Adán JOSÉ-GARCÍA

Adán JOSÉ-GARCÍA

Research Fellow in Digital Health

University of Lille

I am a Research Fellow in Digital Health at the Department of Computer Science, CRIStAL Lab, University of Lille, France. This is a collaborative project with the Lille University Hospital and INCLUDE. My current project involves developing and applying unsupervised machine learning techniques to classify patients with systemic autoimmune diseases.

Before joining the University of Lille, I was a Research Fellow in Machine Learning at the Department of Computer Science, Institute of Data Science and Artificial Intelligence, University of Exeter, United Kingdom (UK). Before this, I was a Postdoctoral Researcher with the Decision and Cognitive Sciences Research Centre, University of Manchester, UK. I hold M.Sc. and Ph.D. degrees in Computer Science from the Center for Research and Advanced Studies of the National Polytechnic Institute, Cinvestav-IPN, Mexico.

In general, my scientific expertise is focused on investigating cluster analysis methods, also known as unsupervised machine learning in Artificial Intelligence. My research consists in creating and adapting clustering approaches (e.g., multi-view clustering, biclustering) and their applications to different research fields such as digital healthcare, the labour market, and network analysis. My research currently focuses on developing integrative cluster analysis approaches to address healthcare-related data problems and help to understand better disease complications and treatment goals.

I am grateful to have been generously supported by or closely working with the following funding institutes.

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Recent Publications

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Projects

BicViz 🦠

A visualizer of SSc biclusters.

CVIK Toolbox

A CVI toolbox for estimating the number of clusters.

Multi-view Data Repository

A multi-view data repository.

COVID-19 en México 🇲🇽

Mapas interactivos del COVID-19 en México.

C3-IoC Project

A career guidance system for assessing student skills.

Evoclustering Project

Evolutionary clustering algorithms with code.

Collaborators

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Julia HANDL

Professor in Decision Sciences

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Mario GARZA-FABRE

Associate Professor in Computer Science

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Clarisse DHAENENS

Professor in Combinatorial Optimization

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Vincent SOBANSKI

Professor in Internal Medicine

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Wilfrido GÓMEZ-FLORES

Associate Professor in Machine Learning

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