Undergraduate and master students, as well as alumni, computer professionals and teachers from various faculties of the UCLM They met on February 17 at regional conferences WiDS, joining the international conference Women in Data Science, which takes place in the Standford University annually since 2015.

According to the professors of the academic institution: Julia Flores, Maite Alonso and Cristina Romero, organizers of the activity and ambassadors WiDS, the balance of the same was positive, with the idea of ​​being able to carry out future editions, “where attractive themes are proposed in this current field. In addition, we invite all interested parties to follow up on ‘streaming’ of the conference WiDS which will take place at Stanford on March 2, ”they indicate.

During the event, two researchers from the Big Data and Machine Learning field participated, with invited papers. The doctor Ana M. Martínez Fernández works as a Large-scale Specialist at the renewable energy company Vestas, and directs research projects in this field, from its headquarters in Aaarhus (Denmark). In his presentation, he explained how wind energy can be treated with big data and machine learning, telling some real examples.

For her part, the doctor Cristina Romero GonzálezShe is currently a professor in the Mathematics department of the UCLM, spoke of the neural networks used in GAN (Generative Adversarial Networks) to allow DeepFake. This last one deals with the technique used so that a person’s face can be integrated into a video where another one originally appeared, “as an example the viral video on social networks and mobile messaging services that was titled‘ Team E ’”.

Before the talks, a ‘data fair ’was held, in which different posters and applications were shown, where women belonging to research groups from different fields exposed how they apply data science to specific problems. In particular, air quality, nursing, juvenile criminology, drug development, and economics were addressed.

The conference concluded with a round where the impact of data science in different areas was analyzed.

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