PhD Student
Department of Computer Science
Stanford University
Office: 464 Gates
zgh23 [at] stanford [dot] edu
Curriculum Vitae

I am a computer science PhD student at Stanford University advised by Professor Kunle Olukotun. I also worked with Professor Fredrik Kjolstad on sparse tensor algebra compilation and Professor Azalia Mirhoseini on efficient sparse large language models.

Research: My research interests lie in better programming models and systems for domain-specific architectures. I am also interested in optimizing GPU kernels for emerging applications, including sparse and recurrent neural networks.

I graduated from Tsinghua University in 2023 with a bachelor degree in Eletronic Engineering. At Tsinghua, I did research at NICS-EFC Lab on effcient sparse tensor algebra for GPU and IDEAL Lab on kernel architecture search.

Selected Publications

Adaptive Self-improvement LLM Agentic System for ML Library Development
Genghan Zhang, Weixin Liang, Olivia Hsu, and Kunle Olukotun
ICLR 2025 Workshop on Reasoning and Planning for Large Language Models; ICLR 2025 DL4C Workshop, May 2025
ICLR 2025 DL4C Workshop Best Paper Award (2/63)
pdf
Compilation of Modular and General Sparse Workspaces
Genghan Zhang, Olivia Hsu, and Fredrik Kjolstad
Conference on Programming Language Design and Implementation (PLDI), June 2024
pdf youtube
Sgap: Towards Efficient Sparse Tensor Algebra Compilation for GPU
Genghan Zhang, Yuetong Zhao, Yanting Tao, Zhongming Yu, Guohao Dai, Sitao Huang, Yuan Wen, Pavlos Petoumenos, and Yu Wang
CCF Transactions on High Performance Computing, 2023
pdf
CATS: Context-Aware Thresholding for Sparsity in Large Language Models
Donghyun Lee, Jeyong Lee, Genghan Zhang, Mo Tiwari, and Azalia Mirhoseini
First Conference on Language Modeling, October 2024
pdf

Blogs

Adaptive Self-improvement LLM Agentic System for ML Library Development
Genghan Zhang , Weixin Liang , Olivia Hsu , and Kunle Olukotun
March 01, 2025