Personal details
Charles G.
Timezone: Pacific Time (US & Canada) (UTC-7)
Summary
Charles researches brain-machine interfaces at Caltech. He focuses on machine learning for decoding movement intent from noisy neural signals. Outside of research, Charles also teaches data science workshops using Python. Previously, he built payments software and hardware as a Senior Embedded Software Engineer at Square. Charles earned his M.S. and B.S. degrees in electrical engineering from Stanford.
Technical skills
Work Experience
Brain-Machine Interface Researcher
Caltech | Sep 2018 - Present
Python
Machine Learning
MATLAB
- Use machine learning to translate brain activity into movement intent
- Used different models (RNNs, autoencoders, linear regression, XGBoost) to analyze and decode noisy data
- Presented preliminary results at conferences, publications in process
Senior Embedded Software Engineer
Square | Jul 2016 - Aug 2018
Embedded C
Embedded Systems
- Developed payments devices that help run over 2 million small businesses
- Wrote firmware for Square Register and Square Terminal, including RTOS, payments logic, and ARM debugging tools
- Redesigned automatic repeat request protocol for reliable communications
between chips and implemented data encryption
- Automated hardware testing using Python
- Supported 5 prototyping builds at contract manufacturer in Shenzhen
Personal Projects
2017
Embedded Linux
Embedded Systems
- Developed firmware for payments devices that run millions of businesses
- Built reliable transport protocol between microcontroller and mobile ARM chip
- Supported 4 manufacturing prototyping trips