Summary
Xi Han is a Research Assistant and PhD candidate in Computer Science with eight years of experience specializing in GPU algorithms and AI workload efficiency optimization. Based at Stony Brook University, Xi has published at top venues like ICML and CVPR for work on neural PDE solvers, PDE-driven foundation models (e.g., Mamba), and computer graphics. Their hands-on systems expertise spans CUDA kernel fusing, PyTorch CUDA extensions, and performance profiling to accelerate training and inference. Earlier roles include deploying and optimizing MobileNet on iOS with CoreML and building CNN-based 3D face reconstruction pipelines, reflecting a blend of research depth and production-minded engineering. Notably, Xi combines mathematical rigor from a strong PhD record (3.9/4.0) with practical optimization wins that measurably improve model speed and accuracy.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science, 3.3/4.0, Bachelor of Engineering - BE, Computer Science, 3.3/4.0 at Tsinghua University
Doctor of Philosophy - PhD, Computer Science, 3.9/4.0, Doctor of Philosophy - PhD, Computer Science, 3.9/4.0 at Stony Brook University
English, Japanese, Chinese