Genesis: A Hardware Acceleration Framework for Genomic Data Analysis. - Tae Jun Ham; David Bruns-Smith; Brendan Sweeney; Yejin Lee 001; Seong Hoon Seo; U. Gyeong Song; Young H. Oh; Krste Asanovic; Jae W. Lee; Lisa Wu Wills (ISCA, 2020)

MERCI: efficient embedding reduction on commodity hardware via sub-query memoization. - Yejin Lee 001; Seong Hoon Seo; Hyunji Choi; Hyoung Uk Sul; Soosung Kim 001; Jae W. Lee; Tae Jun Ham (ASPLOS, 2021)

ELSA: Hardware-Software Co-design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks. - Tae Jun Ham; Yejin Lee 001; Seong Hoon Seo; Soosung Kim 001; Hyunji Choi; Sung Jun Jung; Jae W. Lee (ISCA, 2021)

Accelerating Genomic Data Analytics With Composable Hardware Acceleration Framework. - Tae Jun Ham; Yejin Lee 001; Seong Hoon Seo; U. Gyeong Song; Jae W. Lee; David Bruns-Smith; Brendan Sweeney; Krste Asanovic; Young H. Oh; Lisa Wu Wills (IEEE Micro, 2021)

A 40nm 5.6TOPS/W 239GOPS/mm2 Self-Attention Processor with Sign Random Projection-based Approximation. - Seong Hoon Seo; Soosung Kim 001; Sung Jun Jung; Sangwoo Kwon; Hyunseung Lee 001; Jae W. Lee (ESSCIRC, 2022)

FACIL: Flexible DRAM Address Mapping for SoC-PIM Cooperative On-device LLM Inference. - Seong Hoon Seo; Junghoon Kim; Donghyun Lee 005; Seonah Yoo; Seokwon Moon; Yeonhong Park; Jae W. Lee (HPCA, 2025)