Matthew Chang
Semiconductor Chip Designer Machine Learning
Semiconductor Chip Designer Machine Learning
Hello, I'm Matt. I live in the San Francisco Bay Area. I'm driven by engineering products that customers love using. I started my career in the world of hardware, where I worked on the Apple Watch Series 3 and 4 and designed optical integrated circuits for AI supercomputers. Since then, I took a leap of faith and transitioned into the world of software engineering and machine learning.
Outside of work, I love playing basketball and have followed the NBA since I was a child. Three years ago I transitioned from being a runner to a swimmer, and I recently completed my first open-ocean swim from Alcatraz Island back to San Francisco. I have two cats named Chichi and Tofu, who were one feral kittens but have since mastered the craft of human engineering.
View Resume
July, 2024 - Present
I work on Cascade, Codeium's AI agentic pair programmer that works together with developers to write code more efficiently. Try Cascade out for yourself today.
May, 2019 - May, 2023
I was employee #2 and the Vice President of photonics at Luminous Computing, where I recruited and led a team of 9 engineers. Our team delivered the first monolithically integrated 112 Gbps PAM4 transceiver chips, fabricated in the 300mm GlobalFoundries Fotonix platform. I helped build the design software infrastructure (simulation, layout, integration) and the lab (including a home-grown 300mm wafer tester) from scratch. I also owned the key relationships with our photonics foundry partners (GlobalFoundries, SilTerra) and equipment vendors. The photonics IP lives on today at Enosemi.
June, 2017 - May, 2019
I helped reduce multi-radio coexistence interference in the Apple Watch Series 3 and 4 using both hardware and software techniques. I owned the automation software for in-factory testing of coexistence interference for these products.
2011 - 2017
I received my PhD from the Lightwave Lab at Princeton University, with a research focus on building photonic integrated circuits for ultra wideband wireless signal processing. For my thesis, I designed the first integrated circuit that reduced wireless interference over 1000x over every LTE channel in existence at the time, using analog interference cancellation.
The Big Data Bowl is the premiere sports analytics data science competition hosted by AWS and the NFL. My team was selected as the grand prize winner from a field of over 300 teams using our metric, Missed Tackle Opportunities and Tackle Probability. Missed tackle opportunities represent a new class of defensive mistake that is not captured by the current statistics: think of defenders getting juked out, making ambiguous arm tackles, or being lazy. To detect these missed tackle opportunities, we trained a custom XGBoost model that ingests player tracking data to predict each defender's probability of making the tackle within the next second. We verified the model's accuracy by successfully identifying ~90% of the 1100x labeled missed tackles, and on top of that, also identified an additional 3500x missed tackle opportunities that were previously undetected. Missed tackle opportunities has been incorporated in the AWS NextGenStats pipeline.
