Incoming full-time software engineer, August 2025

This was a 12-week software engineering internship on the Kaggle Datasets team.Using C#, my project works on a backend deployment of Kaggle architecture. Its purpose is tooptimize the pipeline that is responsible for ingesting and processing files for the creation ofdatasets, models, and competitions on the Kaggle platform. This optimization is a great helpto both the users uploading files to Kaggle and the developers working in those three areas. Inother words, the impact is felt across most of the platform. This project has required me to learn about the Google Cloud Platform, the Kaggle backend architecture, and the C# TPL Dataflow library.In collaboration with other Kaggle engineers and using internal documents and code, I was able towrite a 16-page design document that details all background information needed for a person unfamiliar with Kaggle systems to understand the project and the implementation details of the project. Within this document, I also conveyed a way to capture metrics that will show the impact of the project, code that I wrote and shipped to measure the time it takes for files to go through the pipeline,while also recording file size, file extension, and the path the file takes through the pipeline.I also took the initiative to create a document that lays out the process for adding to the data pipeline as well as the challenges I faced. This was done to make it much easier for any future developers to gothrough the same process. Furthermore, I led a bug bash for my feature, helping other engineerstest my feature with a document I wrote and through a virtual meeting. Afterwards, I demoed the feature at a Kaggle All-Teams meeting and then later put on my own presentation. Lastly, now that the feature is up and running, dataset creation times have improved by up to 51%.

• Developed an improved data representation format for OpenSim motion capture software using Python.• Created a simplified pipeline for automated bio-mechanics data extraction from the simulation's coordinate data files.• Interpolate data, apply time normalization and discrete analysis algorithms to produce a file in a simplified data visualization format.This would lower the cost of conducting research by allowing researchers to migrate from expensive proprietary software and tools to open-source software and consumer-level hardware for data collection without significant compromise on data precision.

Developed augmented reality applications using Unity, C#, and the Magic Leap 1 headset on the UM Innovate Team. My first project consisted of a brand new app made from scratch that is meant to educate caregivers about how to handle certain situations they may have with their asthmatic children. I was able to participate in a scientific study using this application, resulting in my name being published in a scientific journal. My next project was an application that is used to educate students on vector math by display vectors and vector operations in 3D space. I worked on this app Spring and Summer 2023. I was able to solve dozens of Jira tickets, add new features, design menus, directly speak with the client in weekly meetings, and create and maintain documentation for over 10,000 lines of C# code.Finally in Spring 2024, I continued to build these skills by working on an augmented reality application that was meant for use on iPads. From this, I learned the ins and outs of developing iOS applications with Unity.

Used C# to write backend services for other departments in the organization and also fully recreated an ASP.NET web application by learning Blazor, C#, SQL, CSS, and HTML. I was able to add new features to the web application as well as run background processes 50% faster.

• Configured 15 different coding projects in JavaScript • Created a 3-player online multiplayer remake of Bomberman from the ground up as a group of 3 students• Delivered a collaborative final project presentation that included a live demonstration to Google employees