Imagine the Future.

A passionate Technologist and Songwriter.

Motivations.

Brandon believes in research with long-term impact, that has potential to improve peoples' lives. His research promises to equip engineers with efficient algorithms for decision-making, and automatic design.

Research.

Brandon is interested in deep reinforcement learning algorithms that acquire generalizing behaviors, that can adapt to novel environments, and that learn efficiently from offline and unstructured experience.

Biography.

Brandon grew up in a rural community along the Columbia River in Oregon. Introduced to coding in 2012 by his close friend, he started building software applications of increasing complexity. He graduated from the Saint Helens High School as Valedictorian in 2017, and entered the UC Berkeley in the EECS Class of 2021. In 2016 and 2017, He worked with Dr. Christof Teuscher at Portland State University, investigating Sequence-To-Sequence Neural Networks. In his first year at UC Berkeley, he worked with Dr. Bruno Olshausen, and Dr. Dawn Song on two projects for Neural Program Synthesis. He is currently working with Dr. Sergey Levine on a project that introduces a new domain called Model-Based Optimization.

Resume.

Trabucco_Brandon_CV