Data Science @ IFCA

This page gathers all Data Science and Deep Learning applications developed at IFCA by the Advanced Computing and e-Science Group.

big projects
deep learning
federated learning
image classification
machine learning
time series
ongoing projects
2022 - Ongoing

AI4EOSC (Artificial Intelligence for the European Open Science Cloud) delivers an enhanced set of advanced [...]

2022 - Ongoing
Anonymity tools

The goal is to perform a comprehensive study of data anonymization techniques. We present the implementation [...]

2022 - Ongoing
FACE (FAir Computational Epidemiology)

FACE (FAIR Computational Epidemiology) is a consortium of the Spanish National Research Council (CSIC), participated by [...]

2022 - Ongoing
Federated Learning

Federated learning is a data decentralization privacy-preserving technique used to perform machine or deep learning in [...]

2022 - Ongoing

This project closely related to the AI4EOSC project. The goal is to support Machine Learning applications for [...]

2021 - Ongoing
COVID and genetics

Project INMUGEN is using deep learning to identify the individual risk of developing severe COVID19 [...]

2021 - Ongoing
COVID and nursing homes

Proyect BRANYAS is using deep learning to infer profile risks associated to COVID19 for people living [...]

2021 - Ongoing
COVID and radiology

We are using deep learning techniques for image analysis to look for radiomic markers in thoracic [...]

2020 - Ongoing
COVID incidence prediction

We trained an deep learning model to try to predict COVID incidence using current incidence [...]

2020 - Ongoing
Alzheimer and wine consumption

We want to understand the relation between wine consumption and the risk of developing alzheimer. For [...]

2019 - Ongoing
Meteorology Statistical Downscaling

This usecase intends to link large-scale atmospheric variables with the local variables of interest relying on [...]

2018 - Ongoing
Intrusion Detection Systems with Deep Learning

This project intends to improve classical Intrusion Detection Systems (IDS) using Deep Learning tools. The idea is [...]

2018 - Ongoing
Water depth from satellite images

We use use a deep learning classifier to accurately predict water depth (bathymetry) from Sentinel-2 images. The [...]

2017 - Ongoing
Water quality from satellite images

We use a deep learning classifier to accurately predict water quality (algae) from Sentinel-2 images. The training [...]

2020 - 2022
COVID in Spanish

The project analyzes the complete corpus of news about COVID19 published by The Conversation (in Spanish) [...]

2019 - 2020
Dark Matter searches

We train an image classifier to classify events of the DAMIC-M (DArk Matter In CCDs) [...]

2019 - 2020
Fire monitoring from satellite images

We use use a deep learning classifier to accurately detect and monitor forest fires from [...]

2019 - 2020
Water quality from sensors

We use use a machine learning models to infer water quality variables (nutrients) from surrogate variables [...]

2018 - 2020

The goal of the project is to prepare a new generation of e-infrastructures that harness latest [...]

2018 - 2020
Satellite super-resolution

We use Deep Learning to upscale the multispectral images of several satellites (Sentinel 2, Landsat 8, [...]

2018 - 2019
Bird sound classifier

We trained an audio classifier to identify bird species from bird sounds. We used the Xenocanto [...]

2018 - 2019
Chest X-ray classifier

The aim of this project is to improve classification speed and accuracy of chest X-ray [...]

2018 - 2019
Conus classification

We trained an image classifier to identify conus marine snails at species level. The training dataset [...]

2018 - 2019
Phytoplankton classification

We trained an image classifier to identify phytoplankton in collaboration with the Vlaams Instituut voor de [...]

2018 - 2019
Seeds classification

We trained an image classifier to identify seed images in collaboration with Spanish Royal Botanical Garden. As [...]

2018 - 2019
Modelling species distributions

We used an autoencoder to learn in an unsupervised manner the distribution of species in a [...]

2018 - 2019
Zooplankton classification

We trained an image classifier to identify zooplankton in collaboration with the Lifewatch project. [...]

2016 - 2019
Plant classification

We trained an image classifier to identify plants species. In a first iteration we used the [...]

2017 - 2018
HEP Particle collisions

The application of deep learning techniques using convolutional neural networks to the classification of particle collisions [...]