Brett Naul
About Brett Naul
Brett Naul is a Founding Engineer at Replica, where he has worked since 2019. He has a strong academic background with a Ph.D. from Stanford University and experience in machine learning and software development.
Work at REPLICA
Brett Naul serves as a Founding Engineer at Replica, a position he has held since 2019. In this role, he contributes to the development and implementation of advanced technologies. His work focuses on enhancing the company's engineering capabilities and driving innovation within the organization. Naul's experience in machine learning and software development supports Replica's mission to create impactful solutions.
Previous Experience at Sidewalk Labs
Before joining Replica, Brett Naul worked as a Machine Learning Engineer at Sidewalk Labs from 2017 to 2019. During his tenure in the San Francisco Bay Area, he applied machine learning techniques to urban innovation projects. His contributions helped advance the company's initiatives in smart city development and data-driven solutions.
Education and Expertise
Brett Naul has an extensive educational background. He earned a Doctor of Philosophy (Ph.D.) in Computational and Mathematical Engineering from Stanford University, where he studied from 2010 to 2015. Additionally, he holds a Bachelor of Science (BS) in Mathematics and a Master of Science (M.S.) in Statistics, both from Stanford University. His academic training provides a strong foundation for his work in engineering and data analysis.
Research at University of California, Berkeley
Brett Naul worked as a Postdoctoral Researcher at the University of California, Berkeley from 2015 to 2017. In this role, he engaged in advanced research projects that contributed to the field of computational science. His work during this period focused on developing methodologies and algorithms that enhance scientific computing.
Software Development at Knewton
Prior to his academic and engineering roles, Brett Naul was a Software Developer at Knewton from 2009 to 2010 in New York, NY. His responsibilities included developing software solutions that supported educational technologies. This early experience in software development laid the groundwork for his future roles in engineering and machine learning.