Charles is an AI Engineer at Modal, focusing on building useful technology with large neural networks. With a PhD in Neuroscience from UC Berkeley, he has a strong background in both research and developer education, previously working as a Deep Learning Educator at Weights & Biases. He is passionate about making complex quantitative methods accessible to non-experts.
Originally from Illinois, Charles began his academic career in biology and computational neuroscience before pivoting to artificial neural networks. Outside of his professional life, he is an avid reader with broad tastes, from contemporary fiction to early modern European history, and also runs tabletop roleplaying games.
He transitioned into machine learning during his PhD by reasoning that "neural networks" had "neuro" in the name, allowing him to study them under the banner of Neuroscience.
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