Mask-Net: A Hardware-efficient Object Detection Network with Masked Region Proposals. - Hanqiu Chen; Cong Hao (ASAP, 2022)

Bottleneck Analysis of Dynamic Graph Neural Network Inference on CPU and GPU. - Hanqiu Chen; Yahya Alhinai; Yihan Jiang; Eunjee Na; Cong Hao (IISWC, 2022)

DGNN-Booster: A Generic FPGA Accelerator Framework For Dynamic Graph Neural Network Inference. - Hanqiu Chen; Cong Hao (FCCM, 2023)

Hardware/Software Co-design for Machine Learning Accelerators. - Hanqiu Chen; Cong Hao (FCCM, 2023)

Rapid-INR: Storage Efficient CPU-Free DNN Training Using Implicit Neural Representation. - Hanqiu Chen; Hang Yang; Stephen B. R. Fitzmeyer; Cong Hao (ICCAD, 2023)

ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model. - Hanqiu Chen; Yitu Wang; Luis Vitório Cargnini; Mohammadreza Soltaniyeh; Dongyang Li; Gongjin Sun; Pradeep Subedi; Andrew Chang; Yiran Chen 001; Cong Hao (DAC, 2024)

Residual-INR: Communication Efficient On-Device Learning Using Implicit Neural Representation. - Hanqiu Chen; Xuebin Yao; Pradeep Subedi; Cong Hao (ICCAD, 2024)

HLSFactory: A Framework Empowering High-Level Synthesis Datasets for Machine Learning and Beyond. - Stefan Abi-Karam; Rishov Sarkar; Allison Seigler; Sean Lowe; Zhigang Wei; Hanqiu Chen; Nanditha Rao; Lizy Kurian John; Aman Arora 001; Cong Hao (MLCAD, 2024)

Survey of Machine Learning for Software-assisted Hardware Design Verification: Past, Present, and Prospect. - Nan Wu; Yingjie Li; Hang Yang; Hanqiu Chen; Steve Dai; Cong Hao; Cunxi Yu; Yuan Xie 001 (ACM Trans. Design Autom. Electr. Syst., 2024)

ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools. - Andy Wanna; Hanqiu Chen; Cong Hao (CoRR, 2025)