Nate Roy
Athlete at Cortex Flex Inc.
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolNate Roy is a multidisciplinary athlete and neuroscientist based in New York with 11 years of professional experience blending elite sport, research, and leadership. As a push athlete for Team USA Bobsled pursuing Olympic qualification, he pairs elite physical performance with evidence-driven training methods he developed through neuroscience research at Weill Cornell and Harvard/MGH partnerships. He founded and leads two ventures, Cortex Flex and The CAPSuLe, applying organizational and scientific thinking to human development and education. Nate also tutors and instructs MCAT candidates, mentors D1 hopefuls, and has hands-on clinical experience in psychiatric and TBI research, demonstrating a rare mix of applied clinical insight and coaching ability. His academic trajectory—Cornell undergrad with top grades and ongoing PhD work at McGill—underscores a rigorous, research-first approach to optimizing performance. Less obvious: he consistently translates lab findings into practical training protocols and student curricula, bridging bench research and real-world outcomes.
12 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Neurochemistry, 4.08 GPA, Bachelor of Science - BS, Neurochemistry, 4.08 GPA at Cornell University4.12 GPA, 4.12 GPA at Oberlin CollegeDoctor of Philosophy - PhD, Neuroscience, Doctor of Philosophy - PhD, Neuroscience at McGill University
Github Skills (77)
fastapi10
python10
json-schema10
swagger10
stac10
python-client10
openapi10
async10
graphical-models10
causality10
swagger-ui10
api10
rasterio10
rest10
json10
Programming languages (5)
Github contributions (5)
n8sty/policeShootings
Sep 2014 - Jul 2015
using the R and Python languages, and publicly available data to help understand when, where, and why civilians are being shot by police officers in the united states
Contributions:33 commits, 4 pushes in 9 months
python
n8sty/dowhy
Jan 2021 - Jun 2023
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Contributions:3 pushes, 4 branches in 2 years 4 months
python-libraryfairness-mlpythonassumptionstesting
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