Charles Frye
About Charles Frye
Charles Frye is an AI Engineer with a strong background in biology and computer science. He has worked in various roles related to deep learning and education, and currently works at Modal Labs in the New York City Metropolitan Area.
Current Role at Modal Labs
Charles Frye serves as an AI Engineer at Modal Labs, a position he has held since 2024. His work is based in the New York City Metropolitan Area, where he operates in a hybrid work environment. In this role, he applies his expertise in artificial intelligence to develop innovative solutions, leveraging his strong background in both biology and computer science.
Previous Experience at Weights & Biases
Charles Frye worked at Weights & Biases as a Deep Learning Instructor from 2019 to 2020. During this seven-month tenure in the San Francisco Bay Area, he focused on educating others about deep learning techniques. He later returned to Weights & Biases as a Deep Learning Educator from 2020 to 2021, where he continued to share his knowledge and expertise in the field.
Internship at Bay Labs, Inc.
In 2018, Charles Frye completed a two-month internship as a Deep Learning Engineering Intern at Bay Labs, Inc. This experience allowed him to apply his skills in deep learning within a practical setting, contributing to projects that intersected healthcare and technology.
Educational Background in Neuroscience
Charles Frye earned his Doctor of Philosophy (PhD) in Neuroscience from the University of California, Berkeley, where he studied from 2014 to 2020. His academic background provides a solid foundation for his work in AI engineering, particularly in understanding the biological aspects of computational models.
Bachelor's Degree in Computational Neuroscience
Charles Frye obtained a Bachelor's degree in Computational Neuroscience from the University of Chicago, where he studied from 2010 to 2013. This early educational experience laid the groundwork for his interdisciplinary approach, combining insights from neuroscience with computational techniques.