Sam Lausten
About Sam Lausten
Sam Lausten is a Machine Learning Engineer with a Master's degree in Data Science from the University of Colorado Boulder. He has experience in data-centric approaches to robotics, specializing in machine learning for autonomous vehicle systems at Torc Robotics.
Work at Torc Robotics
Sam Lausten currently serves as a Machine Learning Engineer at Torc Robotics, a role he has held since 2022. His work focuses on data-centric approaches to enhance robotics systems, particularly in the realm of autonomous vehicles. Prior to this position, he worked as a Data Engineer II at Torc Robotics from 2021 to 2022 and as a Data Engineer from 2020 to 2021. During his tenure, he contributed to the development of machine learning solutions aimed at improving self-driving technology.
Education and Expertise
Sam Lausten holds a Master's degree in Data Science from the University of Colorado Boulder. He also earned a Bachelor's degree in Environmental Data Science from Virginia Tech, where he studied from 2018 to 2021. His educational background provides a strong foundation in data analysis and machine learning, equipping him with the skills necessary to tackle complex challenges in robotics and autonomous systems.
Background
Before joining Torc Robotics, Sam Lausten worked as a Covid-19 Data Intern at Virginia Tech from 2019 to 2020. This role involved analyzing data related to the pandemic, contributing to public health efforts during a critical time. His experience at Virginia Tech and subsequent roles at Torc Robotics have shaped his expertise in data science and machine learning applications.
Achievements
Throughout his career, Sam Lausten has specialized in integrating complex algorithms with machine learning to address challenges in autonomous vehicle systems. His contributions at Torc Robotics have been focused on enhancing self-driving technology, which is a significant area of development in the field of robotics. His work reflects a commitment to leveraging artificial intelligence to tackle global challenges.