I am a Computer Science graduate from the University of Arkansas - Fort Smith, specializing in Data Science and Artificial Intelligence with a minor in Mathematics. My passion lies in developing deep learning models and leveraging computer vision and natural language processing to solve real-world problems. I have experience in full-stack development, research, and the end-to-end process of developing, training, and deploying deep learning models.
University of Arkansas - Fort Smith
2020 - 2024
I pursued a Bachelor of Science in Computer Science with a concentration in Data Science and Artificial Intelligence and a minor in Mathematics. I was a member of the Artificial Intelligence Research Lab and represented the university at the MCPC programming competition for three consecutive years. Relevant coursework includes Data Structures, Algorithms, Formal Languages, Distributed Systems, Software Engineering, Database Systems, Artificial Intelligence, Machine Learning, Computer Graphics, and Deep Learning.
As a member of the UAFS Artificial Intelligence Research Lab, I contributed to projects in deep learning, computer vision, natural language processing, and cybersecurity. My work culminated in two significant projects, both of which were presented at the Undergraduate Research Symposium:
Fake Review Identification Using Deep Learning: Developed and implemented deep learning models to accurately identify and flag fake reviews in e-commerce platforms.
Automated Shoulder Surfing Attacks Using Cameras and Deep Learning: Conducted research to highlight potential security vulnerabilities by demonstrating how shoulder surfing attacks can be automated using only cameras and deep learning techniques. This project aimed to raise awareness about potential security threats in public spaces.I did a month-long contract for Zesty where I did front-end development work. I used GatsbyJS, React, JavaScript, and CSS to build responsive front-end pages for their website.
Currently developing a full-stack open-source system using Flask, MariaDB, Apache, JavaScript, Python, and PyTorch to monitor elderly individuals’ well-being and alert caregivers in real-time with a distributed system, computer vision and deep learning.
View on GitHubDesigned and implemented a survey system for academic group project evaluations with Moodle integration through a custom plugin. Utilized MariaDB, Apache, PHP, and Bootstrap for a full-stack solution.
View on GitHubDeveloped a deep learning model using Python and PyTorch to add accurate color to grayscale images with neural networks.
View on GitHub