Summary
Janghaeng Lee is a Senior Staff Software Engineer with nine years of experience specializing in hardware-software codesign, compiler support for parallel architectures and accelerators, and managed runtime performance tuning. Based in Seoul and currently at Intel, he leads end-to-end deep learning software performance optimization for large-scale GPU systems, applying low-level skills in C/C++, gdb, LLVM, and simulation. His background spans academia and industry—from PhD research on CPU/GPU heterogeneous optimizations and runtime systems at the University of Michigan to production work on custom ISAs, dynamic instrumentation for ARM, and multicore binary translation. He has a track record of bridging research and product engineering, turning static/dynamic compiler techniques into practical performance wins on real hardware. Known for pragmatic scripting and tooling (bash/python) to accelerate debugging and profiling, he brings a rare combination of compiler internals and system-level performance engineering. An inquisitive engineer with a concise "Hello! World!" GitHub presence, he often surfaces subtle cross-layer bottlenecks that others miss.
9 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of Michigan
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at Georgia Institute of Technology