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

NeurIPS Scholar Award

NeurIPS 2025

ISIT Travel Grant Award

IEEE IT Society

Departmental Research 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

Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions

NeurIPS 2025

Acceptance rate: 24.5%.

Weakly Private Information Retrieval from Heterogeneously Trusted Servers

IEEE Transactions on Information Theory

Volume 71, Issue 9, 7292-7309.

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

ISIT 2025

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

AISTATS 2025

Acceptance rate: 31.3%.

Partial Information Decomposition

Information-theoretic multimodal learning

• Gaussian Partial Information Decomposition
• PID via Normalizing Flows

Bayesian Deep Learning

Uncertainty quantification in Bayesian models

• Bayesian LoRA
• Deep Additive Kernel Learning
• Deep Gaussian Processes

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