Astronomy is currently facing one of its greatest challenges: the massive volume of data generated by observations and telescopes. In this scenario, Artificial Intelligence tools, such as machine learning, are emerging as key solutions to automate the classification of images and spectra.
To strengthen their skills in these advanced techniques, students and researchers from across the country gathered for the First School on Machine Learning Applied to the Analysis of Massive Stars and Microlensing Events, held from July 21 to 25 at the University of Valparaíso.
Representing Universidad Mayor, Dr. Ignacio Araya, Director of the Multidisciplinary Center for Physics (CMF), and postdoctoral researcher Sara Cuéllar participated as lecturers. Additionally, Data Science student Claudio Gómez was one of thirty participants selected from 118 applicants to take part in the intensive course.
The program included theoretical lectures, practical sessions, and the development of a research project, covering topics such as artificial neural networks, statistical tools, and automated analysis of astronomical data.
For Gómez, the experience was highly enriching: “The Artificial Intelligence tools I learned during my studies proved useful for the project we carried out, and the University’s name was well represented.”
He also highlighted the collaborative approach of the event: “The best knowledge emerges from multidisciplinary collaboration. I was able to help astrophysicists understand that certain challenges can be addressed using Artificial Intelligence,” he said.
Finally, Dr. Araya praised the initiative and announced that plans for its continuation are already underway: “We hope to hold the School again next year, and we are currently applying for GEMINI funding to organize it once more in 2026,” he concluded.
