Projects
EECS 473: Advanced Embedded Systems
For my senior capstone course project, my team and I created an automated aquarium monitoring and feeding system.
The system could monitor water temperature and pH and automatically feed a configurable number of fish, as well as control tank lighting.
All monitoring data and manual controls were available from a web application.
I was in charge of designing the schematics and layout for the custom PCB that our tank would run off of.
TechLab@MCity Fellowship - Adastec
While working with Adastec, a level 4 autonomous bus company, I implemented a CNN (Convolutional Neural Network) model
from a research paper titled "CNN-Based Lidar Point Cloud De-Noising in Adverse Weather". The model was able to take
Lidar point clouds filled with noise from rain or fog, classify the points as either valid, rain, or fog, and remove the
noise resulting in a clear point cloud image. Adastec intends to use this technology in their autonomous bus software stack.
EECS 442: Computer Vision
For my final project, my team and I created a CNN (Convolutional Neural Network) model that would
recognize the letters signed in ASL through a video format. The model would take in a sampling of the
most recent video frames and make a predictaion based on the sign and movement found in them.
EECS 373: Intro to Embedded Systems
Throughout labs and a final project, my class partner and I created an embedded system
based robot that was capable of navigating a maze in search of a light source. The navigation
algorithms worked based on a timer and interrupt system. The robot could also be
controlled wirelessly with a remote and display pertinent data on an onboard LCD screen during either
autonomous search or controlled modes.