Self-map building in wireless sensor network based on TDOA measurements. - Shuanglong Liu; Yuchao Tang; Chun Zhang; Shigang Yue (MFI, 2012)

Parallel resampling for particle filters on FPGAs. - Shuanglong Liu; Grigorios Mingas; Christos-Savvas Bouganis (FPT, 2014)

An exact MCMC accelerator under custom precision regimes. - Shuanglong Liu; Grigorios Mingas; Christos-Savvas Bouganis (FPT, 2015)

Stacked Auto-Encoders for Feature Extraction with Neural Networks. - Shuanglong Liu; Chao Zhang; Jinwen Ma (BIC-TA (1), 2016)

Stock Price Prediction Through the Mixture of Gaussian Processes via the Precise Hard-cut EM Algorithm. - Shuanglong Liu; Jinwen Ma (ICIC (3), 2016)

Communication-Aware MCMC Method for Big Data Applications on FPGAs. - Shuanglong Liu; Christos-Savvas Bouganis (FCCM, 2017)

Reconfigurable acceleration of genetic sequence alignment: A survey of two decades of efforts. - Ho-Cheung Ng; Shuanglong Liu; Wayne Luk (FPL, 2017)

CNN-LSTM Neural Network Model for Quantitative Strategy Analysis in Stock Markets. - Shuanglong Liu; Chao Zhang; Jinwen Ma (ICONIP (2), 2017)

An Unbiased MCMC FPGA-Based Accelerator in the Land of Custom Precision Arithmetic. - Shuanglong Liu; Grigorios Mingas; Christos-Savvas Bouganis (IEEE Trans. Computers, 2017)

Acceleration of MCMC-based algorithms using reconfigurable logic. - Shuanglong Liu (2017)

Hardware Compilation of Deep Neural Networks: An Overview. - Ruizhe Zhao; Shuanglong Liu; Ho-Cheung Ng; Erwei Wang; James J. Davis 001; Xinyu Niu; Xiwei Wang; Huifeng Shi; George A. Constantinides; Peter Y. K. Cheung; Wayne Luk (ASAP, 2018)

A Low-Power Deconvolutional Accelerator for Convolutional Neural Network Based Segmentation on FPGA: Abstract Only. - Shuanglong Liu; Xinyu Niu; Wayne Luk (FPGA, 2018)

ADAM: Automated Design Analysis and Merging for Speeding up FPGA Development. - Ho-Cheung Ng; Shuanglong Liu; Wayne Luk (FPGA, 2018)

Reconfigurable Acceleration of 3D-CNNs for Human Action Recognition with Block Floating-Point Representation. - Hongxiang Fan; Ho-Cheung Ng; Shuanglong Liu; Zhiqiang Que; Xinyu Niu; Wayne Luk (FPL, 2018)

A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA. - Hongxiang Fan; Shuanglong Liu; Martin Ferianc; Ho-Cheung Ng; Zhiqiang Que; Shen Liu; Xinyu Niu; Wayne Luk (FPT, 2018)

Memory-Efficient Architecture for Accelerating Generative Networks on FPGA. - Shuanglong Liu; Chenglong Zeng; Hongxiang Fan; Ho-Cheung Ng; Jiuxi Meng; Zhiqiang Que; Xinyu Niu; Wayne Luk (FPT, 2018)

Optimizing CNN-based Segmentation with Deeply Customized Convolutional and Deconvolutional Architectures on FPGA. - Shuanglong Liu; Hongxiang Fan; Xinyu Niu; Ho-Cheung Ng; Yang Chu; Wayne Luk (ACM Trans. Reconfigurable Technol. Syst., 2018)

Optimizing CNN-Based Hyperspectral Image Classification on FPGAs. - Shuanglong Liu; Ringo S. W. Chu; Xiwei Wang; Wayne Luk (ARC, 2019)

F-E3D: FPGA-based Acceleration of an Efficient 3D Convolutional Neural Network for Human Action Recognition. - Hongxiang Fan; Cheng Luo; Chenglong Zeng; Martin Ferianc; Zhiqiang Que; Shuanglong Liu; Xinyu Niu; Wayne Luk (ASAP, 2019)

