We can get machine learning models to do very complicated things that can't be programmed imperatively.
Rafael Rivera-Soto
Rafael Rivera-Soto posed outside the HPC building
PEOPLE HIGHLIGHT

Rafael Rivera-Soto Shares His Passion for AI

Rafael Rivera-Soto is passionate about artificial intelligence, deep learning, and machine learning technologies. He works in LLNL’s Global Security Computing Applications Division, also known as GSCAD, which implements innovative solutions to pressing national security concerns brought to the Lab by government sponsors.

These areas of data science are crucial to the national and global security Lab’s mission, especially with huge amounts of data generated at the Lab every day. Rafael says, “AI can be thought of as a new form of programming. Programs used to be imperative, needing step-by-step specifications of what to do. Now we can train models that learn those steps directly from the data.”

Rafael grew up in Puerto Rico and studied at Universidad Ana G. Mendez Gurabo, where he earned a B.S. in Computer Engineering. He’s currently working on a Master’s in Computer Science from UC Davis with help from the Lab’s Education Assistance Program and expects to graduate in 2021. Rafael credits his father with seeing his potential in CE and CS, nudging his son in that direction during school. “I fell in love with the field and started to do a lot of self-learning,” Rafael explains. He took online classes in addition to regular coursework and landed a Lab internship in 2013. At the Lab he enjoys managing multiple diverse projects and interacting with talented people in a variety of fields.

Artificial intelligence can be thought of as a new form of programming. Programs used to be imperative, needing step-by-step specifications of what to do. Now we can train models that learn those steps directly from the data.

Rafael Rivera-Soto