Neil Schroeder
About Neil Schroeder
Neil Schroeder is a Machine Learning Engineer with a strong background in theoretical and mathematical physics. He specializes in developing interpretable Python algorithms and focuses on computer vision solutions in the precision agriculture sector.
Work at Sentera
Neil Schroeder has been employed as a Machine Learning Engineer at Sentera since 2023. In this role, he focuses on developing computer vision solutions tailored for the precision agriculture sector. His work involves leveraging machine learning techniques to enhance agricultural practices through data-driven insights.
Education and Expertise
Neil Schroeder completed his Bachelor’s degree in Theoretical and Mathematical Physics at the University of Minnesota from 2014 to 2017. He further pursued a Doctor of Philosophy (PhD) in Elementary Particle Physics at the University of Minnesota-Twin Cities, which he completed from 2017 to 2021. His educational background is complemented by a strong foundation in mathematics, statistics, and computer science, which underpins his expertise in machine learning.
Background
Neil Schroeder began his academic journey at the University of Minnesota Duluth, where he studied Physics from 2012 to 2014. He later worked as a Student Laborer at the University of Minnesota from 2015 to 2017. Following this, he joined CERN as a Research Associate from 2017 to 2023, where he gained significant experience in high energy physics before transitioning to his current role at Sentera.
Achievements
Neil Schroeder specializes in developing interpretable and explainable Python algorithms for extracting insights from data. His work emphasizes the application of data-driven approaches to solve complex problems. He thrives in fast-paced environments and is dedicated to creating innovative solutions within the fields of machine learning and precision agriculture.