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Matthew Chang
Machine Learning | Formerly Silicon Photonics | Ex-Apple
Matthew Chang is a professional transitioning from semiconductor chip design to machine learning.
He holds a Doctor of Philosophy (PhD) in Electrical Engineering from Princeton University and a Bachelor of Science (B.S.) with a Minor in Physics in Electrical Engineering from Penn State University.
He has held key positions in various organizations such as Vice President of Photonics, Senior Photonics Engineer, and Product Lead at Luminous Computing, Wireless Design Engineer at Apple, and Chief Technical Officer at Rebeless.
Matthew has documented his journey of transitioning to machine learning on his Medium blog.
Highlights
I'm excited to share that my team won the 2024 NFL #BigDataBowl, a data science competition hosted by the #NFL and #AWS!
For the competition, we used the NFL's player tracking data to build a tackle probability model, which predicts the probability that a defender will make a tackle within the next second. Using the model, we derived a new metric, Missed Tackle Opportunities, which represents instances where a defender had a chance to make a tackle, but let it slip away. Think of a defender getting juked out or making an ambiguous arm tackle. Our model uncovered over 4000 missed tackle opportunities in weeks 1-9 of the 2022 season. For reference, only ~1100 missed tackles were logged by existing stats.
To learn more about our work check out our:
- Report: https://lnkd.in/gBJkWrvr
- Presentation: https://lnkd.in/ga_3ye-y
- Expected Value Podcast episode with Paul Carr: https://lnkd.in/g_3HG9FJ
- Code: https://lnkd.in/g68b7Y9D
Shoutout Kat Dai, Harvey Cheng, and Daniel Jiang for being the dream team. And a big thanks to the NFL and all the team and league staff members who made this such an incredible opportunity.
#MachineLearning #SportsAnalytics #DataScience
Over the past 6 months, I've been working on a career pivot from silicon photonics to machine learning. It's been a fun journey that has taken me back to the fundamentals and, unexpectedly, to the NFL Combine.
I'm now seeking new opportunities as a machine learning engineer that will allow me to build ML products at scale, with all the nitty-gritty details that come with it. Please reach out if you know of any interesting opportunities!
P.S. I'm writing about my career pivot journey in real time. If you're curious or thinking about making a switch yourself, follow along here:
