Spring 2023 Capstone Projects

Learn about Texas A&M University Department of Computer Science and Engineering capstone projects completed in fall 2023 and see our sponsors.

Company Sponsors

Our spring 2023 company sponsors for capstone projects were:

Give n Share

The project built Give n’ Share, a mobile app whose main goal is to reduce waste and promote sustainability habits by providing a platform for users to give and share things they do not use or need anymore. Research area: AI, ML, NLP.

BRL-CAD Visualization

The system auto-generates beautiful concise one-page summary reports of 3D geometry models in BRL-CAD, an open-source computer-aided design (CAD) system. The report contains visual, textual, and contextual information about a given 3D model. Research Area: Graphics, visualization and computational fabrication.

Darth Vader looking at several monitors writing code.

L3Harris Vader SC

The project Vader SC auto-generates software documentation for all functions from existing code that has not been documented. Large language models (e.g., GPT-J, Llama, and Code T5) chosen by the user were used to generate source code comments. Research Area: AI, ML, NLP.

Diagram showing a “black box” function which converts biomtetrics and user files into encrypted data.

Lockheed Martin Project Speakeasy: Easy End-To-End Encryption

Painlessly encrypt and decrypt your files without the need for remembering a password or cryptographic key. The only thing you need to bring is yourself! Research area: Cybersecurity.

Title card displaying the purpose of the project, reducing noise in waveforms, as well as the class and semester, CSCE Spring 2023 Capstone Project.

Sandia Waveform Analysis Sandstone

The project created a simple and user-friendly command line tool with GUI that analyze complex waveforms related to electrical equipment, including waveform clean up (i.e., noise removal), and report generation containing statics of the user’s choice. Research Area: Data science.

College of Nursing IntelligentCHILD

A highly efficient search engine tailored to provide users with high-quality curated resources on maternal healthcare and pregnancy-related topics. The application is accessible to people without a medical background, facilitating easy comprehension of the resources presented. Research Area: AI, ML, NLP.