Modeling, identification, and control of a multi-link lightweight manipulator. - Hanqing Zeng (Cuvillier, 1999)

Multiobjective control of a four-link flexible manipulator: a robust H∞ approach. - Zidong Wang 001; Hanqing Zeng; Daniel W. C. Ho; Heinz Unbehauen (IEEE Trans. Control. Syst. Technol., 2002)

Quickly finding a truss in a haystack. - Oded Green; James Fox; Euna Kim; Federico Busato; Nicola Bombieri; Kartik Lakhotia; Shijie Zhou 001; Shreyas G. Singapura; Hanqing Zeng; Rajgopal Kannan; Viktor K. Prasanna; David A. Bader (HPEC, 2017)

Design and implementation of parallel PageRank on multicore platforms. - Shijie Zhou 001; Kartik Lakhotia; Shreyas G. Singapura; Hanqing Zeng; Rajgopal Kannan; Viktor K. Prasanna; James Fox; Euna Kim; Oded Green; David A. Bader (HPEC, 2017)

Fast generation of high throughput customized deep learning accelerators on FPGAs. - Hanqing Zeng; Chi Zhang 022; Viktor K. Prasanna (ReConFig, 2017)

An FPGA framework for edge-centric graph processing. - Shijie Zhou 001; Rajgopal Kannan; Hanqing Zeng; Viktor K. Prasanna (CF, 2018)

A Framework for Generating High Throughput CNN Implementations on FPGAs. - Hanqing Zeng; Ren Chen; Chi Zhang 022; Viktor K. Prasanna (FPGA, 2018)

A Fast and Efficient Parallel Algorithm for Pruned Landmark Labeling. - Qing Dong; Kartik Lakhotia; Hanqing Zeng; Rajgopal Karman; Viktor K. Prasanna; Guna Seetharaman (HPEC, 2018)

Throughput-Optimized Frequency Domain CNN with Fixed-Point Quantization on FPGA. - Weiyi Sun; Hanqing Zeng; Yi-Hua Edward Yang; Viktor K. Prasanna (ReConFig, 2018)

A Flexible Design Automation Tool for Accelerating Quantized Spectral CNNs. - Rachit Rajat; Hanqing Zeng; Viktor K. Prasanna (FPL, 2019)

SPEC2: SPECtral SParsE CNN Accelerator on FPGAs. - Yue Niu 001; Hanqing Zeng; Ajitesh Srivastava; Kartik Lakhotia; Rajgopal Kannan; Yanzhi Wang; Viktor K. Prasanna (HiPC, 2019)

Accurate, Efficient and Scalable Graph Embedding. - Hanqing Zeng; Hongkuan Zhou; Ajitesh Srivastava; Rajgopal Kannan; Viktor K. Prasanna (IPDPS, 2019)

Hardware Acceleration of Large Scale GCN Inference. - Bingyi Zhang; Hanqing Zeng; Viktor K. Prasanna (ASAP, 2020)

Accelerating Large Scale GCN Inference on FPGA. - Bingyi Zhang; Hanqing Zeng; Viktor K. Prasanna (FCCM, 2020)

GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms. - Hanqing Zeng; Viktor K. Prasanna (FPGA, 2020)

GraphSAINT: Graph Sampling Based Inductive Learning Method. - Hanqing Zeng; Hongkuan Zhou; Ajitesh Srivastava; Rajgopal Kannan; Viktor K. Prasanna (ICLR, 2020)

VTR 8: High-performance CAD and Customizable FPGA Architecture Modelling. - Kevin E. Murray; Oleg Petelin; Sheng Zhong; Jia Min Wang; Mohamed Eldafrawy; Jean-Philippe Legault; Eugene Sha; Aaron Graham; Jean Wu; Matthew J. P. Walker; Hanqing Zeng; Panagiotis Patros; et al. (ACM Trans. Reconfigurable Technol. Syst., 2020)

Decoupling the Depth and Scope of Graph Neural Networks. - Hanqing Zeng; Muhan Zhang; Yinglong Xia; Ajitesh Srivastava; Andrey Malevich; Rajgopal Kannan; Viktor K. Prasanna; Long Jin; Ren Chen (NeurIPS, 2021)

