Hello and welcome to my portfolio! I'm a software and machine learning engineer who enjoys building intelligent systems and the full-stack applications that put them to work. My most recent work spans anomaly detection, retrieval-augmented generation, and turning research ideas into reliable, production-ready tools. I graduated Summa Cum Laude from Cleveland State University in May 2026 with a B.S. in Computer Science.
A selection of projects that I chose for a reason. Each solves a problem that I believe matters, avoids well-trodden ground, and produces verifiable results during every stage of development.
Retrieval and Memory A local-first memory engine that turns long-lived personal artifacts (notes, code, images, and PDF files) into a queryable, time-aware system. Every answer stays tied to retrievable source evidence, with an explicit citation you can open and verify. Everything runs locally, with no cloud dependency by default.
LLMs and Formal Methods My senior design project done with a team of 4 CS students. We evaluated and improved how well flagship large language models (LLMs) convert natural-language mathematics into verifiable LEAN 4 code, then wrapped the method in an accessible natural-language interface for formal theorem proving.
Deep Learning Unsupervised runtime fault detection in finite state machines (FSMs). A dense autoencoder trained only on normal behavior flags anomalous state sequences, measured against a rule-based transition whitelist across three FSMs and three fault types.
B.S. Computer Science
Cleveland, OH · Jan 2023 – May 2026
GPA: 3.90 / 4.00
Languages, frameworks, and tools I use to build scalable applications and machine learning systems.
Interested in discussing opportunities, projects, ideas, or potential collaborations? I would love to hear from you!
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