John Holler

Product Engineer

Personal Info

email
jholler423@gmail.com
telephone
419-787-3325
website
johnholler.com
github
github.com/johnholl

Skills

Frontend
React · React Native · Redux · Functional Components · HTML · CSS
Backend
Express · Websockets · Django · Flask · MongoDB · MySQL · Firebase
Machine Learning
TensorFlow · Neural Networks · Reinforcement Learning · Game Theory · Computer Vision
Programming Languages
Javascript > Python > Java > C > C++
Primary System
Linux
Other Skills
Teaching · Public Speaking · Reading Technical Papers · Quickly Learning New Tech
PhD mathematician, freelance software developer, and lifelong learner excited to tackle challenging, ambiguous problems. I have worked in diverse fields, including abstract mathematics, artificial intelligence, and full stack application development.

Experience

Software Developer

Freelance

2019-present
  • Created a sales management application using React Native for the Appropriate Technology Collaborative
  • Created an interactive mapping tool using React and Firebase for Ola Filter
  • Founded beunstuck.net, an all in one tool for offering appointments online using a suite of tools with Google API and ecommerce (Stripe) integrations
  • Learned numerous modern frameworks and libraries
  • Gained practical experience interacting with clients and bring products from inception to production
See Portfolio for more details

Math and Computer Science Teacher

Greenhills School

2019-present
  • Teach Precalculus, AP Calculus, and AP Computer Science
  • Developed unique projects in AP Computer Science requiring coding the infrastructure for integrating student work
  • Implemented online self-hosted homework system using WebWork by MAA
  • Mentored students in numerous independent programming projects as well as the Robotics team

Graduate Student Research / Research Intern

DiDi Labs

2017-2019
  • Implemented classical Reinforcement Learning algorithms to optimize taxi assignment
  • Designed and wrote a simulator to test cutting edge neural network approaches
  • Processed and visualized large, noisy datasets

Education

PhD, Pure Mathematics

University of Michigan

2014-2019
  • Published papers in Artificial Intelligence, Game Theory, and Algebraic Topology
  • Coursework included Computer Security, Reinforcement Learning, Linear Optimization, Probability
  • Gained practical experience writing research code in Python

Bachelors of Science, Honors Mathematics

University of Michigan

2010-2014
  • Research projects in Particle Physics, Mathematical Logic and Recursion, Cryptography
  • Graduated Cum Laude