Wenguang Chen

Wenguang Chen is a researcher affiliated with Tsinghua University and Pengcheng Laboratory, specializing in computer science and high-performance computing. His work bridges theoretical advancements with practical applications in domain-specific languages, parallel programming, and machine learning.

Research Interests include:

• Development of modular DSLs for numerical methods (e.g., Mat2Stencil)
• Performance optimization in distributed and parallel systems
• Compiler frameworks for privacy-preserving AI (e.g., FHE-based neural network inference)
• Graph algorithms scaling to trillion-edge datasets
• Applications of Rust in memory-safe pointer analysis

Recent Publications span 2014–2025, focusing on:

• Parallelization strategies for supercomputing
• Compiler automation tools
• Extreme-scale data processing
• Performance variance diagnosis in production environments