante.

Website: https://sites.google.com/site/scohomepage/

Publications in association with the ELLIS Unit Alicante

2023

Begga, A., Garibo I Orts, O., De Maria Garcia, S., Escolano, F., Lozano, M.A., Oliver, N., & Conejero, J.A. (2023). Predicting COVID19 pandemic waves including vaccination data with deep learning. Frontiers of Public health .

Arnaiz-Rodríguez, A., Escolano, F., & Oliver, N. (2023). FairShap: A Data Re-weighting Approach for Algorithmic Fairness based on Shapley Values. arXiv:2303.01928 .

2022

Arnaiz-Rodríguez, A., Begga, A., Escolano, F., & Oliver, N. (2022). DiffWire: Inductive Graph Rewiring via the Lovász Bound. Proceedings of the First Learning on Graphs Conference, PMLR , 198, 15:1-15:27.

Lozano, M.A., Garibo, O., Piñol, E., Rebollo, M., Polotskaya, K., Garcia-March, M. A., Conejero, J. A., Escolano, F., & Oliver, N. (2022). Open Data Science to fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge. International Joint Conference on Artificial Intelligence Organization (IJCAI) 5304-5308.

Best paper award track from sister conferences

Riccio, P., Psomas, B., Galati, F., Escolano, F., Hofmann, T., & Oliver, N. (2022). OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters. 36th Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track .

Riccio, P., Oliver, J. L., Escolano, F., & Oliver, N. (2022). Algorithmic Censorship of Art: A Proposed Research Agenda. 13th International Conference on Computational Creativity .

2021

Lozano, M.A., Garibo, O., Piñol, E., Rebollo, M., Polotskaya, K., Garcia-March, M. A., Conejero, J. A., Escolano, F., & Oliver, N. (2021). Open Data Science to fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge. Joint European Conference on Machine Learning and Knowledge Discovery in Databases 384-399.

Best paper award!