Seonjin Na

I’m a Senior High Performance AI Engineer at NVIDIA, accelerating AI workloads on NVIDIA GPUs through GPU architecture and full-stack software optimization. I focus on accelerating distributed AI training/inference for LLMs and multi-modal models through GPU-centric runtimes and system-level solutions.

Prior to joining NVIDIA, I was a Postdoctoral Fellow in the HPArch Group at Georgia Institute of Technology, supervised by Prof. Hyesoon Kim. I received my Ph.D. from the School of Computing at KAIST in 2023, advised by Prof. Jaehyuk Huh.

My research interests lie in GPU architecture, trusted computing, heterogeneous systems, distributed computing, and systems for machine learning. During my Ph.D., I focused on building secure architectures to provide trusted execution environments (TEE) on accelerators such as GPUs and NPUs with minimal performance overhead. Currently, I am actively engaged in expanding my research to address various challenges in multi-GPU architecture, hardware security, and accelerating large language models (LLMs).

Research Interest (Keyword): GPU/NPU Architecture, Secure Architecture for GPU/NPU, Systems for Machine Learning.