Résumé
Led analysis and visualization efforts for data collected at various stages of the product development cycle at Apple including design, prototyping, manufacturing, and post-release. Wrote scripts and created tools that allowed engineers to identify core issues within minutes as opposed to days. Collaborated closely with various teams across the company as the data science and visualization lead. These teams include Industrial Design, Product Design, Manufacturing Design, Advanced Manufacturing Engineering, and Operations. Created automated reports detailing daily factory performance for a few key products. Wrote algorithms to help determine part selection that would optimize final system cosmetics. Built generic visualization tools (primarily web-based or in Processing) that continue to be used throughout the company. Architected and developed visualizations for viewing and monitoring manufacturing data in real-time. Revamped an existing product quality monitoring tool to improve usability and speed and permit more in-depth analysis of issues.
Are you actually reading this? Wow, I'm impressed! (Hi mom! Hi dad!)
On to some *utterly amazing facts that will blow your mind!*: Kangaroos can't jump backwards; Horses can't vomit; When hippos are upset, their sweat turns red; Human saliva has a boiling point three times that of regular water; "Do geese see God" is a palindrome; Recycling one glass jar saves enough energy to watch TV for 3 hours; A small child could swim through the veins of a blue whale; Birds don't urinate;
Come back next time for 40 amazing facts on Toucans! I have to get back to listing out my life in bullet points now.
Created and maintained the open-source papaya library — a collection of statistics, mathematics, and matrix manipulation related utilities — for the Processing programming environment.
Analyzed and visualized data specific to an at-the-time unreleased project with the help of various software platforms (primarily Matlab, Processing, Adobe Illustrator).
Helped develop and improve upon a model of the lumbar spine. Wrote algorithms to aid with data acquisition and interpretation of experimental data sets obtained from in-vitro testing of lumbar specimens. Ran extensive error analysis on the resulting data. Published articles in peer-reviewed journals on a musculoskeletal model of the lumbar spine , the dynamics of the intervertebral disc , Cartesian stiffness matrices, error analysis of experimentally obtained data sets , quantification of rigid body motion using quaternions , and plant growth dynamics.
Nowadays, I primarily code in R, Python, and Javascript. Processing was my first love though and I continue to be impressed by the work that they're doing.
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