Hojae Son, UMass PhD Student, Supports GPU Computing to Advance AI Research

Hojae Son, a PhD student at the University of Massachusetts Amherst advised under Marco Serafini, has found his passion in software design and general testing. His current research involves systems for machine learning and distributed systems. In his free time, he enjoys listening to music and watching EFL soccer games. Hojae previously worked at an industrial research group developing AI SDK.

Now, Hojae is a joint research facilitator for Research Computing & Data and Center for Data Science. His daily work focuses on facilitating workflow execution on Unity, where he supports machine learning researchers by setting up multi-node AI training environments. 

With expertise in multi-node GPU training, Hojae is integral to helping research groups leverage UMass’ highest-powered GPU resource: the A100 superpod.