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Data Science Center Mission

As a hub for research, training and knowledge transfer in Data Science and Artificial Intelligence, we aim to foster both technical advances and their permeation to society, industry and other areas of scientific enquiry.

The center serves as a meeting place for our affiliated faculty, which includes world-leading researchers in Statistics, Operations Research, Applied Economics and Artificial Intelligence, and for their international network of collaborators. 

Specific activities include hosting research projects funded by public and private institutions related to data science methodology and applications, a program for visiting scholars, and research events (seminars, scientific conferences, BGSE Summer Forum in Data Science).

We host training activities at different levels. The center coordinates the MSc in Data Science, created in 2014 as one of the first of its kind in Europe to produce graduates who can help tackle the data analysis challenges shaping our present and future. 

We also organize regular training workshops within the BGSE Summer School, Winter School, and specific training for researchers and corporations. The workshops cover topics ranging from applied data science to advanced methodology and theoretical issues.

The center is actively involved in consulting activities and inter-disciplinary academic collaborations.

Check our consulting section for success stories of firms and institutions that already benefited from our collaboration in any of our fields of expertise.

How we can help

Let us train you to acquire data science anlytics skills that you or your team are missing.

Need some help in any analytics challenge you are facing? Get your analytics to the next level: count on us as expert consultants.

Highlights and Case Studies

What we can do

New ERC project in the frontier of text analytics
Analysis of tweets to understand main topics and triggering events, together with tweet toxicity
Partner: Reuters Institute

More Cases

José G.Montalvo, Omiros Papaspiliopoulos, Timothée Stumpf-Fétizon
New methodology for predicting electoral results that combines a fundamental model and national polls within an evidence synthesis framework.
Method: Optimization
Jésica de Armas, Helena Ramalhinho
Crew optimization
Method: deep learning
Carlos Segura, Joan Verdú
Deep Learning applied to seed classification

Community

If you are interested in our activities and want to keep in touch with us, please join our community of data scientists.