Currently at Apple, I work as a Machine Learning Engineer on data-centric AI for multimodal foundation models. With 7+ years of experience across academia and industry, my focus has been on building AI/ML systems where robustness, generalization, and strong performance come from the data itself.

Previously at Inocras, I led AI/ML efforts in genomics — developing genomic foundation models, minimal residual disease (ctDNA) detection (JCO 2025), and large-scale cloud/HPC optimizations.

During my PhD at KAIST, I created BWA-MEME (Oxford Bioinformatics 2022), a high-speed genomic data preprocessing tool now in production worldwide; developed semi-supervised and domain adaptation frameworks for deep variant callers; and built LiveNAS (SIGCOMM 2020), an online-learning super-resolution deep learning system for live video.

Over the years, I have worked across diverse domains, including AI-enhanced video delivery systems, data center networking, genomics data preprocessing software, and now, large-scale multimodal foundation models.

Keywords: Deep-learning and Machine-learning, Generative AI, High-performance network systems