Teaching Effect of College English Based on Cloud Class Platform. - Yongqin Wang; Mingming Han; Fei Lang (eLEOT, 2018)

Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments. - Krishna Giri Narra; Zhifeng Lin; Yongqin Wang; Keshav Balasubramaniam; Murali Annavaram (CoRR, 2019)

A general framework for fatigue reliability analysis of a high temperature component. - Weiqi Du; Yuanxin Luo; Yongqin Wang; Ling Ma (Qual. Reliab. Eng. Int., 2019)

Research on reliability allocation technology for NC machine tool meta-action. - Yulong Li; Genbao Zhang; Yongqin Wang; Xiaogang Zhang; Yan Ran (Qual. Reliab. Eng. Int., 2019)

Time-variant reliability analysis using the parallel subset simulation. - Weiqi Du; Yuanxin Luo; Yongqin Wang (Reliab. Eng. Syst. Saf., 2019)

DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks. - Hanieh Hashemi; Yongqin Wang; Murali Annavaram (CoRR, 2020)

A reliability-based fatigue design for mechanical components under material variability. - Weiqi Du; Yongqin Wang; Yuanxin Luo (Qual. Reliab. Eng. Int., 2020)

Research on meta-action decomposition and meta-action unit modeling technology for electromechanical product. - Yulong Li; Xiaogang Zhang; Yan Ran; Genbao Zhang; Yongqin Wang (Qual. Reliab. Eng. Int., 2020)

Origami Inference: Private Inference Using Hardware Enclaves. - Krishna Giri Narra; Zhifeng Lin; Yongqin Wang; Keshav Balasubramanian; Murali Annavaram (CLOUD, 2021)

Research on Evaluation Model of College English Online and Offline Mixed Learning Under Digital Environment. - Yongqin Wang (DLI, 2021)

DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware. - Hanieh Hashemi; Yongqin Wang; Murali Annavaram (MICRO, 2021)

Privacy and Integrity Preserving Training Using Trusted Hardware. - Hanieh Hashemi; Yongqin Wang; Murali Annavaram (CoRR, 2021)

Byzantine-Robust and Privacy-Preserving Framework for FedML. - Hanieh Hashemi; Yongqin Wang; Chuan Guo 001; Murali Annavaram (CoRR, 2021)

Look Ahead ORAM: Obfuscating Addresses in Recommendation Model Training. - Rachit Rajat; Yongqin Wang; Murali Annavaram (CoRR, 2021)

Characterization of MPC-based Private Inference for Transformer-based Models. - Yongqin Wang; G. Edward Suh; Wenjie Xiong 001; Benjamin Lefaudeux; Brian Knott; Murali Annavaram; Hsien-Hsin S. Lee (ISPASS, 2022)

PageORAM: An Efficient DRAM Page Aware ORAM Strategy. - Rachit Rajat; Yongqin Wang; Murali Annavaram (MICRO, 2022)

MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine Learning Inference. - Yongqin Wang; Rachit Rajat; Murali Annavaram (CoRR, 2022)

LAORAM: A Look Ahead ORAM Architecture for Training Large Embedding Tables. - Rachit Rajat; Yongqin Wang; Murali Annavaram (ISCA, 2023)

CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for Deep Neural Networks. - Yongqin Wang; Pratik Sarkar; Nishat Koti; Arpita Patra; Murali Annavaram (IACR Cryptol. ePrint Arch., 2023)

MPC-Pipe: an Efficient Pipeline Scheme for Semi-honest MPC Machine Learning. - Yongqin Wang; Rachit Rajat; Murali Annavaram (ASPLOS (4), 2024)

Fastrack: Fast IO for Secure ML using GPU TEEs. - Yongqin Wang; Rachit Rajat; Jonghyun Lee; Tingting Tang; Murali Annavaram (CoRR, 2024)

PIGEON: A Framework for Private Inference of Neural Networks. - Christopher Harth-Kitzerow; Yongqin Wang; Rachit Rajat; Georg Carle; Murali Annavaram (IACR Cryptol. ePrint Arch., 2024)

External validation and application of risk prediction model for ventilator-associated pneumonia in ICU patients with mechanical ventilation: A prospective cohort study. - Jiaying Li; Guifang Li; Ziqing Liu; Jincong Wang; Xueping Jia; Hongxiao Yang; Yongqin Wang (Int. J. Medical Informatics, 2025)

High-Throughput Secure Multiparty Computation with an Honest Majority in Various Network Settings. - Christopher Harth-Kitzerow; Ajith Suresh; Yongqin Wang; Hossein Yalame; Georg Carle; Murali Annavaram (Proc. Priv. Enhancing Technol., 2025)

PIGEON: A High Throughput Framework for Private Inference of Neural Networks using Secure Multiparty Computation. - Christopher Harth-Kitzerow; Yongqin Wang; Rachit Rajat; Georg Carle; Murali Annavaram (Proc. Priv. Enhancing Technol., 2025)

Characterization of GPU TEE Overheads in Distributed Data Parallel ML Training. - Jonghytun Lee; Yongqin Wang; Rachit Rajat; Murali Annavaram (CoRR, 2025)