More About Me

Batten College of Engineering and Technology Dean's List from Fall 2023 - Spring 2026
Department of Electrical and Computer Engineering's Undergraduate Faculty Award in Computer Engineering for Spring 2026
Member of Tau Beta Pi engineering honor society

Trained a lightweight convolutional neural network to identify humans from 3D skeleton data captured by an RGB-D camera, achieving 75% recognition accuracy during live testing.
Deployed the trained network on an inexpensive Raspberry Pi 4 microcomputer that consumes under 10 W.
Implemented an asynchronous client-server pipeline that kept total identification latency below 100 ms.
Built a Qt5 UI to visualize real-time skeletons at 30 FPS and display identification results.
Developed an integrated recording and training pipeline to allow seamless dataset expansion.
Authored detailed documentation that enabled our project mentor to independently recreate our results.

Collaborated in an Agile-based team environment by attending stand-ups, writing user stories, practicing TDD, and drafting a software requirements specification.
Trained an SVM classifier to categorize documents using TF-IDF features, achieving 70% average accuracy.
Built a Java CLI application to parse PDFs, extract text, and display predicted categories.
Implemented CI/CD with GitHub Actions, build management with Gradle, and unit testing with JUnit.

Designed a MIPS-based single-cycle processor in VHDL that supports 7 instructions, 8 registers, and 512 bytes each of data and instruction memory.
Constructed an ALU that supports addition, subtraction, multiplication, and value pass-through.
Developed a data path by hand, including PC, registers, ALU, instruction and data memories, and control unit.
Built VHDL testbenches to verify the data path’s correctness, including edge cases like value overflow.