Frank Fang
Teaching Assistant - EECS 498-009 (Bayesian Methods For Machine Learning) at University of Michigan
Newton, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolFrank Fang is a software engineer and graduate student at the University of Michigan with eight years of hands-on experience building full-stack applications and teaching foundational CS topics. As a TA for Bayesian Methods and Discrete Mathematics he blends rigorous academic training with practical engineering, having interned at Capital One and Golub Capital and worked as a software analyst and ITS consultant. He specializes in React/React Native and Vue.js front-ends while grounded in data structures, algorithms, and end-to-end workflows, enabling him to move quickly from prototype to production. Based in Newton, MA, Frank is motivated by using software to fix everyday frictions and tackle long-term problems, and brings the uncommon combination of classroom instruction experience plus real-world fintech and consulting development.
8 years of coding experience
2 years of employment as a software developer
High School Diploma, High School Diploma at Newton North High SchoolMaster of Science - MS Computer Science, Master of Science - MS Computer Science at University of Michigan
Github Skills (12)
sdk10
java9
wechat9
adp8
music7
cp6
react5
borrowing2
typescript1
nextjs1
mongodb1
nodejs1
Programming languages (5)
Github contributions (5)
frank920120/TSpace
Jun 2018 - Jun 2019
Contributions:53 pushes, 6 branches in 1 year
frank920120/react-portfolio
Sep 2018 - Jun 2019
Personal Reactjs website includes all my side projects
Contributions:24 pushes, 1 branch in 9 months
reactjsreactreactjs-websiteside-projects
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