Ryan Moelter

Heypenny is an iOS and Android app that helps friends split bills and trips fairly. Scan a receipt with the camera, split it with friends, and settle it later in collaborative groups. It prioritizes user experience and polish, balancing form with function.

To get the best experience, the apps are native iOS and Android apps with a Kotlin multiplatform offline sync engine. The Android app uses Kotlin and Jetpack Compose, built on a custom open-source navigation framework, and the iOS app uses Swift and SwiftUI. The GraphQL back end is Kotlin/JVM, built on a micro-framework (http4k) focused on simplicity and speed.

The app is currently available on the App Store and Play Store.

A fully native Android app for accessing all of Headspace's content. I worked on various parts, including rewriting the homepage to make it simpler and easier to use based on user feedback, improving the technical infrastructure to make it easier to maintain, and setting the technical direction on the team to help the code from multiple distinct teams blend seamlessly.

An Android client for Wealthfront's offerings, including investment management, cash account, and financial planning. I collaborated with a team of five to fifteen people over the four years I was there and worked on most parts of the app, from writing new features to updating and refactoring aging infrastructure. I also kick-started the design system team to standardize our UX and UI across our growing app on all platforms (Android, iOS, and web).

A cross-platform mobile app to help people form and maintain new habits. The app focuses on gentle positive reinforcement of a new habit rather than adding stress to an already stressful goal. It was my first foray into multi-platform development and a continuation of my experience designing for Android and iOS. It was a hobby project that was only published in beta on TestFlight and the Play Store.

For my capstone project in college, we were tasked with creating a wearable stress tracker, both the hardware and software. Our prototype relied on three biosignals that we decided to use based on the available research:

• Heart rate variability: the difference in heart rate between breathing in and breathing out
• Galvanic skin response: also known as skin conductivity, or how much sweat is present
• Electromyography: how tense particular muscles are

The prototype was a functional Arduino board with all the necessary sensors and analyzed the data through a connected laptop. I also learned a lot as the team's elected leader.