Sully Chen
Machine Learning Engineer at OpenAI
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSully Chen is a machine learning engineer and medical researcher with a decade of experience building applied ML systems across healthcare, autonomous sensing, and brain–computer interfaces. He has blended hands-on research roles at OpenAI and NIH with practical engineering—shipping TensorFlow adaptations for autonomous driving and developing satellite and multispectral models to detect environmental hazards. Trained in computer science, biochemistry, and currently an MD candidate at Duke, Sully bridges deep learning, neurotechnology, and biomedical optics to pursue AI-driven improvements in neurosurgery and regenerative medicine. Notably, his work ranges from single-molecule conductance experiments to high-accuracy EEG-based BCI models, reflecting a rare mix of wet-lab, device, and algorithmic expertise.
10 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Biochemistry, GPA: 3.9, Bachelor of Science - BS, Biochemistry, GPA: 3.9 at University of Southern CaliforniaCalifornia Polytechnic State University, San Luis ObispoDoctor of Medicine - MD, Doctor of Medicine - MD at Duke University School of Medicine
English, Chinese, French, Spanish
Github Skills (6)
computer-vision10
machine-learning10
tensorflow10
python10
autonomous-driving9
opencv9
Programming languages (4)
Github contributions (5)
SullyChen/Autopilot-TensorFlow
Oct 2016 - Aug 2022
A TensorFlow implementation of this Nvidia paper: https://arxiv.org/pdf/1604.07316.pdf with some changes
Role in this project:
ML Engineer
ML EngineerContributions:42 commits, 9 PRs, 50 pushes in 5 years 11 months
Contributions summary:Sully primarily focused on adapting and improving the provided TensorFlow implementation for autonomous driving, addressing compatibility issues and fixing errors. Key contributions include fixing Tensorboard errors, resolving TensorFlow 2.0 incompatibilities, and improving Windows compatibility. They also modified the data loading and preprocessing pipelines, and adapted existing scripts for improved functionality.
arxivpdfnvidiadeep-learningmachine-learning
SullyChen/driving-datasets
Jul 2018 - Sep 2021
Contributions:9 commits, 9 pushes, 1 branch in 3 years 3 months
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