Braden Everson ðĶ
Summary
Dedicated Software Engineering Intern at Cognex Corporation with hands-on experience in full stack development and embedded systems. Strong background in Rust, C, C++, with a focus on embedded systems that make a difference for the world. Passionate about roles involving embedded systems, firmware development, and leveraging Rust for high-performance, thread-safe applications. Actively seeking opportunities that align with career goals of contributing to impactful, real-world solutions in cutting-edge technology 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.
Mobile App Developer Intern
HIR Wellness Institute | September 2023 - December 2023
- Developed React Native mobile application for internal company scheduling of interns.
- Created interface between Firebase NoSQL database and JavaScript frontend.
- Created database schema depicting hierarchy of users with varying rights and access levels.
- Implemented Google Maps and Apple Maps API to create a real time map of all nearby events posted by administrators.
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
ðpinned project
Unda - Open-Source Machine Learning Library in Rust from
Scratch ð
- 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.
Star Unda on GitHub
Chromogotchi - Tamagotchi Living in a Chrome Extension
- Utilizing 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
td - Tower Defense Game in Rust ðïļ
- 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.
- Utilized TypeScript for the frontend to manage game state, render animations, and handle user inputs on an HTML5 canvas.
wunos - Rust-Based Uno Game Server ð
- 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.
Embedded Machine Learning - Predictive Heart Attack Monitor ð
- Utilized 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.
Embedded Source Code
Model Source Code
Embedded Machine Learning - Automated Plant Care âïļð§
- 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.
Embedded Source Code
Model Source Code
SiteSmith - Rust CLI Tool for Generating Personal Websites ð 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.
Source Code
Machine Learning Drones - Embedded Deep Learning ðĶū
- 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 ðŠī
- 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.