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Justin Skycak (pr: Sky-zack)
Chief Quant, Director of Analytics at MathAcademy.com. Instead of optimizing return in the stock market, I optimize learning efficiency in students' brains. I do all our AI, science, and algo-heavy infra. Nothing excites me more than seeing people lean into serious upskilling (stages 2-3 in Bloom's talent development process) and use the increased agency to benefit both themselves and the world. Nothing disappoints me more than seeing people fall short of their potential due to needless friction in the pursuit of serious upskilling.

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More Detail:
  • Math Academy is an online math learning platform that is hyper-efficient, individualized, adaptive, and fully automated.
  • I develop all our quantitative software (among other things). This includes building our entire AI system from scratch, as well as all the science-y stuff, knowledge graph management infrastructure, and any algorithmically complicated back-end infrastructure in general. more
  • I first joined Math Academy helping out with its in-school program, America's most accelerated math program, where students learn all of high school math in 6th-7th grade, take AP Calculus BC in 8th grade, and study the equivalent of a full college math major in 9th-12th grade. Then the 2020 pandemic hit and we built an AI system to run our classes: automatically determining what a student knows and is ready to learn, selecting personalized learning tasks, teaching new material, reviewing and quizzing previous material, leveraging over a century of research to maximize learning efficiency every step of the way. In all measurable learning outcomes, including AP scores, our system turned out to be far superior to manual teaching. Math Academy is the most efficient and effective way to learn math. more
Previously: Physics research ➔ data science ➔ math/CS education ➔ Math Academy. Degrees in math and [the mathy side of] computer science.
  • Improved data transmission within Fermilab and CERN particle detectors; finalist in the 2013 International Science & Engineering Fair. more
  • Full-ride academic scholarship (Lilly Scholarship) to the University of Notre Dame; spent a summer in Los Alamos working on a LANL computational neuroscience project and then 2 years working full-time as a data scientist at Aunalytics while simultaneously an undergraduate. Master's in Computer Science (Machine Learning) from Georgia Tech. more
  • Tutored 300+ students from 2013-20 and developed what was, during its operation from 2020-23, the most advanced high school math/CS sequence in the USA. It culminated in high school students doing masters/PhD-level coursework (reproducing academic research papers in artificial intelligence, building everything from scratch in Python). more
  • Solved every problem that Math Academy has faced while constructing an educational knowledge graph for all of 4th grade through university-level mathematics and building a fully automated, fully adaptive learning system around it. This includes building our entire AI system from scratch, including formalizing a novel theory of maximum-efficiency spaced repetition in hierarchical knowledge structures. more
Hobbies: Calisthenics. (Previously: math, music, tutoring, hockey.)
  • Self-studied most of undergraduate math during high school; self-published several math textbooks (over 1000 pages total) shortly after college. more
  • Achieved an extreme physique transformation from 2021-23 using only calisthenics; continued training advanced calisthenics including various moves on the gymnastic rings. more