CV

Ph.D.

Texas A&M University, United States

Information Science and Learning Systems

• Advisor: Prof. Chao Tian
• GPA: 4.0/4.0

M.S.

University of California San Diego, United States

Communication Theory and Systems

• Advisor: Prof. Xinyu Zhang

B.E.

Southeast University, China

Information Engineering

• Advisor: Prof. Cheng Zhang

ISIT Travel Grant Award

IEEE IT Society

Departmental Poster Event Winner

Texas A&M University

Sun Qingyun Scholarship

Southeast University

First Place in Mathematical Contest in Modeling (CUMCM)

China Society for Industrial and Applied Mathematics

Top 0.7%, best from Southeast University

Mitsubishi Electric Corporation Scholarship

Southeast University

Weakly Private Information Retrieval from Heterogeneously Trusted Servers

IEEE Transactions on Information Theory

Accepted.

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

Presented at ISIT 2025

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

Presented at AISTATS 2025

Acceptance rate: 31.3%.

Bayesian Learning and Inference

Deep Gaussian processes as Bayesian neural networks.

• Deep Additive Kernel Learning
• Deep Markov GP

Coding for Privacy

Optimizing code schemes for private information retrieval (PIR) systems.

• Weakly Private Information Retrieval
• Leaky Private Information Retrieval

Dynamic mmWave Networking

Highly dynamic network control decisions in 5G IAB, from heterogeneous network slices to run-time decision-making.

• Self-supervised Adaptive Configuration
• Reinforcement Learning Mesh Controller