Yongqin Wang

Yongqin Wang

University of Southern California

H-index: 6

North America-United States

About Yongqin Wang

Yongqin Wang, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at University of Southern California, specializes in the field of Privacy, Machine Learning, MPC, Trusted Execution Environment, Oblivious RAM.

His recent articles reflect a diverse array of research interests and contributions to the field:

CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for Deep Neural Networks

Laoram: A look ahead oram architecture for training large embedding tables

Pageoram: An efficient dram page aware oram strategy

MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine Learning Inference

Characterization of mpc-based private inference for transformer-based models

DarKnight: An accelerated framework for privacy and integrity preserving deep learning using trusted hardware

Origami inference: Private inference using hardware enclaves

Byzantine-robust and privacy-preserving framework for fedml

Yongqin Wang Information

University

Position

PhD Student

Citations(all)

179

Citations(since 2020)

179

Cited By

9

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Yongqin Wang Skills & Research Interests

Privacy

Machine Learning

MPC

Trusted Execution Environment

Oblivious RAM

Top articles of Yongqin Wang

CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for Deep Neural Networks

arXiv preprint arXiv:2311.04406

2023/11/8

Laoram: A look ahead oram architecture for training large embedding tables

2023/6/17

Pageoram: An efficient dram page aware oram strategy

2022/10/1

MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine Learning Inference

arXiv preprint arXiv:2209.13643

2022/9/27

Characterization of mpc-based private inference for transformer-based models

2022/5/22

DarKnight: An accelerated framework for privacy and integrity preserving deep learning using trusted hardware

2021/10/18

Origami inference: Private inference using hardware enclaves

2021/9/5

Yongqin Wang
Yongqin Wang

H-Index: 2

Murali Annavaram
Murali Annavaram

H-Index: 31

Byzantine-robust and privacy-preserving framework for fedml

arXiv preprint arXiv:2105.02295

2021/5/5

See List of Professors in Yongqin Wang University(University of Southern California)

Co-Authors

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