"I was associated with the PINA, MathLab group supervised by Professor Gianluigi Rozza, which works on developing an open-source library to help assist scientists in scientific machine learning research. My specific project was designing PINA’s NestedSINDy, an enhanced version of SINDy and an approach for symbolic regression, which is used to discover the governing equations from data with accuracy and interpretability. This is beneficial to the research community of PINA because it assists in understanding the governing law of scientific phenomena and generalization beyond the training data."
Tri's story
In addition to learning new math and its application to ML during Tri Nguyen ‘29 internship at SISSA, he found new hobbies such as reading, walking, and running around the city of Trieste, Italy, and took an Italian class along the way.
"This experience was my first exposure to machine learning, specifically deep learning. I was surprised that I really enjoyed exploring this topic, even though it is very math-intensive. Realizing its applications renewed my enthusiasm for studying math at MIT."Tri Nguyen '29
Major & Minor, Class
Mathematics (18) , Class of 2029
MISTI program
Internship
MISTI host
SISSA Trieste
Location
Trieste, Italy