Contract work based around supporting and building UI for an AI+AR computer vision physical therapy app. Developed algorithms for manipulating, refining and rendering 3D skeletal representations and transforming them based on user input, alongside the relevant UI, menus, and code architecture for pathing that data to and from a reactive backend (using RXSwift and Combine). Also was the primary developer on a full API integration with the healthcare data provider AthenaOne, a particularly difficult challenge considering how opaque healthcare data is and how difficult it is to comply with security and privacy regulations such as HIPPA.

Worked as the primary point of contact for two of the company’s biggest contracts. I primarily serviced bugfixes, did long term feature development, expanded documentation, and was the main dev behind a push to modernize the codebase from ObjC to Swift.

iOS developer for a white-label ordering app used at international companies like Chipotle and KFC AU. Involved UI implementation, API work, documentation, and backend work with payment services, done in Swift. Supervised my team for six months as the senior developer after everyone with more experience left, so I wound up with management and critical development experience even as a fairly inexperienced hire.

I cofounded and worked as an instructor at what was initially Asheville School's app development camp, and later became a startup called Swift App School. I wrote and designed projects for a the curriculum, then taught it to students. For this purpose, I developed a game each year and wrote a tutorial book which was given to the campers, then stepped through the creation process over the last two days of the camp. We used Swift and SpriteKit.

I worked with the ATSDR and a research team from Georgia Tech to develop an application that parses atmospheric pollution data from low-cost sensors around the United States and helps display and analyze this data for use by researchers and eventually the general public. This is part of an initiative to replace extremely high-cost sensors with lower cost ones implementable by the general public. We used the R programming language and the 'openair' library to accomplish this.

I worked with the MediaQ team at USC to help develop RSA/AES based cryptography systems for their app. I also helped develop the initial phase of a neural network based pollution mapping project, and helped test alpha versions of the main MediaQ app.