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Justin Skycak (pr: Sky-zack)
I develop quantitative models that emulate the behavior of human experts. In particular, I specialize in developing interpretable models that combine mathematical theory with human intuition. Currently, I'm developing the models & algorithms that drive Math Academy's fully automated and personalized online learning system.
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Background: I earned a BS in Mathematics from Notre Dame on full-ride scholarship, and a MS in Computer Science (Machine Learning track) from Georgia Tech, all while working full time. I've done plenty of interesting things with math, including building predictive models for businesses as a data scientist, simulating and proving properties of biological neural networks, and completing two particle physics research projects that improved CERN and Fermilab particle detectors. I also tutored & taught math for a decade, culminating in (currently) developing and teaching one of the most advanced high school applied math/CS sequences in the country, Math Academy's Eurisko sequence.

Hobbies
  • Music. I taught myself guitar in grade school and still pick it up every once in a while. I learned viola too, but haven't kept it up since high school. During college, I spent some time tinkering with music production. I listen to music all the time while working; here are my top picks. I especially enjoy finding covers that are better than the original and combining covers that I like.
  • Writing. I've written several textbooks for fun as a way to consolidate and clarify my quantitative intuition.