52.5 TOPS/W 1.7GHz Reconfigurable XGBoost Inference Accelerator Based on Modular-Unit-Tree with Dynamic Data and Compute Gating. - Chang Eun Song; Yidong Li; Amardeep Ramnani; Pulkit Agrawal 003; Purvi Agrawal; Sung-Joon Jang; Sang-Seol Lee; Tajana Rosing; Mingu Kang (CICC, 2024)

Efficient Transformer Acceleration via Reconfiguration for Encoder and Decoder Models and Sparsity-Aware Algorithm Mapping. - Chang Eun Song; Ashkan Moradifirouzabadi; Tajana Rosing; Mingu Kang (ISLPED, 2024)

FSL-HDnn: A 5.7 TOPS/W End-to-end Few-shot Learning Classifier Accelerator with Feature Extraction and Hyperdimensional Computing. - Haichao Yang; Chang Eun Song; Weihong Xu; Behnam Khaleghi; Uday Mallappa; Monil Shah; Keming Fan; Mingu Kang; Tajana Rosing (CoRR, 2024)

Hybrid SLC-MLC RRAM Mixed-Signal Processing-in-Memory Architecture for Transformer Acceleration via Gradient Redistribution. - Chang Eun Song; Priyansh Bhatnagar; Zihan Xia; Nam Sung Kim; Tajana Rosing; Mingu Kang (ISCA, 2025)

Clo-HDnn: A 4.66 TFLOPS/W and 3.78 TOPS/W Continual On-Device Learning Accelerator with Energy-efficient Hyperdimensional Computing via Progressive Search. - Chang Eun Song; Weihong Xu; Keming Fan; Soumil Jain; Gopabandhu Hota; Haichao Yang; Leo Liu; Kerem Akarvardar; Meng-Fan Chang; Carlos H. Diaz; Gert Cauwenberghs; Tajana Rosing; et al. (CoRR, 2025)