Braden Everson ðŸĶ€

Summary

Dedicated Software Engineering Intern at Cognex Corporation with hands-on experience in full stack development, systems programming and embedded systems. Strong background in Rust, C, Zig, and Go with a focus on solving challenging problems in the world of systems programming. Passionate about roles involving embedded systems, internal systems, and high-performance, mission critical applications in unique areas of focus. Seeking opportunities that align with career goals of contributing to impactful, real-world solutions in unique fields.

Work Experience

Embedded Software Engineering Intern

Cognex Corporation | May 2024 - Current

  • Researched and integrating Rust into a large CMake-based C++/C codebase, replacing an in-house HTTP server implementation responsible for multiple user-facing crashes due to memory related issues.
  • Utilized the Corrosion crate and cxx for seamless C++ and Rust interoperability, ensuring smooth integration into the existing codebase.
  • Leveraging Rust's memory safety to architect a robust and crash-resistant HTTP server, improving system stability while maintaining performace deltas.
  • Implemented WebSocket upgrade protocols in Rust, enabling more modern features within the server.
  • Utilized asynchronous Rust for thread-safe, optimized server management, ensuring efficient handling of multiple connections.
  • Developed and executed unit and integration tests in both Rust and C++ to validate compatibility with existing FFI consumers.
  • Reported daily findings and progress to scrum team of engineers.

Full Stack .NET Developer Intern

FitX On Demand | January 2023 - August 2023

  • Developed cloud-based IoT solution for remote access QR codes that can scan into fitness content.
  • Implemented secure zone identifier that bans video access if scan location is out of range from the designated hotel/gym.
  • Leveraged AWS S3 buckets to host video content securely with limited endpoints open.
  • Developed data visualization through QR code scan location statistics on a map along with dynamic QR code disabling based on how much variety these scan locations carried.

Full Stack .NET Contract Developer

BrightBean Labs | November 2020 - January 2023

  • Developed Asp.Net web applications and Xamarin Forms mobile applications for clients seeking unique software solutions in the .Net space.
  • Developed Denver Health DHREM scheduling platform: an Asp.Net built application providing continuously integrated scheduling services in real time for Denver Health resident interns.
  • Used Xamarin forms and MVC architecture to develop an IoT mobile solution for smart truck engine warmers that could be dynamically controlled through the app.

Projects

📍pinned project
MaoLang - Interpreted Language with Randomized Syntax Rules

  • Inspired by the card game, created an interpreted language with dynamic syntax rules that change based on the Sha256 hash of the file being interpreted (as an April fools joke)
  • Implemented if/else conditional branching, printing, variable assignment and reassignment, while and for style loops and primitive types including booleans, floats and strings
  • Created dynamic rules that affect if parenthesis are required and what is necessary to end a statement (;, 'done', or '.')
  • Managed to actually generate a few working Mao scripts
GitHub Repo

📍pinned project
Page Rank and TUI Search Engine from Scratch

  • Implemented the PageRank algorithm from scratch to analyze and rank web pages based on their link structure
  • Created a basic linear algebraic type system with Matrix operations tied directly to type (i.e. only stochastic matrices can get a steady state solution)
  • Created a web crawler that stores sites and all links they hold
  • Constructed a graph based interpretation of the site crawling that could be transformed into a stochastic matrix plus bias
  • Wrapped this entire process into a TUI web browser application that performs the algorithm upon search
GitHub Repo

Chalk - Calculator interpreter with discrete math operations and graphing capabilities

  • Created a top down LL parser for mathematical expressions
  • Implemented branching statement types including simple math evaluations, function calls, and variable assignments
  • Compiled to WASM to create a graphing calculator backed with Chalk as the primary engine
  • Created a simple terminal REPL for evaluating quick expressions (helping me with discrete homework)
  • Implemented discrete math operations such as prime factorization, GCD and LCM from scratch for use in the engine
GitHub Repo
Online Graphing Calculator

Miami - MIDI Parser and Generator

  • Created a zero dependency MIDI file reader capable of representing the format through layered structures
  • Using an abstract interface/trait based system, created a modular means to error correction during the parsing process
GitHub Repo

