Matthew Lai is a research engineer at DeepMind with 11 years of experience spanning machine learning, embedded systems, hardware/software interfacing, computer vision, and electronics design. He pairs deep learning research with low-level engineering, demonstrating high proficiency in modern C++ and hands-on firmware work from contributions to prominent projects like the libopencm3 STM32 library and Adafruit's ADS1X15 driver. His background includes roles at Google, NVIDIA, Avigilon, and robotics labs, plus an MSc in Advanced Computing from Imperial College and an electrical engineering degree from UBC. Known for bridging algorithmic research and pragmatic hardware implementation, he often moves seamlessly between cloud-scale ML and microcontroller power/flash support—an uncommon cross-domain skillset among researchers.
11 years of coding experience
2 years of employment as a software developer
MSc Advanced Computing, MSc Advanced Computing at Imperial College London
Bachelor of Applied Science (B.A.Sc.), Electrical Engineering, Bachelor of Applied Science (B.A.Sc.), Electrical Engineering at The University of British Columbia
Contributions:15 commits, 14 PRs, 43 comments in 2 years 7 months
Contributions summary:Matthew primarily contributes to the STM32 microcontroller library, focusing on adding and improving support for various STM32F7 microcontroller features. Their work includes fixing errors, adding conditional compilation based on chip model, and refactoring clock setup. They also add basic power control support and flash memory support, demonstrating an understanding of the hardware architecture and low-level programming.
Driver for TI's ADS1015: 12-bit Differential or Single-Ended ADC with PGA and Comparator
Role in this project:
Embedded Systems Engineer / IoT Developer
Contributions:9 commits, 2 PRs, 5 comments in 2 days
Contributions summary:Matthew primarily contributed to the driver for TI's ADS1015 ADC. Their work involved refactoring code related to reading analog-to-digital conversions, and adding the capability for continuous data reads, improving the library's efficiency. They also added examples demonstrating continuous and non-blocking read operations to aid users. In addition, the user addressed formatting and documentation issues.
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Matthew Lai - Research Engineer (DeepMind) at Google