Taylor Faucett

Taylor Faucett has a diverse professional background with experience in machine learning engineering, research, and systems engineering. They are currently working at Machina Labs as a Machine Learning Engineer since June 2022. Prior to that, they were a Postdoctoral Researcher at UC Irvine from December 2021 to June 2022, where they conducted research on deep learning and computer vision in high-energy particle detectors. They also worked as a Graduate Research Assistant at UC Irvine from June 2015 to December 2021, where they developed strategies for the application of deep learning and computer vision in physical science datasets.

Before joining UC Irvine, Taylor was a Graduate Research Assistant at the University of Hawaii at Manoa from August 2011 to May 2015, where they designed Bose-Einstein Condensate simulations and interfaced analysis and trigger system code to FPGA hardware. Additionally, they have experience as a Systems Engineer at Northrop Grumman Corporation from September 2009 to May 2011, where they designed and deployed a secure PTP radio network for Air Force installations and managed network security and stability. They also obtained a secret security clearance during this role.

Taylor Faucett completed a Doctor of Philosophy (Ph.D.) degree in Machine Learning and Experimental Particle Physics from UC Irvine, starting in 2015 and finishing in 2021. Prior to that, Taylor obtained a Master's Degree in Physics from the University of Hawaii at Manoa, studying from 2011 to 2015. Additionally, Taylor holds a Bachelor's Degree in Physics, Mathematics, and Music from Westminster College, which was earned between 2005 and 2009.