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Aquí puedes ver el último seminario de la serie “Nuevas soluciones con Big Data” organizados por el UC3M-Santander Big Data Institute (IBiDat) donde se presentan problemas reales en distintos campos y la solución aportada utilizando todos los datos disponibles. Lo seminarios intentan ser un punto de encuentro de profesionales y académicos para presentar problemas y analizar posibles soluciones basadas en Big Data.

Este seminario se celebró el jueves 16 de diciembre a las 17:00 en formato online.

En esta ocasión el seminario tiene como título Applications of AI and Data Science in Policing: 7 years of collaborations with the Spanish National Police. y será impartido por  Lara Quijano Sanchez – Profesora Ayudante doctor de la Escuela Politécnica Superior de la UAM

Since 2015, the speaker has undertaken multiple research projects in collaborations with the Spanish National Police in the context of AI and Data Science, ranging from predictive policing to hate speech detection. The talk provides an overview of the research advances and tools developed during these last seven years, with a particular emphasis on (i) Smart Patrolling, which combines predictive policing and patrol optimization models; (ii) VeriPol, a Natural Language Processing tool for detecting false robbery reports; (iii) VioGén, a data-driven model for determining the risk of recidivism in intimate partner violence cases; (iv) and SocialHaterBERT, a framework for the detection and visualization of hate speech in social networks. Also, the speaker presents the challenges met as an academic that collaborates with a national police institution, providing her perspective and some takeaway points on the complex interaction between the academy, the police, and the public, especially on the subject of applying AI and Data Science-based tools to public security.

 

Los seminarios están organizados por Patricia Callejo, investigadora de IBiDat (pcallejo@inst.uc3m.es) a la que puedes dirigirte para información adicional.

Los seminarios son de carácter abierto y gratuito.

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