Education

• Physics student in Zhili College, Tsinghua University, 2023-Present

Skills

• Programming Languages: Python, C++, MATLAB
• Deep Learning Frameworks: PyTorch, TensorFlow

Project Experience

• Research on Batch Test and Analysis Program for Microwave Transmission Characteristics of Microwave Impedance Analyzer / Network Analyzer
  2024.04 - 2024.12
  1. Learned the usage methods of microwave impedance analyzer and vector network analyzer; used software packages to write programs to automatically read data such as S-parameters, temperature, and cooling time of vector network analyzers and temperature sensors during the testing process.
  2. Based on the commonly used data acquisition software tools in the laboratory, controlled the microwave impedance analyzer and vector network analyzer to set parameters such as power, frequency, and bandwidth to realize batch automatic testing of the same type of test items. According to the requirements of sample data analysis, summarized the data analysis process and realized the basic analysis and plotting functions of batch test data.
  3. Aiming at the testing requirements of low-temperature microwave devices, based on the hardware of impedance analyzers and vector network analyzers, formed a series of programs with basic functions of data acquisition and data analysis and wrote experimental manuals for undergraduates.
• Research on UAV High-Speed Obstacle Avoidance and Target Detection Algorithm Based on DVS and RGB Images
  2025.06 - Present
  1. Research on multimodal fusion algorithm based on DVS and RGB images: Analyzed the spatial mapping relationship between DVS event streams and RGB images, designed a deep learning model to fuse the features of the two modalities, and solved the problems of low-texture target detection and misidentification;
  2. Self-built UAV obstacle avoidance and target detection dataset: Collected data containing various environments such as low-texture targets and high-dynamic scenes, designed a labeling process and verified data quality to ensure the effectiveness of algorithm training;
  3. Design and optimization of low-power real-time detection system: Aiming at the edge computing requirements of UAVs, optimized the computational complexity of the algorithm, developed a lightweight model to adapt to the hardware platform, and improved the real-time performance and energy efficiency of the system.