Summary
Kyurae Kim is a PhD student at the University of Pennsylvania with a decade of hands-on experience bridging probabilistic machine learning, Bayesian inference, and high-performance computing. His work spans stochastic optimization, signal processing, and computational statistics, with applied projects from medical imaging and sonar to embedded ultrasound firmware and GPU-accelerated cluster scheduling. Comfortable in C/C++, Julia, Python, MATLAB, CUDA and VHDL, he combines low-level systems design (FPGA/firmware) with scalable parallel algorithms and probabilistic modeling. Past roles include research at Sogang University, the University of Liverpool, and a Genentech internship, and he has contributed to GCC/OpenMP tooling and published practical advances in Bayesian optimization for scheduling and medical image enhancement. Notably, his background blends hardware development for instruments like mass spectrometers with modern Bayesian methods, revealing a rare cross-domain fluency between physical systems and statistical computation.
9 years of coding experience
4 years of employment as a software developer
학사 전자공학, 학사 전자공학 at Sogang University
Doctor of Philosophy - PhD Computer and Information Science, Doctor of Philosophy - PhD Computer and Information Science at University of Pennsylvania
English, French, Korean