Zhekai Zhang is a fourth-year Ph.D. student at MIT EECS advised by Professor Song Han. His research focuses on the development of high-performance and efficient hardware architectures for sparse linear algebra and deep learning. Zhekai has published several papers in the field of computer architecture, which have received over 250 citations. Some of his notable contributions include SpArch, an accelerator for sparse matrix multiplication presented at HPCA 2020; SpAtten, a hardware architecture for efficient natural language processing presented at HPCA 2021, and PointAcc, a hardware accelerator for 3D point-cloud neural networks presented at MICRO 2021. Zhekai also leads the FPGA implementation of Once-for-All network, which was presented at ICLR 2020, and has won first place in the Low-Power Computer Vision Challenge 2020 and 2021 in the FPGA track.