'24     '23     '22     '21     '20     '19     '18     '17     '16     '15     '14     '13     '12     '11     '10 |
work    <-- Math Academy Algo Dev ------------]          [ AU Data Sci --][ Misc Research Intern ---]                       |
             [ Math Acdmy Teaching ---][ Misc Math Edu -][ Mathnasium Instructor -------------]                             |
hobby   <----- TBD ][ Math Book Writing ----------------][ Music Production ---------]         [ Sports (mainly Hockey) --->|
school                        [TchCred][ GaTech MS CS --][ Notre Dame BS Math -------][ High School -----------------]      |
                                                                              [MathPhysNeuro SelfStudy]                     |
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             ↑ move to Boston MA                         ↑ move to Pasadena CA

Growing up in South Bend, Indiana, I always enjoyed math. I initially focused my time on sports, but once I realized that I had more talent and fun with math, I leaned into it hard. In high school I self-studied MIT's undergraduate math/physics curricula, completed two research projects at local physics labs that helped improve acoustic and optical acoustic and optical data transmission in particle detectors, worked as a Mathnasium instructor on evenings and weekends, and derived a nasty closed-form expression for decomposing a general rational expression into partial fractions (this was before I learned about the residue method).


From 2014 to 2018, I attended Notre Dame on full-ride scholarship and majored in math. At the beginning my interests were primarily academic, consisting of a crazy courseload and a self-directed project that involved involved modeling the human brain as a dynamic weighted graph. My initial approach was to abstract from first principles: I wanted to understand how the topology of biological neural networks with spike-timing dependent plasticity could be shaped by periodic stimulation. While this led to an interesting toy problem that permitted computational simulations and was mathematically solvable in a simple case, I later realized that bringing models of the brain to terms with reality would require even more experimental wet-lab work than math (which did not appeal to me). I pivoted to a top-down approach and took an internship in Los Alamos the summer after my freshman year, attempting to create an emergent phenomenon of brain oscillations by implementing spiking neurons in a deep learning model. But training a spiking neural network turned out to be an incredibly difficult task and, beyond implementing the spiking neurons themselves, the project wasn't very fruitful.

During my sophomore year I interned as a data scientist at Aunalytics, and they gave me a full-time position during my junior and senior years while simultaneously finishing up my degree. My main projects centered on churn prediction and exploratory analyses in financial services / digital news / general subscription services, plus a side project evaluating the potential of topological data analysis (which turned out to be elegant in theory but not so useful for Aunalytics's practical needs). However, I gradually realized that quantitative modeling was most valuable when paired with domain expertise, and although I was grateful to have broken into data science so early, I wasn't excited by any of the contexts in which it was conventionally applied. This was very upsetting to me because by that point I had also lost interest in graduate math and couldn't envision any other paths forward.

During this time, the only two things that gave me satisfaction were tutoring and music production. I had more talent and passion for tutoring: even while working full time in data science and finishing my degree, I simultaneously continued to work at Mathnasium on evenings and weekends just for the fun of it. So after graduating from Notre Dame in 2018, I decided to throw myself fully into tutoring. I left Aunalytics, moved to California to accompany my girlfriend Sanjana who was attending Caltech (we met as co-workers at Mathnasium in South Bend before she left for college), and enrolled in Georgia Tech's online master's in computer science (which seemed like a no-brainer for $7k).

Math Academy

Upon arriving in Pasadena, California, I took on scattered freelance work in math education: tutoring for many different agencies, developing content for several online learning platforms, teaching high school and weekend test prep, and even writing several textbooks for fun. Gradually, all my teaching and content development work converged at the same organization, Math Academy, a highly accelerated 6-12th grade math program where 8th graders took AP Calculus BC and high schoolers studied a full undergradute math curriculum. Math Academy ran on top of educational software built by the founder, Jason Roberts, a serial entrepreneur who, after developing much of Uber's foundational technology, wanted to create and commercialize the ultimate online math learning system.

I got involved at the core of Math Academy's software during the summer of 2019, when Jason asked me to develop an algorithm that would automatically create personalized assignments while leveraging effective learning techniques like spaced repetition and interleaving. It turned out that my background in computational neuroscience, data science, tutoring, and content development was perfect preparation for the job. By the end of the summer the project was a success, upgrading the software from a teaching tool to a fully automated and personalized learning system that could effectively support independent learners (without any teacher). During the 2020-21 school year (and COVID-19 pandemic) it proved to be significantly more effective than conventional instruction, and by spring 2021 nearly all of Math Academy's in-school classes were using it. Jason and I kept iterating on it the following summer, and by the 2021-22 school year we reached the point that the system was 4x as efficient as traditional in-person classes covering the same material. A bunch of cool stuff has started happening like 6th graders progressing all the way from prealgebra to AP Calculus BC in a single year. We're currently beta testing and prepping for a real launch.

Recent miscellaneous:
  • In collaboration with Jason, I also developed a special applied math/CS sequence within Math Academy's school program. It is one of the most advanced in the country. In addition to furthering the mission of Math Academy's school program, it will help inform the delivery of applied math/CS courses via Math Academy software in the future.
  • I'm moving to Boston in June 2023. Sanjana is doing her PhD there, and we've endured long-distance since early 2020. I'll be leaving Math Academy's school program, but will continue working on Math Academy's commercial product in full force.

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Thank you to the following people who have significantly impacted my life:
  • My parents - for always encouraging and wishing the best for me
  • Ken Andrzejewski and Douglas Sisk - for teaching me how to put myself out there, find research opportunities, and compete in science fairs during high school
  • Ilan Levine - for advising my first high school physics research project
  • Cari Ingram - for hiring me as a Mathnasium instructor during high school and letting me have so much fun goofing around with the kids
  • Dave Cieslak - for hiring me as a data scientist during college and sending interesting projects my way
  • Jason Roberts - for helping me find my niche after college and providing a constant stream of challenge and mentorship