Yi-le Chen
Software Engineer at NVIDIA
California, United States
Summary
🤩
Rockstar🎓
Top SchoolYi-le Chen is a software engineer with seven years of experience bridging research and production systems in machine learning, computer vision, and robotics. Currently at NVIDIA after internships at NVIDIA DriveIX and Arm, Yi-le has contributed to open-source time-series anomaly detection (TODS), improving DeepLog model stability and hyperparameter tuning. Trained in computer engineering at Texas A&M and with hands-on robotics competition experience, they combine low-level C/C++ systems work with Python-based ML development. Comfortable shipping both research code and production software, Yi-le also brings practical QA and infrastructure performance experience and a creative side evidenced by photography and music.
7 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Computer Engineering, Bachelor of Science - BS, Computer Engineering at Texas A&M UniversityHong Kong University of Science and Technology (HKUST)
Chinese, English
Github Skills (6)
machine-learning10
time-series10
anomaly-detection10
python10
deep-learning9
tensorflow8
Programming languages (5)
Github contributions (5)
datamllab/tods
Sep 2020 - Dec 2020
TODS: An Automated Time-series Outlier Detection System
Role in this project:
ML Engineer
ML EngineerContributions:16 commits, 2 PRs, 23 pushes in 3 months
Contributions summary:Yi-le's commits primarily focus on modifying and fixing the `DeepLog` anomaly detection algorithm. These changes include code corrections and updates to the `DeepLog` model, with edits to the hyperparameter settings and the model's compilation process. The modifications aim at resolving bugs and enhancing the functionality of the time-series anomaly detection system.
time-series-analysisoutlier-detectionanomaly-detectionmachine-learningoutlier
YileAllenChen1/RobomasterComputerVision-CYL
Dec 2020 - Feb 2021
Contributions:34 commits, 31 pushes, 1 branch in 2 months
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