Efficient Weight Reuse for Large LSTMs. - Zhiqiang Que; Thomas Nugent; Shuanglong Liu; Li Tian; Xinyu Niu; Yongxin Zhu 001; Wayne Luk (ASAP, 2019)

Towards Efficient Deep Neural Network Training by FPGA-Based Batch-Level Parallelism. - Cheng Luo; Man-Kit Sit; Hongxiang Fan; Shuanglong Liu; Wayne Luk; Ce Guo (FCCM, 2019)

Towards an Efficient Accelerator for DNN-Based Remote Sensing Image Segmentation on FPGAs. - Shuanglong Liu; Wayne Luk (FPL, 2019)

Optimizing CNN-based Hyperspectral ImageClassification on FPGAs. - Shuanglong Liu; Ringo S. W. Chu; Xiwei Wang; Wayne Luk (CoRR, 2019)

Optimizing FPGA-Based CNN Accelerator Using Differentiable Neural Architecture Search. - Hongxiang Fan; Martin Ferianc; Shuanglong Liu; Zhiqiang Que; Xinyu Niu; Wayne Luk (ICCD, 2020)

Optimizing Fully Spectral Convolutional Neural Networks on FPGA. - Shuanglong Liu; Wayne Luk (FPT, 2020)

Acceleration of Short Read Alignment with Runtime Reconfiguration. - Ho-Cheung Ng; Shuanglong Liu; Izaak Coleman; Ringo S. W. Chu; Man-Chung Yue; Wayne Luk (FPT, 2020)

Accelerating Fully Spectral CNNs with Adaptive Activation Functions on FPGA. - Shuanglong Liu; Hongxiang Fan; Wayne Luk (DATE, 2021)

Reconfigurable Acceleration of Short Read Mapping with Biological Consideration. - Ho-Cheung Ng; Izaak Coleman; Shuanglong Liu; Wayne Luk (FPGA, 2021)

Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. - Hongxiang Fan; Martin Ferianc; Zhiqiang Que; He Li 008; Shuanglong Liu; Xinyu Niu; Wayne Luk (ASP-DAC, 2022)

FPGA-Based Acceleration for Bayesian Convolutional Neural Networks. - Hongxiang Fan; Martin Ferianc; Zhiqiang Que; Shuanglong Liu; Xinyu Niu; Miguel R. D. Rodrigues; Wayne Luk (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs. - Shuanglong Liu; Hongxiang Fan; Martin Ferianc; Xinyu Niu; Huifeng Shi; Wayne Luk (IEEE Trans. Neural Networks Learn. Syst., 2022)

High-Performance Acceleration of 2-D and 3-D CNNs on FPGAs Using Static Block Floating Point. - Hongxiang Fan; Shuanglong Liu; Zhiqiang Que; Xinyu Niu; Wayne Luk (IEEE Trans. Neural Networks Learn. Syst., 2023)

Enhancing Dropout-based Bayesian Neural Networks with Multi-Exit on FPGA. - Hao Mark Chen; Liam Castelli; Martin Ferianc; Hongyu Zhou; Shuanglong Liu; Wayne Luk; Hongxiang Fan (CoRR, 2024)

Design of Fully Spectral CNNs for Efficient FPGA-Based Acceleration. - Shuanglong Liu; Hongxiang Fan; Wayne Luk (IEEE Trans. Neural Networks Learn. Syst., 2024)

FPGA-Based Acceleration of MCMC Algorithm through Self-Shrinking for Big Data. - Shuanglong Liu; Shiyu Peng; Wan Shen (DATE, 2025)

Efficient CORDIC-Based Activation Functions for RNN Acceleration on FPGAs. - Shen Wan; Junye Jiang; Minghan Li; Shuanglong Liu (IEEE Trans. Artif. Intell., 2025)

DCP-CNN: Efficient Acceleration of CNNs With Dynamic Computing Parallelism on FPGA. - Kui Dai; Zheren Xie; Shuanglong Liu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review. - Junye Jiang; Yaan Zhou; Yuanhao Gong; Haoxuan Yuan; Shuanglong Liu (CoRR, 2025)