Chen Zhao
Beijing, China
Contact
Chen Zhao
Beijing, China
School of Artificial Intelligence
Beijing University of Posts and Telecommunications
I'm currently a third-year master's student at the School of Artificial Intelligence, Beijing University of Posts and Telecommunications(BUPT), Beijing, China. My advisor is Prof. Zhuqing Jia. Previously, I received my bachelor's degree from the School of Communications and Information Engineering, Shanghai University(SHU) in 2023.
My research interests include information and coding theory, machine learning and their applications. Now I am seeking PhD opportunities starting in Fall 2026. Prospective supervisors please feel free to contact me at [email protected].
My research interests include information and coding theory, machine learning and their applications. Now I am seeking PhD opportunities starting in Fall 2026. Prospective supervisors please feel free to contact me at [email protected].
News
[Accepted ITW 2025] Jun 27 2025 Robust Dynamic Coded Distributed Storage with Partially Storage Constrained Servers has been accepted to ITW 2025! Thanks for my wonderful collaborators.
Research Experience
Coding Design for Robust Dynamic Distributed Storage in Heterogeneous Storage Constraints
Research Overview
Robust dynamic coded distributed storage enables
- read/write operations under server dropouts,
- update-increment privacy against collusion by any X servers
- operation completion under storage constraints.
The goal is to characterize the fundamental limits and achievable schemes for communication cost in heterogeneous storage constraints.
Main Contributions
- Characterized the fundamental limits of robust dynamic storage under partial storage constraints and proposed achievablity schemes that match the converse bound.
- Established fundamental limits of robust dynamic storage under arbitrary storage constraints, proposing a coding scheme based on message-splitting that:
- Achieves total storage optimality,
- Maintains communication load within a constant factor of fundamental limits at scale.
Non-Interactive Privacy-Preserving Linear Regression Algorithm (Undergraduate thesis)
Research Overview
Linear regression (linear transformation) is widely used in neural network training. Designed a non-interactive, privacy-preserving training scheme with low communication overhead to train a global model while protecting user privacy.
Main Contributions
Proposed a novel training framework that eliminates the need for iterative client-server interactions, reducing communication costs. It can be experimentally validated that the scheme outperforms existing federated learning methods in computational efficiency and communication load. Published a Chinese patent as the first-author student.
Competition Experience
The 21st China Post-Graduate Mathematical Contest in Modeling
National Second Prize, Problem B (Huawei Problem), 2024
National Undergraduate Electronic Design Contest | Shanghai Division
First Prize, Problem D, 2022
Scholarships and Honors
First-Class Scholarship at Beijing University of Posts and Telecommunications (Twice awarded, 2023,2024)
Shanghai University Academic Excellence Award (2022, 2%)
Shanghai Outstanding Graduate (2023)
Teaching Asistant
Class: Mathematics Related to Artificial Intelligence, Teacher: Prof. Zhuqing Jia
Content: Math class including Inforamtion Theory, Statistic, Analysis, etc. Duty: Mark students’ homework and give feedback.
Campus Experience
BUPT Swimming Team, 2023~2026, BUPT
Participated in the 43rd and 45th Capital Universities Swimming Championships, Beijing
Monitor, 2020~2023, SHU
In charge of the daily affairs for Class 5 of the 2019 Communications Engineering cohort, Shanghai University
Work Experience
Shanghai Laoquan Technology Co., Ltd.
Algorithm Engineer, Intern, March 2022~July 2022
Responsible for developing financial investment strategies and performing backtesting analyses.