Summary
Jaehoon Koo is an Assistant Professor at Hanyang University ERICA and a Northwestern PhD-trained researcher specializing in machine learning, deep learning, and autotuning for high-performance computing and imaging. He has translated academic research into impactful engineering results—e.g., a Pytorch MLP/CNN that reconstructed plasma equilibria with a 1000x speedup and autotuners that delivered multi-fold performance gains on exascale proxy apps. With 9+ years of Python experience across PyTorch, TensorFlow, Gym, and scikit-learn and 7+ years working on real-world image and text datasets, he bridges theory and practice in ML modeling (CNN, RNN, RL, BO) and surrogate-assisted optimization. His background includes cross-disciplinary collaborations with plasma, X‑ray, and materials scientists and contributions to ML-based autotuning tools (Ytopt) used in HPC packaging ecosystems. Based in Seoul, he combines rigorous industrial engineering training with hands-on systems work, often focusing on latency-sensitive and online autotuning applications.
6 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Industrial Engineering and Management Sciences, Doctor of Philosophy - PhD, Industrial Engineering and Management Sciences at Northwestern University
Bachelor of Science - BS, Industrial Engineering, Bachelor of Science - BS, Industrial Engineering at Ajou University
Master of Science - MS, Industrial Engineering, Master of Science - MS, Industrial Engineering at Korea Advanced Institute of Science and Technology