Thomas M.

Thomas M. has extensive work experience in various research and engineering roles. Thomas currently works at Q-CTRL as a Lead Software Engineer, where they are responsible for developing error suppression technology MVP and implementing machine learning based product features. Prior to that, they worked at the University of California, Los Angeles as a Graduate Research and Teaching Assistant and a Project Mentor. At the university, they conducted research on reinforcement learning and supervised a team of undergraduates on a sponsored research project. Thomas also worked as a Visiting Researcher at the Max Planck Institute for Mathematics in the Sciences, focusing on stochastic neural networks and convolutional neural networks. Additionally, Thomas has interned at the Air Force Research Laboratory, where they conducted research on low dimensional mathematical models and optimization algorithms for Hall thrusters.

Thomas M. completed their Bachelor's degree in Applied Mathematics from Rensselaer Polytechnic Institute between 2013 and 2016. Thomas then pursued a Master's degree in Applied Mathematics from UCLA, where they studied from 2016 to 2018.