Jack Bodine

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This project is a self-hosted short-form video client I built to replace corporate-owned apps like Instagram Reels. I wanted complete control over the algorithm and the content. The objective was to turn an addictive infinite feed into something that feels more healthy and productive. The backend is written in Python using FastAPI and SQLite, and uses ffmpeg to process scraped media into encrypted HLS streams. For the frontend, I developed a native iOS app using SwiftUI and a pool of AVPlayers. This project eventually turned into three blog posts, available on this site, which describe the implementation details of the project.

iOS Development, Swift, Python, Project Management

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For my master’s thesis, I created computational models for processing neuroscience data, specifically the massive amount of video data generated by two-photon calcium imaging (2PCI). Neuroscientists use 2PCI to record neuron activity, but manually mapping out individual neurons across terabytes of video makes scalable studies impossible. Existing automated tools either only segment the main body of the cell, or struggle to process lab-grown neural organoids.

To solve this, I built an end-to-end deep learning pipeline, focusing on U-Net segmentation models that I trained to map both the cell bodies and their processes. The biggest hurdle was an extreme lack of training data, as I only had 32 manually annotated images to work with. To get the model to perform, I implemented synthetic image generation (GANs and heuristics), data augmentation, and domain transferability to investigate if a model trained on one type of brain tissue could generalize to another.

I validated the pipeline on two very different datasets provided by the University of Copenhagen. The first involved neural organoids, comparing samples from healthy patients to those with schizophrenia, which allowed me to extract and analyze specific signal features like burst rates and synchronicity. The second dataset contained in vivo recordings of mice to observe how different medications affected their neuronal behavior. The results derived from my models are currently being worked into neuroscience publications.

Machine Learning, Research, Python, Project Management

App Store Listing

Sift and Winnow are a pair of iOS apps I made to track and rank different forms of entertainment. I first made Sift, which is meant to be a goodreads-like platform for tracking video games (without any of the social features.) Pretty quickly after I made Sift, I adapted it to track any type of content and called that version Winnow. The gimmick with these apps is that you don’t get to rank the items manually, instead you answer a simple questions about which entries you prefered and the rankings are built using an elo-like algorithm.

iOS Development, Swift, UI/UX Design, Project Management

App Store Listing

Following Cinemigos, I wanted to apply the software and iOS development skills I had recently learned to the desktop. Pocket Jisho is a simple macOS application I built over the summer and have found quite useful. Although I wrote all the code in 2023, I didn’t release it until the summer of 2025.

iOS Development, Swift, UI/UX Design, Project Management

App Store Listing

During the senior year of my bachelors degree, I worked with Clark Brace to create Cinemigos, an social media app for finding and sharing movies with friends. This capstone project was one of the largest and most comprehensive projects I undertook during my undergraduate education, integrating various skills and knowledge areas.

The project involved learning Swift for iOS development, designing UIs with Adobe XD, managing databases with Firebase, and navigating the entire iOS development platform. It brought together different aspects of my education, including programming, collaboration, UI design, and machine learning.

iOS Development, Swift, UI/UX Design, Project Management

App Store Listing

After the first year of my bachelor’s degree, I tasked myself with creating and publishing an iOS app to showcase what I had learned. The result was Evil Hangman on iOS. This was a significant project, completed entirely on my own, and involved extensive research. The app was developed using Swift and SwiftUI. It is available for download on the iOS app store.

iOS Development, Swift, UI/UX Design, Project Management