PROJECT 01
MLB Machine Learning
Machine learning system designed to predict the probability of a batter reaching base using MLB player and pitcher statistics collected through the MLB Stats API.
Computer Science & Engineering
Computer Science and Engineering graduate building software and intelligent systems that bridge the gap between code and the physical world.
01 / About
I'm a Computer Science and Engineering graduate interested in software engineering, robotics, embedded systems, and machine learning.
I enjoy working at the intersection of hardware and software — whether that means debugging a robotic system, developing machine learning models, programming embedded devices, or building software applications.
My approach centers around experimentation, systematic debugging, and turning ideas into systems that actually work.
02 / Projects
Machine learning system designed to predict the probability of a batter reaching base using MLB player and pitcher statistics collected through the MLB Stats API.
Embedded baseball umpire assistant combining pitch timing, count tracking, physical buttons, LED indicators, and haptic feedback using an ESP32 microcontroller.
Machine learning project analyzing genetic data related to traumatic brain injury, including model development, experimentation, and integration into a larger application.
Robotics development involving ROS2, navigation, sensor integration, coordinate transforms, localization, debugging, and hardware/software system validation.
03 / Skills
Python, C++, C, Git, APIs, Object-Oriented Programming
ROS2, Nav2, TF transforms, localization, sensor integration
Scikit-learn, TensorFlow, Pandas, classification, data processing
Linux, Docker, ESP32, embedded development, debugging
Yes, this website is running on a microcontroller.
Instead of deploying this portfolio to a traditional web server, this site is stored in flash memory and served directly from an ESP32 microcontroller running an HTTP server over Wi-Fi.
04 / Contact
I'm interested in opportunities involving software engineering, robotics, embedded systems, machine learning, and engineering teams building real-world technology.