Eric Hofesmann

Eric Hofesmann has been working in the field of machine learning since 2014. Eric began as an Undergraduate Researcher in Machine Learning and Astrophysics at the College of Charleston, where they analyzed structural connectomics from medical imaging using deep neural networks and used data-driven approaches to investigate structural properties of gamma ray burst pulses. Eric then became a Research Engineer at the University of Michigan College of Engineering in 2017, where they developed a TensorFlow-based framework for action classification including a model zoo and efficient prototyping, as well as managed a laboratory Linux cluster. In 2018, they became a Graduate Student Research Assistant at the University of Michigan, where they investigated advances in video understanding including a PyTorch-based platform for repeatable and flexible machine learning workflows. Currently, they are a Machine Learning Engineer at Voxel51.

Eric Hofesmann completed a Bachelor's Degree in Physics from the College of Charleston between 2013 and 2017. Eric also completed a Bachelor's Degree in Computer Science from the same school during the same time period. In 2018, they went on to pursue a Master's Degree in Computer Science specializing in Artificial Intelligence from the University of Michigan, which they completed in 2019.