HybridDNN: A Framework for High-Performance Hybrid DNN Accelerator Design and Implementation. - Hanchen Ye; Xiaofan Zhang 001; Zhize Huang; Gengsheng Chen; Deming Chen (DAC, 2020)

DNNExplorer: A Framework for Modeling and Exploring a Novel Paradigm of FPGA-based DNN Accelerator. - Xiaofan Zhang 001; Hanchen Ye; Junsong Wang; Yonghua Lin; Jinjun Xiong; Wen-Mei Hwu; Deming Chen (ICCAD, 2020)

Being-ahead: Benchmarking and Exploring Accelerators for Hardware-Efficient AI Deployment. - Xiaofan Zhang 001; Hanchen Ye; Deming Chen (CoRR, 2021)

ScaleHLS: Scalable High-Level Synthesis through MLIR. - Hanchen Ye; Cong Hao; Jianyi Cheng; Hyunmin Jeong; Jack Huang; Stephen Neuendorffer; Deming Chen (CoRR, 2021)

ScaleHLS: a scalable high-level synthesis framework with multi-level transformations and optimizations: invited. - Hanchen Ye; HyeGang Jun; Hyunmin Jeong; Stephen Neuendorffer; Deming Chen (DAC, 2022)

ScaleHLS: A New Scalable High-Level Synthesis Framework on Multi-Level Intermediate Representation. - Hanchen Ye; Cong Hao; Jianyi Cheng; Hyunmin Jeong; Jack Huang; Stephen Neuendorffer; Deming Chen (HPCA, 2022)

CHARM: Composing Heterogeneous AcceleRators for Matrix Multiply on Versal ACAP Architecture. - Jinming Zhuang; Jason Lau; Hanchen Ye; Zhuoping Yang; Yubo Du; Jack Lo; Kristof Denolf; Stephen Neuendorffer; Alex K. Jones; Jingtong Hu; Deming Chen; Jason Cong; et al. (FPGA, 2023)

High-level Synthesis for Domain Specific Computing. - Hanchen Ye; HyeGang Jun; Jin Yang 006; Deming Chen (ISPD, 2023)

AutoScaleDSE: A Scalable Design Space Exploration Engine for High-Level Synthesis. - HyeGang Jun; Hanchen Ye; Hyunmin Jeong; Deming Chen (ACM Trans. Reconfigurable Technol. Syst., 2023)

Invited Paper: Software/Hardware Co-design for LLM and Its Application for Design Verification. - Lily Jiaxin Wan; Yingbing Huang; Yuhong Li; Hanchen Ye; Jinghua Wang; Xiaofan Zhang 001; Deming Chen (ASPDAC, 2024)

HIDA: A Hierarchical Dataflow Compiler for High-Level Synthesis. - Hanchen Ye; Hyegang Jun; Deming Chen (ASPLOS (1), 2024)

Invited: New Solutions on LLM Acceleration, Optimization, and Application. - Yingbing Huang; Lily Jiaxin Wan; Hanchen Ye; Manvi Jha; Jinghua Wang; Yuhong Li; Xiaofan Zhang 001; Deming Chen (DAC, 2024)

Subgraph Extraction-Based Feedback-Guided Iterative Scheduling for HLS. - Hanchen Ye; David Z. Pan; Chris Leary; Deming Chen; Xiaoqing Xu (DATE, 2024)

SnapKV: LLM Knows What You are Looking for Before Generation. - Yuhong Li; Yingbing Huang; Bowen Yang; Bharat Venkitesh; Acyr Locatelli; Hanchen Ye; Tianle Cai; Patrick Lewis 002; Deming Chen (NeurIPS, 2024)

New Solutions on LLM Acceleration, Optimization, and Application. - Yingbing Huang; Lily Jiaxin Wan; Hanchen Ye; Manvi Jha; Jinghua Wang; Yuhong Li; Xiaofan Zhang 001; Deming Chen (CoRR, 2024)

CHARM 2.0: Composing Heterogeneous Accelerators for Deep Learning on Versal ACAP Architecture. - Jinming Zhuang; Jason Lau; Hanchen Ye; Zhuoping Yang; Shixin Ji; Jack Lo; Kristof Denolf; Stephen Neuendorffer; Alex K. Jones; Jingtong Hu; Yiyu Shi 001; Deming Chen; et al. (ACM Trans. Reconfigurable Technol. Syst., 2024)

Unsupervised perturbation based self-supervised federated adversarial training. - Yuyue Zhang; Hanchen Ye; Xiaoli Zhao (Appl. Intell., 2025)

MLCD: Machine Learning-Based Code Version and Device Selection for Heterogeneous Systems. - Kaiwen Cao; Hanchen Ye; Yihan Pang; Deming Chen (IEEE Trans. Computers, 2025)