Summary
Matias Mazzanti is a CONICET doctoral researcher in Computer Science with a strong foundation in physics (Licenciatura, Universidad de Buenos Aires, 8.85) and eight years of experience combining teaching and research. He pivoted from theoretical physics to applied programming, focusing on machine learning, Bayesian inference and data science through electives, a robotics lab internship, and a thesis on Bayesian inference with ML techniques. Comfortable moving between rigorous mathematical thinking and practical implementation, he has taught at secondary schools while developing research-grade code and experiments. Based in Vicente López, Argentina, he brings a problem-solving mindset honed in physics to tackle complex data and inference challenges in academic and applied settings.
8 years of coding experience
Licenciatura, Physics, 8.85, Licenciatura, Physics, 8.85 at Universidad de Buenos Aires