Wenyuan Zhao

ROOM 326

WEB Building

College Station, TX 77840

Hi, I am Wenyuan (Warren), a second year Ph.D. student in the Electrical and Computer Engineering Department at Texas A&M University, advised by Professor Chao Tian. Currently, I am working on the general area of Machine Learning and Information Theory where new algorithms are proposed dealing with diverse settings.

Before joining TAMU, I obtained my M.S. degree in Communication Theory & Systems at UC San Diego, where I worked on Dynamic mmWave Networking with Professor Xinyu Zhang. Before that, I obtained my B.E. degree in Information Engineering at Southeast University in 2021.

My research interests lie in machine learning, information theory, and communication. Particularly, I am working on Bayesian deep learning, uncertainty quantification and generative models.

News

Apr 15, 2025	“Optimizing leaky private information retrieval codes to achieve O(log K) leakage ratio exponent” is accepted by ISIT 2025!
Feb 25, 2025	2025 Departmental Poster Event Winner @ Texas A&M University!
Jan 21, 2025	“From deep additive kernel learning to last-layer Bayesian neural networks via induced prior approximation” is accepted by AISTATS 2025!
Apr 19, 2024	“Weakly private information retrieval from heterogeneously trusted servers” is accepted by ISIT 2024!
Aug 15, 2023	Pursuing Ph.D. degree at Texas A&M University with Prof. Chao Tian!
Jun 30, 2023	Graduation from UCSD with M.S. degree conferred. Goodbye, UCSD! 🎓
Jun 30, 2021	Graduation from SEU with B.E. degree conferred. Goodbye, SEU! 🎓
Jun 15, 2020	Sun Qingyun Scholarship from ECEN @ SEU.
Nov 10, 2019	First-prize winner at 2019 Mathematical Contest in Modeling!

Selected Publications

AISTATS

From Deep Additive Kernel Learning to Last-layer Bayesian Neural Networks via Induced Prior Approximation

Wenyuan Zhao, Haoyuan Chen, Tie Liu, Tuo Rui, and Chao Tian

In , 2025

Bib PDF Code

@inproceedings{zhao2025deep,
  title = {From Deep Additive Kernel Learning to Last-layer Bayesian Neural Networks via Induced Prior Approximation},
  author = {Zhao, Wenyuan and Chen, Haoyuan and Liu, Tie and Rui, Tuo and Tian, Chao},
  journal = {The 28th International Conference on Artificial Intelligence and Statistics},
  year = {2025},
  organization = {PMLR},
}

ISIT

Optimizing Leaky Private Information Retrieval Codes to Achieve ${O}( \log K) $ Leakage Ratio Exponent

Wenyuan Zhao, Yu-Shin Huang, Chao Tian, and Alex Sprintson

In 2024 IEEE International Symposium on Information Theory (ISIT), 2025

Bib PDF

@inproceedings{zhao2025optimizing,
  title = {Optimizing Leaky Private Information Retrieval Codes to Achieve $$\{$O$\}$( $\log$ K) $ Leakage Ratio Exponent},
  author = {Zhao, Wenyuan and Huang, Yu-Shin and Tian, Chao and Sprintson, Alex},
  booktitle = {2024 IEEE International Symposium on Information Theory (ISIT)},
  year = {2025},
  organization = {IEEE},
}

ISIT

Weakly Private Information Retrieval from Heterogeneously Trusted Servers

Yu-Shin Huang, Wenyuan Zhao, Ruida Zhou, and Chao Tian

In 2024 IEEE International Symposium on Information Theory (ISIT), 2024

Bib PDF Code

@inproceedings{huang2024weakly,
  title = {Weakly Private Information Retrieval from Heterogeneously Trusted Servers},
  author = {Huang, Yu-Shin and Zhao, Wenyuan and Zhou, Ruida and Tian, Chao},
  booktitle = {2024 IEEE International Symposium on Information Theory (ISIT)},
  pages = {2862--2867},
  year = {2024},
  organization = {IEEE},
}