Tevis Gehr
About Tevis Gehr
Tevis Gehr is the Principal Machine Intelligence Architect at SRC, where he leads the core machine intelligence team. He has a background in mechanical engineering and data science, with previous roles in various organizations, including KickView Corporation and Sundyne.
Current Role at SRC
Tevis Gehr serves as the Principal Machine Intelligence Architect at SRC, a position he has held since 2021. In this role, he leads the core machine intelligence team at SRC's Machine Intelligence and Autonomy Center of Excellence. His responsibilities include overseeing projects that integrate advanced machine learning techniques with various applications, focusing on enhancing the capabilities of machine intelligence systems.
Previous Experience
Tevis Gehr has a diverse background in engineering and machine learning. He worked at Sundyne as a Project Management Intern and Engineering Intern in 2014. He then served as a Machine Learning Research Engineer at KickView Corporation from 2017 to 2019. Prior to that, he held the position of Mechanical Engineering Intern at Woodward, Inc. from 2013 to 2014 and worked as a Mechanical Process Automation Engineer at Sundyne from 2014 to 2017. Additionally, he gained experience as a Data Center Intern at NOAA from 2006 to 2008.
Education and Expertise
Tevis Gehr has a strong educational foundation in engineering and data science. He earned a Bachelor's Degree in Mechanical Engineering from Colorado State University, completing his studies from 2010 to 2015. He furthered his education by obtaining a Master of Science in Computer Science from Georgia Institute of Technology between 2018 and 2021. Additionally, he studied Data Science at Galvanize in Denver, achieving a Data Science Immersive in 2017, and completed a Deep Learning Foundations Nanodegree from Udacity.
Research Interests
Tevis Gehr has a strong interest in the integration of machine learning with signal processing. This focus aligns with his work at SRC, where he leads initiatives that explore the application of machine intelligence in various technological contexts. His expertise in both machine learning and engineering positions him to contribute significantly to advancements in these fields.