Gig-economy platforms — Uber, Lyft, DoorDash, Instacart, Amazon DSP, and many smaller ones — share a deep operational problem: they need to evaluate the performance of large numbers of independent workers using objective data, but the data is full of factors the worker cannot control.

A pattern I have seen in nearly every company I have worked at, regardless of size or sophistication: somewhere in the engineering org, there is a critical data pipeline that is “automated” only in the loosest sense. An engineer runs a script. The script does some things. Sometimes it works. Sometimes it produces malformed output and somebody has to spend two hours figuring out what went wrong, manually cleaning up, and re-running.

One of my favorite algorithms in graph theory is Union Find. It is a beautiful algorithm for tracking disjoint sets. A disjoint set is a group of nodes in an undirected graph that are all connected to each other through some path, but disconnected from any node outside the set.

I’ve been working full time since 2020, and it’s been 5 years in my professional career. I’m currently a software engineer at Amazon, and before that I worked at a startup. If you count my college years, when I interned at PayPal, I’ve been involved in building software for 8 years.

There’s a huge difference among a startup, large corp and academia and I wanted to share some of my experiences.

ICPC stands for International Collegiate Programming Contest. It is the largest competitive programming (CP) competition among the universities of the world.

We started a senior design project titled “Artificial Intelligent Requirement Analysis Tools”, an yearlong project with Collins Aerospace.

I’m excited to announce that Primer Server we developed at Vollbrecht Lab is finally up on the Iowa State website.

I presented a poster about Primer Server at the National Conferences on Undergraduate Research at University of Central Oklahoma last week.