Jonathon Byrd
Jonathon Byrd is a Ph.D. candidate at Carnegie Mellon University's Machine Learning department, where he focuses on Deep Learning, Graph Neural Networks, Survival Analysis, Domain Adaptation, Graph Neural Networks, and Healthcare Applications. His work has been published at top machine learning conferences including NeurIPS and ICML. He has also developed novel ML algorithms and models that are being used in practice today.
