Summary
Joong-ho Won is a Professor of Statistics at Seoul National University with over a decade of academic and research experience spanning high-performance statistical computing, optimization (MM and proximal algorithms), machine learning, and image processing. He progressed through faculty ranks from assistant to full professor at SNU after earlier roles at Korea University, the VA Cooperative Studies Program, and a postdoc at Stanford focusing on large-scale biomedical data. His work blends theory and practical algorithm engineering, emphasizing scalable implementations for computationally intensive statistical methods. Known for translating optimization advances into applied tools, he brings deep expertise in algorithm design for imaging and modern ML workflows. Based in Seoul, he pairs a Stanford PhD pedigree with a sustained record of interdisciplinary collaboration between statistics, engineering, and biomedical domains. Colleagues value his pragmatic approach to making sophisticated algorithms run efficiently on real-world data.
10 years of coding experience
11 years of employment as a software developer
B.S, B.S at Seoul National University
Ph.D, Ph.D at Stanford University