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Brian Soe has worked in the field of robotics control since 2013. In 2010, they were a Summer Research Fellow at NIST, where they investigated the magnetic properties of Germanium doping in alloys for MRAM application and created an adaptable multi-purpose Labview program for controlling 6+ laboratory devices. Brian also conducted experiments to measure resistivity of microscopic samples. In the same year, they were an Independent Research Study/Research Fellow at Harvey Mudd College - Computational Mechanics Lab, where they investigated the 3-dimensional morphology of microbands in plastically deformed crystalline metals and optimized the run time and memory usage of a Fast Multiscale Clustering algorithm in Matlab. In 2012, Brian was a Battery Technologies Intern at Tesla Motors, where they improved and developed cell cycling fixtures, and worked on embedded systems, thermodynamics, simulation, mechanical design, and machining. From 2013 to 2017, they were a Research Assistant in Artificial Intelligence Lab at Stanford University, where they worked towards the realization of ideal force control for robotic manipulators. Since 2017, Brian has been a System Analyst (Robotics Control) Engineer at Intuitive Surgical. In 2019, they took on the role of Controls and Systems Architecture Lead at Flexiv Ltd., where they are responsible for multi-robot system architecture, multi-arm behaviors, contact/impact control, and passivity-based joint torque control.

Brian Soe attended Harvey Mudd College from 2008 to 2012 and obtained a Bachelor of Arts in Engineering. Brian then attended Stanford University from 2012 to 2014 and earned a Master's Degree in Mechanical Engineering. Brian continued their studies at Stanford University from 2014 to 2016 and obtained an Engineer's Degree in Mechanical Engineering.