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  • ETSE exposition

Three specialists from the Universitat awarded for their research and dissemination of Artificial Intelligence

  • Scientific Culture and Innovation Unit
  • November 19th, 2019
(From left to right) Daniel García-Costa, Emilia López-Iñesta and Francisco Grimaldo.
(From left to right) Daniel García-Costa, Emilia López-Iñesta and Francisco Grimaldo.

The DataBeers València+Barcelona Project, aimed at disseminating advances in the intelligent processing of data and which is part of research staff of the Universitat de València (UV), has been awarded by the Associació Catalana d’Intel·ligència Artificial (ACIA, Catalan Association for Artificial Intelligence) on the occasion of its divulgation task. In addition, Francisco Grimaldo, Professor at the Department of Computer Science of the Universitat de València and member of the Data Beers València node, has been awarded for his research work at the ACIA International Congress.

The first ACIA Prize for the best work on dissemination research in Artificial Intelligence 2019 has been awarded to a team composed by Francisco Grimaldo; Emilia López-Iñesta, Professor in the Department of Mathematics Education; and Daniel García-Costa, PhD student in Artificial Intelligence at the Engineering Technical School (ETSE-UV).

DataBeers València+Barcelona is a dissemination initiative that explains the Artificial Intelligence and Data Science advantages in a relaxed atmosphere.  It has a global reach and is organised in more than 20 cities in 12 countries. The València and Barcelona meetings have been held for the past four years, and take place approximately every three months. In the case of València, the host entity is the Octubre Centre de Cultura Contemporània, and until the end of September of this year there have been 56 lectures in 14 of these events. The 15th Edition will take place next Thursday 28th November. Free tickets available at the following link

In addition, Francisco Grimaldo, also Vice-Dean of the ETSE-UV, has received the Best Communication prize of the ACIA International Congress for his work Micro-Foundations of Macroeconomic Dynamics:  The Agent-Based BAM Model. This has been developed in collaboration with Mexican researchers from the Universidad Veracruzana, with whom ETSE-UV has a specific collaboration agreement in the AI field and with researchers from the Italian CNR, in which Grimaldo is an associate researcher.

The research, the presentation of which has been awarded by ACIA, proposes to implement an agent-based model for the study of macroeconomic dynamics from the micro interactions that occur between individuals who are part of labour markets, credit and goods consumption.

Francisco Grimaldo, Emilia López Iñesta and Daniel García-Costa explore in the field of applied artificial intelligence, data analysis and visualization. Also, they are members of the Intelligent Data Analysis Laboratory research group.


DataBeers VLC

DataBeersVLC is the reference meeting in València to get to know the benefits and advances of Artificial Intelligence and Data Science in a relaxed and fun atmosphere. The aim of this non-profit organization is to bring together the community interested in any aspect of data, from a point of view totally multidisciplinary.

In the DataBeersVLC days, 4 or 5 speakers give a short lecture, saving a little bit of their time before and after these interventions to discuss among the attendees and speakers. Since 2016, the activity has had more than 1700 registrations and, as a result of the implementation of active policies to give visibility to the female references in this sector, has achieved a balanced composition of both women and men speakers.

DataBeersVLC has the support of ETSE-UV, the Faculty of Mathematics, the Scientific Culture and Innovation Unit of the UV, the Institut d'Estudis Catalans, Acció Cultural del País Valencià and the Octubre Centre de Cultura Contemporànea.



Platas-López, A., Guerra-Hernández, A., Cecconi, F., Paolucci, M., & Grimaldo, F.  «Micro-foundations of macroeconomic dynamics: the agent-based BAM model». Artificial Intelligence Research and Development.


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