Younghyun Cho

Younghyun Cho is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University (SCU), leading the Systems & Performance Research Lab. He holds a Ph.D. from Seoul National University (2020) and previously served as a Postdoctoral Scholar at UC Berkeley. His research focuses on compiler/runtime-level performance optimizations, autotuning for high-performance computing (HPC), and emerging workloads such as quantum computing and machine learning. Key contributions include GPTune, a Bayesian optimization-based autotuning framework, and Dopia, an online parallelism management system for heterogeneous architectures.

Education: Ph.D., Seoul National University, Electrical Engineering and Computer Science (2020). Research highlights include non-smooth Bayesian optimization for scientific applications and surrogate-based autotuning for randomized sketching algorithms. He has authored over 20 peer-reviewed publications in top venues like DAC, IPDPS, and SIAM Journal on Matrix Analysis.

Awards include the SCU AI Scholarship Award (2025), Seoul National University's Excellence Research Award (2019), and a 2016 Open Source Software World Challenge prize for the SnuMAP profiler. He actively serves on program committees for PACT, LCTES, and IPDPS, and manages grants including AMD HPC Cloud resources (2025-2026).