Join the Meetup to hear talks in Spanish from experts on cutting-edge topics across AI, ML, and computer vision.

Every day, we are exposed to hundreds of advertising campaigns; however, only about 12% of all this advertising leaves a lasting impression in our brains, highlighting the importance of capturing consumer attention. Evaluating the effectiveness of an advertising campaing allows us to predict its potential success. This practice has been employed by traditional marketing companies for many years, the results can be influenced. In this research, the acquisition and pre-processing of electroencephalographic (EEG) signals generated while viewing visual advertising campaigns are conducted. These signals reflect individuals' autonomic responses and are not consciously or voluntarily fabricated reactions to stimuli. Subsequently, an electrical activation analysis of the cortical brain and visualization of the EEG signals are performed through a three-dimensional representation on a standardized brain model. The brain regions with the highest electrical activation are analyzed and compared using two mathematical and computational techniques, one linear and one non-linear. The neural response due to the advertising images are compared against the brain representation during the performance of cognitive tasks involving selective attention and implicit memory. This allows us to infer the occurrence of these cognitive processes, evoked by marketing campaigns (visual ads), which are essential constructs for studying consumer behavior. The results indicate that visual advertising campaigns containing linguistic and cultural elements embedded in the graphic designs trigger greater brain activation, which is associated with the cognitive processes of selective attention and implicit memory. Thus, it can be concluded that this type of advertising images increases the probability of influencing purchasing decisions.

Victor Alfonso is from the Technological University of Pereira, with postgraduate studies in education and pedagogy. In the field of engineering, I hold a Master’s degree in Physical Instrumentation, and I am currently a Ph.D. student in Engineering at UTP. I am passionate about neuroscience, with expertise in biosignal processing, data analysis, machine learning, and experimental design. In recent years, I have devoted my work to researching the brain and its main cognitive processes.

La detección de anomalías está transformando la manufactura y la vigilancia, pero ¿qué pasa con la agricultura? ¿Puede la IA detectar realmente enfermedades de las plantas y daños por plagas con suficiente anticipación para marcar una diferencia?

Esta charla demuestra cómo la detección de anomalías identifica y localiza problemas en los cultivos, usando como ejemplo principal la salud de las hojas de café. Comenzaremos con la teoría fundamental y luego examinaremos cómo estos modelos detectan la roya y el daño por minadores en imágenes de hojas.

La sesión incluye un flujo de trabajo práctico y completo utilizando la herramienta de visión por computadora de código abierto FiftyOne, que abarca la curación de datasets, la extracción de parches, el entrenamiento de modelos y la visualización de resultados. Obtendrás tanto una comprensión teórica de la detección de anomalías en visión por computadora como experiencia práctica aplicando estas técnicas a desafíos agrícolas y en otros dominios.

Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia.

Descubre cómo la inteligencia artificial generativa está revolucionando la creación y gestión de pipelines en Azure DevOps y Github Actions. En esta sesión práctica, exploraremos cómo automatizar la generación de pipelines CI/CD que cumplan automáticamente con los estándares corporativos, utilizando plantillas inteligentes y análisis predictivo de código.

Aprenderás a implementar un sistema que interpreta cambios en pull requests, predice problemas de calidad y seguridad, y garantiza el cumplimiento normativo de forma proactiva. Veremos como documentar políticas para que la IA tome decisiones coherentes sobre advertencias y errores.

Dachi Gogotchuri of Arcasiles Group and Platform Engineering Lead at Nationale Nederlanden Spain, shaping platforms, communities, and the future through real innovation.

People have a reason to workout and with every reason, there's a story behind. Whether the goal is strength, stress relief, or transformation. In contemporary culture, these stories are often shared digitally, where exercise becomes not just a performative act but a resonant gesture within communities of friends, families, and clubs.

This project explores how real-time workout detection can amplify such narratives by translating physical poses into audiovisual messages. Each detected pose becomes a trigger for text or visual cues—ranging from poetic phrases and evocative song lyrics to quotes aligned with the symbolic act of the movement. This way, exercise becomes both action and expression creating a personalized narrative layered on top of the physical activity.

The system leverages computer vision, machine learning, large language models, and design software to construct a responsive application that shapes meaning alongside exercise. It further investigates how personalized outputs can empower individuals and reinforce collective resonance. Use cases developed with Voxel51 dependencies will also be presented.

Jose Bringas is a creative technologist exploring how emerging technologies, real-time systems, and AI can expand human expression. With a background spanning visual effects, motion design, virtual reality, and interactive media, he brings an out-of-the-box mindset to designing responsive experiences.