Accurate, efficient and scalable training of Graph Neural Networks. - Hanqing Zeng; Hongkuan Zhou; Ajitesh Srivastava; Rajgopal Kannan; Viktor K. Prasanna (J. Parallel Distributed Comput., 2021)

Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. - Hongkuan Zhou; Ajitesh Srivastava; Hanqing Zeng; Rajgopal Kannan; Viktor K. Prasanna (Proc. VLDB Endow., 2021)

DecGNN: A Framework for Mapping Decoupled GNN Models onto CPU-FPGA Heterogeneous Platform. - Bingyi Zhang; Hanqing Zeng; Viktor K. Prasanna (FPGA, 2022)

Input Feature Pruning for Accelerating GNN Inference on Heterogeneous Platforms. - Jason Yik; Sanmukh R. Kuppannagari; Hanqing Zeng; Viktor K. Prasanna (HIPC, 2022)

Low-latency Mini-batch GNN Inference on CPU-FPGA Heterogeneous Platform. - Bingyi Zhang; Hanqing Zeng; Viktor K. Prasanna (HIPC, 2022)

Generative Graph Dictionary Learning. - Zhichen Zeng 001; Ruike Zhu; Yinglong Xia; Hanqing Zeng; Hanghang Tong (ICML, 2023)

An Efficient Distributed Graph Engine for Deep Learning on Graphs. - Gangda Deng; Ömer Faruk Akgül; Hongkuan Zhou; Hanqing Zeng; Yinglong Xia; Jianbo Li; Viktor K. Prasanna (SC Workshops, 2023)

LLM-Rec: Personalized Recommendation via Prompting Large Language Models. - Hanjia Lyu; Song Jiang 002; Hanqing Zeng; Yinglong Xia; Jiebo Luo 001 (CoRR, 2023)

Mixture of Weak & Strong Experts on Graphs. - Hanqing Zeng; Hanjia Lyu; Diyi Hu; Yinglong Xia; Jiebo Luo 001 (CoRR, 2023)

GraphAGILE: An FPGA-Based Overlay Accelerator for Low-Latency GNN Inference. - Bingyi Zhang; Hanqing Zeng; Viktor K. Prasanna (IEEE Trans. Parallel Distributed Syst., 2023)

Mixture of Weak and Strong Experts on Graphs. - Hanqing Zeng; Hanjia Lyu; Diyi Hu; Yinglong Xia; Jiebo Luo 001 (ICLR, 2024)

TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. - Gangda Deng; Hongkuan Zhou; Hanqing Zeng; Yinglong Xia; Christopher Leung; Jianbo Li; Rajgopal Kannan; Viktor K. Prasanna (IPDPS, 2024)

LLM-Rec: Personalized Recommendation via Prompting Large Language Models. - Hanjia Lyu; Song Jiang 002; Hanqing Zeng; Yinglong Xia; Qifan Wang 001; Si Zhang; Ren Chen; Christopher Leung; Jiajie Tang; Jiebo Luo 001 (NAACL-HLT (Findings), 2024)

Retrieval Augmentation via User Interest Clustering. - Hanjia Lyu; Hanqing Zeng; Yinglong Xia; Ren Chen; Jiebo Luo 001 (CoRR, 2024)

Language Models are Graph Learners. - Zhe Xu 007; Kaveh Hassani; Si Zhang; Hanqing Zeng; Michihiro Yasunaga; Limei Wang; Dongqi Fu; Ning Yao; Bo Long; Hanghang Tong (CoRR, 2024)

On the Equivalence of Graph Convolution and Mixup. - Xiaotian Han; Hanqing Zeng; Yu Chen 022; Shaoliang Nie; Jingzhou Liu; Kanika Narang; Zahra Shakeri; Karthik Abinav Sankararaman; Song Jiang 002; Madian Khabsa; Qifan Wang 001; Xia Hu 001 (Trans. Mach. Learn. Res., 2024)

S'MoRE: Structural Mixture of Residual Experts for LLM Fine-tuning. - Hanqing Zeng; Yinglong Xia; Zhuokai Zhao; Gilbert Jiang; Qiang Zhang; Jiayi Liu; Lizhu Zhang; Xiangjun Fan; Benyu Zhang (CoRR, 2025)