Developing a vision system to autonomously detect and classify artifacts in large outdoor environments using AI and computer vision.
It's been a pleasure helping out!
In the spring of 2024, I was e-mailed by the head of the Academic Success Center at Bradley University to see if I would be interested in the opportunity. What a great way to keep my skills sharp! I tutored for every Computer Science and Math class we offered.
I love spreading my passion for Computer Science and Math, and am grateful for the opportunities I had to help students succeed in their academic journeys.
Automated data entry, developed COBOL programs for IBM-i systems, and streamlined accounting workflows to boost productivity. I saw a lot of opportunity for automation at this job, just like last year's internship at Keypath Education.
During my undergraduate studies, I led the development of a low-cost thermal camera system aimed at providing businesses with an affordable thermal imaging solution, retaining essential functionality at a fraction of the cost of traditional systems. Thermal cameras typically cost thousands of dollars, making them prohibitively expensive to many organizations that may need them for practical use. I designed the necessary experiments to collect the data needed, became certified as a drone pilot with the Federal Aviation Administration, flew the team’s drone to collect the data, designed a related Convolutional Neural Network to process the data, and evaluated the overall performance of the new technology. The resulting model, trained on 96,000 examples and tested with 24,000, achieved an average percent difference of 3.14%, 4.60%, and 3.55% across the RGB channels. This project was sponsored by Blue Roof Labs and Bradley University.
Placed 2nd in a regional programming competition against over thirty teams as "The Dirty Bit", partnered up with Ian Wilkey. We were allowed three people on a team, yet we were extremely close to 1st place! All five algorithmic problems were solved under the given time constraints.