An Empirical Study of Quad-Level Cell (QLC) NAND Flash SSDs for Big Data Applications. - Shuwen Liang; Zhi Qiao 001; Sihai Tang; Jacob Hochstetler; Song Fu; Weisong Shi; Hsing-Bung Chen (IEEE BigData, 2019)

Smart Home IoT Anomaly Detection based on Ensemble Model Learning From Heterogeneous Data. - Sihai Tang; Zhaochen Gu; Qing Yang 003; Song Fu (IEEE BigData, 2019)

F-cooper: feature based cooperative perception for autonomous vehicle edge computing system using 3D point clouds. - Qi Chen 018; Xu Ma 005; Sihai Tang; Jingda Guo; Qing Yang 003; Song Fu (SEC, 2019)

Cooper: Cooperative Perception for Connected Autonomous Vehicles Based on 3D Point Clouds. - Qi Chen 018; Sihai Tang; Qing Yang 003; Song Fu (ICDCS, 2019)

Low-Latency High-Level Data Sharing for Connected and Autonomous Vehicular Networks. - Qi Chen 018; Sihai Tang; Jacob Hochstetler; Jingda Guo; Yuan Li 054; Jinbo Xiong; Qing Yang 003; Song Fu (ICII, 2019)

A middle-ware approach to leverage the distributed data de-duplication capability on HPC and Cloud storage systems. - Hsing-bung Chen; Sihai Tang; Song Fu (IEEE BigData, 2020)

Cascaded Context Dependency: An Extremely Lightweight Module For Deep Convolutional Neural Networks. - Xu Ma 005; Zhinan Qiao; Jingda Guo; Sihai Tang; Qi Chen 018; Qing Yang 003; Song Fu (ICIP, 2020)

Spanet: Spatial Pyramid Attention Network for Enhanced Image Recognition. - Jingda Guo; Xu Ma 005; Andrew Sansom; Mara McGuire; Andrew Kalaani; Qi Chen 018; Sihai Tang; Qing Yang 003; Song Fu (ICME, 2020)

Attention Meets Normalization and Beyond. - Xu Ma 005; Jingda Guo; Qi Chen 018; Sihai Tang; Qing Yang 003; Song Fu (ICME, 2020)

Cooperative Mixed Reality Leveraging Edge Computing and Communication. - Sihai Tang; Bruce Haidi Chen; Jacob Hochstetler; Jason Hirsch; Song Fu (SEC, 2020)

DCANet: Learning Connected Attentions for Convolutional Neural Networks. - Xu Ma 005; Jingda Guo; Sihai Tang; Zhinan Qiao; Qi Chen 018; Qing Yang 003; Song Fu (CoRR, 2020)

CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles. - Jingda Guo; Dominic Carrillo; Sihai Tang; Qi Chen 018; Qing Yang 003; Song Fu; Xi Wang 001; Nannan Wang 003; Paparao Palacharla (CoRR, 2020)

VECFrame: A Vehicular Edge Computing Framework for Connected Autonomous Vehicles. - Sihai Tang; Bruce Haidi Chen; Harold Iwen; Jason Hirsch; Song Fu; Qing Yang 003; Paparao Palacharla; Nannan Wang 003; Xi Wang 001; Weisong Shi (EDGE, 2021)

APCNN: Explore Multi-Layer Cooperation for CNN Optimization and Acceleration on FPGA. - Beilei Jiang; Xianwei Cheng; Sihai Tang; Xu Ma 005; Zhaochen Gu; Hui Zhao 013; Song Fu (FPGA, 2021)

Learning Connected Attentions for Convolutional Neural Networks. - Xu Ma 005; Jingda Guo; Sihai Tang; Zhinan Qiao; Qi Chen 018; Qing Yang 003; Song Fu; Paparao Palacharla; Nannan Wang 003; Xi Wang 001 (ICME, 2021)

Characterizing Job-Task Dependency in Cloud Workloads Using Graph Learning. - Zhaochen Gu; Sihai Tang; Beilei Jiang; Song Huang; Qiang Guan; Song Fu (IPDPS Workshops, 2021)

CoFF: Cooperative Spatial Feature Fusion for 3-D Object Detection on Autonomous Vehicles. - Jingda Guo; Dominic Carrillo; Sihai Tang; Qi Chen 018; Qing Yang 003; Song Fu; Xi Wang 001; Nannan Wang 003; Paparao Palacharla (IEEE Internet Things J., 2021)

Spatial Pyramid Attention for Deep Convolutional Neural Networks. - Xu Ma 005; Jingda Guo; Andrew Sansom; Mara McGuire; Andrew Kalaani; Qi Chen 018; Sihai Tang; Qing Yang 003; Song Fu (IEEE Trans. Multim., 2021)

MLCNN: Cross-Layer Cooperative Optimization and Accelerator Architecture for Speeding Up Deep Learning Applications. - Beilei Jiang; Xianwei Cheng; Sihai Tang; Xu Ma 005; Zhaochen Gu; Song Fu; Qing Yang 003; Mingxiong Liu (IPDPS, 2022)

Online Self-Evolving Anomaly Detection for Reliable Cloud Computing. - Tianyu Bai; Haili Wang; Jingda Guo; Xu Ma 005; Mahendra Talasila; Sihai Tang; Song Fu; Qing Yang 003 (UCC, 2022)

Perception Workload Characterization and Prediction on the Edges with Memory Contention for Connected Autonomous Vehicles. - Sihai Tang; Shengze Wang 004; Song Fu; Qing Yang 003 (EDGE, 2023)