CV

Brief

Technical Skills

Programming Languages: Python, Java, JavaScript, C#

Core Competencies: Program Analysis, Compiler Construction, High-Performance Computing, Data Analysis & Visualization, Machine Learning

Tools: Git, HPC Clusters, Docker.

Work Experience

Hangzhou Sheng’ao Information Technology Co., Ltd., Hangzhou, China

• Position: Algorithm and Data Intern

• Duration: 07/2022 - 09/2022

• Responsibilities:

  Applied deep learning algorithms to small molecule drug discovery. Conducted preprocessing and analysis of biochemical datasets. Performed database operations and data pipeline optimization.

Projects

Exploring Large Language Models for Automated Static Program Analysis

Course project of DTU 02806 Program Analysis

• Year: 2024

• Description:

  Evaluated the effectiveness of Large Language Models in enhancing program analysis by testing their performance on common error detection tasks including array bounds violations, divide-by-zero errors, assertion failures, and deadlocks. Developed a hybrid approach combining LLM-based static analysis with dynamic testing validation using fuzz testing and dictionary-based input selection strategies.

Application User Management System

Course project of DTU 02239 Data Security, link to the project github repository

• Year: 2024

• Key Features:

  1. Authentication System: Implemented secure password-based authentication mechanisms for client/server applications, covering password storage with salting and hashing, secure transmission protocols, verification workflows, and session management using RMI framework.

  2. Access Control: Designed and implemented two access control approaches - Access Control List (ACL) and Role-Based Access Control (RBAC). Simulated organizational change scenarios demonstrating dynamic permission adjustment and role hierarchy management.

High-Performance Numerical Computing

Course project of DTU 02613 Python and High-Performance Computing

• Year: 2024-2025

• Technical Implementation:

  Conducted performance profiling and optimization for large-scale numerical simulations. Implemented parallel computing solutions using Python multiprocessing. Applied Just-In-Time compilation with Numba for computational bottlenecks and GPU acceleration with CUDA/CuPy for matrix operations. Deployed and benchmarked solutions on HPC cluster infrastructure using job arrays for distributed computing tasks.

Compiler Construction (Hygge Compiler)

Course project of DTU 02247 Compiler Construction

• Year: 2024

• Major Contributions:

  Extended the Hygge compiler with seven significant enhancements spanning syntax, semantics, type checking, interpreter functionality, and RISC-V code generation. Key achievements include:

  • Redesigned RISC-V stack frame architecture for functions with 9+ arguments, ensuring full compliance with calling conventions and proper 16-byte stack alignment. Link to the project blog - stack frame
  • Developed partial evaluation optimization pass achieving 30-80% instruction reduction through constant folding, constant propagation, and dead code elimination techniques. Link to the project blog - optimization

Explore NYC Public Toilets: Interactive Data Visualization

Course project of DTU 02806 Social Data Analysis and Visualization. Link to the project

• Year: 2025

• Technical Skills:

  Conducted social data analysis on NYC public infrastructure data. Developed interactive visualizations using Python (matplotlib, seaborn, pandas) and JavaScript (D3.js). Implemented narrative visualization techniques, exploring patterns in toilets distribution and accessibility across New York City.