Chromogotchi - Tamagotchi Living in a Chrome Extension

  • Using GoLang, created a virtual pet chrome extension with a mongodb managed state
  • Developed websocket listener server in Go that could interact with a pet's state by feeding, playing with, and putting to sleep
  • Created lightweight Chrome extension that communicates with Heroku-hosted Go server to display the pet directly in the browser
GitHub Repo

td - Tower Defense Game in Rust 🏗ïļ

  • Developed a real-time, WebSocket-enabled tower defense game with a focus on multiplayer interactions.
  • Implemented a WebSocket server in Rust to handle real-time game state synchronization across multiple clients.
  • Designed an asynchronous server flow optimized for performance and low latency in a multiplayer environment.
  • Used TypeScript for the frontend to manage game state, render animations, and handle user inputs on an HTML5 canvas.
GitHub Repo

wunos - Rust-Based Uno Game Server 🃏

  • Developed a WebSocket-based server for playing Uno, written in Rust to ensure high performance and low latency.
  • Implemented the game logic, including rules enforcement and turn management, in a scalable, event-driven architecture.
  • Created a robust system for managing player connections, game state, and real-time interactions.
  • Integrated with a custom WebSocket client to provide a seamless multiplayer Uno experience.
  • Developed an intuitive and charming TUI for playing Uno directly from the terminal.
GitHub Repo

Unda - Open-Source Machine Learning Library in Rust from Scratch 🌊

  • Led the development of the Unda machine learning library in Rust, designed for efficient execution of machine learning workloads.
  • Engineered an intermediate API for constructing neural networks using a sequence of computation nodes within a custom compute graph.
  • Integrated XLA bindings in Rust to dynamically compile and optimize compute graphs for accelerated execution.
  • Developed a high-level API to facilitate the creation of supervised machine learning models, with ongoing work on unsupervised and generative models.
  • Unda achieved 4th place in the 2024 MSOE ROSIE Supercomputer Challenge, demonstrating its effectiveness in large-scale ML tasks.
Unda was a part of the 2024 MSOE ROSIE Supercomputer challenge and ranked 4th place overall!!
Star Unda on GitHub

Embedded Machine Learning - Predictive Heart Attack Monitor 💓

  • Used the Unda library to train a dense neural network on the Heart Attack Analysis Prediction Dataset from Kaggle.
  • Achieved a 96.08% accuracy rate using a model with approximately 512 parameters.
  • Exported the trained model as a custom .unda file for embedded use, enabling real-time inference on an ESP32-based circuit.
  • Developed firmware in Rust for the ESP32, integrating peripherals such as a heart rate sensor and LEDs to signal model predictions, housed within a custom 3D-printed case.
This project was showcased at the 2024 MSOE ROSIE Supercomputer challenge and ranked 4th place overall!!
Embedded Source Code
Model Source Code

Embedded Machine Learning - Automated Plant Care ☀ïļðŸ’§

  • Leveraged the Unda library to develop a predictive model trained on sun exposure, soil moisture, and time since last watering to automate plant care.
  • Designed and integrated an ESP32-based embedded system that controls a water pump, moisture sensor, light sensor, and servo motor for plant care automation.
  • Trained a model with over 350,000 parameters, optimized using a supercomputer and exported as a custom .unda file for embedded deployment.
  • Implemented firmware in Rust for the ESP32, enabling the system to autonomously manage watering and shading based on model predictions.
This project was showcased at the 2024 MSOE ROSIE Supercomputer challenge and ranked 4th place overall!!
Embedded Source Code
Model Source Code

SiteSmith - Rust CLI Tool for Generating Personal Websites 🛠ïļ

  • Developed SiteSmith, a Rust-based CLI tool that automates the generation of personal websites using JSON-formatted project and work experience data.
  • Implemented features for parsing JSON data and generating HTML websites from customizable templates.
  • Published the tool on Cargo, making it publicly available for developers seeking to automate the creation of personal websites.
This website was generated using SiteSmith!
Source Code

Machine Learning Drones - Embedded Deep Learning ðŸĶū

  • Developing and implementing an autonomous drone capable of responding to hand signals using embedded deep learning algorithms.
  • Designed and trained a convolutional neural network for computer vision and path decision-making, enabling dynamic flight pattern adjustments.
  • Created a lightweight embedded Rust library to parse precompiled model weights and biases, enabling on-device inference with minimal resource consumption.
  • Developed a custom file format for compact storage of machine learning models, optimized for memory-constrained embedded systems.

Senior Capstone - Smart IoT Gardening Systems ðŸŠī

  • Developed a smart gardening system that autonomously monitors and maintains plant health through IoT-enabled sensors and actuators.
  • Integrated soil moisture, temperature, and light sensors to dynamically adjust watering schedules and alert users to potential issues.
  • Connected the system to a mobile app, providing real-time data and remote control over the gardening environment.
  • Leveraged machine learning algorithms to predict optimal watering times and amounts, enhancing garden management efficiency.