Data science hackathon attracts IMPA Tech students

21/3/25

This week, IMPA Tech students took part in Hack4Dev, a data science hackathon for space research. The event, which took place from March 17 to 20 at the headquarters of the Brazilian Center for Physics Research (CBPF), aimed to promote practical experience in data science applied to space problems and stimulate education in the area of machine learning and artificial intelligence.

There were three days of immersion, during which the participants worked on machine learning solutions to challenges associated with the use of CubeSats, small satellites widely used in scientific and technological research.

Richard Viana, an IMPA Tech student selected for the hackathon, explained how the challenge worked: “The main goal was to improve a model for classifying satellite images, prioritizing the sending of data to Earth in such a way that the model requires the least possible computational resources and has a superior response time.”

For him, the experience was enriching and allowed him to develop critical thinking applied to the field of data science. “It was an intense and motivating experience, which reinforced my interest in the area. The opportunity to interact with other participants and mentors was valuable, as it allows for the exchange of knowledge and different perspectives on the problem,” he said.

The Hackathon was promoted by the National Observatory (ON), the Federal University of Rio de Janeiro (UFRJ) and the CBPF. The event was organized by the Artificial Intelligence in Physics Laboratory (LAB-IA) and Professor Clécio Roque de Bom.

For some participants, the Hackathon was also an opportunity to get to know CBPF’s laboratories, facilities and areas of activity. Bianca Zavadisk, an IMPA Tech student, took advantage of the challenge to gain practical experience by solving real-world research problems. “Immersive learning stimulates problem-solving skills, teamwork and time organization, as well as being an opportunity to learn more about different machine learning and data science techniques in an applied context,” she said.

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