Chang Huai-Yuan
Email: hamiltonchangwork”at”gmail.com / hamiltonchang”at”pku.edu.cn
Education
Peking University, M.E. in Software Engineering, Sept. 2017 - Aug. 2020
Chung Yuan Christian University, B.S. in Computer Science and Information Engineering, Sept. 2013 - June 2017
Experience
Infortrend Technology, New-Taipei, Taiwan
AI Research and Develop Engineer, May.2021-Jul.2022
- Solved the issue of multi-processes shared face database through shared memory and accelerated comparison time by 3times, and accelerated inference time by 5 times through quantization and TensorRT on Face Recognition API
- Reduced half docker image size of AI Service API through Multi-Stage and deleted-redundant dependencies.
- Reduced inference time by 3 times on general CPU platforms using TensorFlow Lite with XNNPack.
- Developed an auto-tiered model to improve IO performance by 60% on Infortrend storage systems
Patere Technologies, Inc., Taipei, Taiwan
Computer Vision Engineer, Nov. 2020 - Jan. 2021
- Designed a rule-based confidence and speech fluency detection algorithm with basic speech features
- Built an extractor to get more complex and useful features which served for ML/DL, such as MFCC, FBank features
- Designed an attention detection algorithm reaching about 80% accuracy, precision and recall on the testing dataset
Lenovo Group Ltd, Lenovo Research, Beijing, China
Computer Vision and AI Algorithm Intern, Aug. 2019 - Nov. 2019
- Developed automatic training system for commodity detection based on RetinaNet for unmanned stores
- Optimzed the success rate of commodity detection about 20% through collecting and generating more complex and suitable data
Zero Zero Robotics, Beijing, China
Computer Vision and AI Algorithm Intern, Nov. 2018 - Aug. 2019
- Developed, maintained and optimized long-term object tracking module on Hover Camera 2 drone
- Improved by 15% tracking success rate and reduced by 5% CPU utility through adding constraints and modifying object re-identification strategy for tracking module
Project
Design and Implementation of Real-time Long-term Single Person Tracking System
Individual Work, Nov. 2019 - April. 2020
- Tracking successful rate is 79.02%, recall is 77.54%, and FPS is 12.87 on Intel i7-6700k CPU
- Built three tracking states: target selection, track and retrieval, to fully handle the situations
- Designed several strategies to achieve real-time and stable long-term person tracking
2D Anime Charactors Recognition
Team Leader, May 2018 - June 2018
- TOP1 result is 73.25%
- Developed a model to recognize the different anime characters and let it can distinguish the same ones drawn by distinct artists
- Utilized the trained LBPcascade to detect anime faces and recognized ones with the fine-tuned Inception-v3 model
OurScheme: A Scheme Interpreter Implemented in C++
Individual Work, Mar. 2017 - May 2017
- Developed a complete interpreter workflow
- Designed for high stability and robustness
Face Recognition Access Control System Based on Raspberry Pi
Team Leader, Feb. 2016 - Nov. 2016
- Developed a complete face recognition access control solution on Raspberry Pi
- Recall and precision is about 85%
Skills
- Programming Language: Python, C/C++, Java, R
- Other: Git, Docker, Kubernetes, GDB, pdb