Molecular Modeling of the 3D Structure of 5-HT1AR: Discovery of Novel 5-HT1AR Agonists via Dynamic Pharmacophore-Based Virtual Screening. - Lili Xu; Shanglin Zhou; Kunqian Yu; Bo Gao; Hualiang Jiang; Xuechu Zhen; Wei Fu (J. Chem. Inf. Model., 2013)

JUMP: A Fast Deterministic Algorithm to Find the Closest Pair of Subsequences. - Xingyu Cai; Shanglin Zhou; Sanguthevar Rajasekaran (SDM, 2018)

An Efficient Deep Reinforcement Learning Framework for UAVs. - Shanglin Zhou; Bingbing Li; Caiwu Ding; Lu Lu 003; Caiwen Ding (ISQED, 2020)

A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods. - Tianyun Zhang; Xiaolong Ma; Zheng Zhan 001; Shanglin Zhou; Minghai Qin; Fei Sun; Yen-Kuang Chen; Caiwen Ding; Makan Fardad; Yanzhi Wang (CoRR, 2020)

MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks. - Yijue Wang; Chenghong Wang; Zigeng Wang; Shanglin Zhou; Hang Liu 001; Jinbo Bi; Caiwen Ding; Sanguthevar Rajasekaran (CoRR, 2020)

A Surrogate Lagrangian Relaxation-based Model Compression for Deep Neural Networks. - Deniz Gurevin; Shanglin Zhou; Lynn Pepin; Bingbing Li; Mikhail A. Bragin; Caiwen Ding; Fei Miao (CoRR, 2020)

Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (ASAP, 2021)

A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. - Tianyun Zhang; Xiaolong Ma; Zheng Zhan 001; Shanglin Zhou; Caiwen Ding; Makan Fardad; Yanzhi Wang (DAC, 2021)

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs: (Invited Paper). - Zhepeng Wang 001; Zhiding Liang; Shanglin Zhou; Caiwen Ding; Yiyu Shi 001; Weiwen Jiang (ICCAD, 2021)

Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation. - Deniz Gurevin; Mikhail A. Bragin; Caiwen Ding; Shanglin Zhou; Lynn Pepin; Bingbing Li; Fei Miao (IJCAI, 2021)

Against Membership Inference Attack: Pruning is All You Need. - Yijue Wang; Chenghong Wang; Zigeng Wang; Shanglin Zhou; Hang Liu 001; Jinbo Bi; Caiwen Ding; Sanguthevar Rajasekaran (IJCAI, 2021)

An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving. - Shanglin Zhou; Mimi Xie; Yufang Jin; Fei Miao; Caiwen Ding (ISQED, 2021)

Application of Hidden Markov Models to Analyze, Group and Visualize Spatio-Temporal COVID-19 Data. - Shanglin Zhou; Paolo Braca; Stefano Maranò 001; Peter Willett 001; Leonardo Maria Millefiori; Domenico Gaglione; Krishna R. Pattipati (IEEE Access, 2021)

Binary Complex Neural Network Acceleration on FPGA. - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs. - Zhepeng Wang 001; Zhiding Liang; Shanglin Zhou; Caiwen Ding; Jinjun Xiong; Yiyu Shi 001; Weiwen Jiang (CoRR, 2021)

Enabling Super-Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. - Sahidul Islam; Jieren Deng; Shanglin Zhou; Chen Pan; Caiwen Ding; Mimi Xie (CoRR, 2021)

Poster: Cryptographic Inferences for Video Deep Neural Networks. - Bingyu Liu; Rujia Wang; Zhongjie Ba; Shanglin Zhou; Caiwen Ding; Yuan Hong 001 (CCS, 2022)

Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. - Sahidul Islam; Jieren Deng; Shanglin Zhou; Chen Pan; Caiwen Ding; Mimi Xie (DATE, 2022)

EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System. - Sahidul Islam; Shanglin Zhou; Ran Ran; Yufang Jin; Wujie Wen; Caiwen Ding; Mimi Xie (ICCAD, 2022)

On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond. - Zhirui Hu; Jinyang Li 001; Zhenyu Pan; Shanglin Zhou; Lei Yang 018; Caiwen Ding; Omer Khan; Tong Geng; Weiwen Jiang (ICCD, 2022)

An Intermittent OTA Approach to Update the DL Weights on Energy Harvesting Devices. - Wei Wei 060; Sahidul Islam; Jishnu Banerjee; Shanglin Zhou; Chen Pan; Caiwen Ding; Mimi Xie (ISQED, 2022)

Combining multi-view ensemble and surrogate lagrangian relaxation for real-time 3D biomedical image segmentation on the edge. - Shanglin Zhou; Xiaowei Xu 004; Jun Bai; Mikhail A. Bragin (Neurocomputing, 2022)

Encoding time in neural dynamic regimes with distinct computational tradeoffs. - Shanglin Zhou; Sotiris C. Masmanidis; Dean V. Buonomano (PLoS Comput. Biol., 2022)

PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. - Hongwu Peng; Shanglin Zhou; Yukui Luo; Nuo Xu; Shijin Duan; Ran Ran; Jiahui Zhao; Chenghong Wang; Tong Geng; Wujie Wen; Xiaolin Xu 001; Caiwen Ding (DAC, 2023)

Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. - Shanglin Zhou; Yingjie Li; Minhan Lou; Weilu Gao; Zhijie Shi; Cunxi Yu; Caiwen Ding (DAC, 2023)

A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller. - Ya-sine Agrignan; Shanglin Zhou; Jun Bai; Sahidul Islam; Sheida Nabavi; Mimi Xie; Caiwen Ding (ISQED, 2023)

RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference. - Hongwu Peng; Shanglin Zhou; Yukui Luo; Nuo Xu; Shijin Duan; Ran Ran; Jiahui Zhao; Shaoyi Huang; Xi Xie; Chenghong Wang; Tong Geng; Wujie Wen; et al. (CoRR, 2023)

Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles. - Songyang Han; Shanglin Zhou; Lynn Pepin; Jiangwei Wang; Caiwen Ding; Fei Miao (CoRR, 2023)

Surrogate Lagrangian Relaxation: A Path to Retrain-Free Deep Neural Network Pruning. - Shanglin Zhou; Mikhail A. Bragin; Deniz Gurevin; Lynn Pepin; Fei Miao; Caiwen Ding (ACM Trans. Design Autom. Electr. Syst., 2023)

Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques. - Hee-Seung Kim; Shanglin Zhou; Adam Bienkowski; Krishna R. Pattipati (Zenodo, 2023)

Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques. - Hee-Seung Kim; Shanglin Zhou; Adam Bienkowski; Krishna R. Pattipati (Zenodo, 2023)

A Multi-Agent Reinforcement Learning Approach for Safe and Efficient Behavior Planning of Connected Autonomous Vehicles. - Songyang Han; Shanglin Zhou; Jiangwei Wang; Lynn Pepin; Caiwen Ding; Jie Fu 002; Fei Miao (IEEE Trans. Intell. Transp. Syst., 2024)

Secure and Efficient Video Inferences with Compressed 3-Dimensional Deep Neural Networks. - Bingyu Liu; Ali Arastehfard; Rujia Wang; Weiran Liu; Zhongjie Ba; Shanglin Zhou; Yuan Hong 001 (CODASPY, 2025)

A unified DNN weight compression framework using reweighted optimization methods. - Mengchen Fan; Tianyun Zhang; Xiaolong Ma; Jiacheng Guo; Zheng Zhan 001; Shanglin Zhou; Minghai Qin; Caiwen Ding; Baocheng Geng; Makan Fardad; Yanzhi Wang (Intell. Syst. Appl., 2025)