Mr. Chuanxi Liu, State Nuclear Power Information Technology Company.LTD, China
Mr. Chuanxi Liu is a highly skilled professional with a background in Applied Physics and Astrophysics. He holds a BSc. from Shandong Jianzhu University and an MSc. from the University of Chinese Academy of Sciences. With expertise in programming languages such as Embedded C, Python, MATLAB, and more, he has contributed significantly to research and development in various fields. During his tenure at Yunnan Observatory, he conducted groundbreaking research on gamma-ray burst spectra and light, resulting in several published papers. At Shandong University Electric Power Technology Co., Ltd. and State Nuclear Power Information Technology Company.LTD, he applied his expertise in data analysis and image processing to develop innovative solutions for waveform analysis and crack recognition in wind power inspection. His dedication to advancing technology and his commitment to excellence make him a valuable asset in any organization. š
š Professional Profile:
Scopus
Education:
- Shandong Jianzhu University BSc. Applied Physics September 2011 – June 2015
- University of Chinese Academy of Sciences MSc. Astrophysics September 2015 – June 2019
Skills:
- Programming Languages: Embedded C, Python, LaTeX, MATLAB, HTML, C++, C#, CSS, JavaScript, Fortran
- Hobby: Exercising, Skating, Football, Swimming
Work Experience:
- Yunnan Observatory Master of Science September 2015 – June 2019
- Conducted research and analysis on gamma-ray burst spectra and light, validating astrophysical models.
- Published papers on GRB X-Ray Flare properties and statistical studies of Swift X-Ray Flash.
- Shandong University Electric Power Technology Co., Ltd. Distributed Traveling Wave March 2020 – June 2022
- Processed one-dimensional waveform data using neural network calculation for ranging.
- Developed image processing methods for identifying faulty waveform signals.
- Patented a Traveling Wave Ranging Method and System based on dynamic waveform analysis.
- State Nuclear Power Information Technology Company.LTD Wind Power Inspection March 2020 – June 2022
- Conducted oil leakage detection, regional segmentation, and instrument panel reading.
- Developed algorithms for crack recognition using skeleton extraction and defect detection.
- Presented paper on TBFF-DAC: Two-branch Feature Fusion Based on Deformable Attention and Convolution for Object Detection.
Publication Top Notes:
TBFF-DAC: Two-branch feature fusion based on deformable attention and convolution for object detection
- Published in Computers and Electrical Engineering, 2024.