Eliot Shytaj

Directed a team of 9 interns to develop an AI-driven compliance dashboard supporting document upload, task tracking, and collaboration for internal audit workflows.

Built and integrated a chatbot leveraging EU AI Act standards to automate compliance checks, improving review speed and consistency across client documentation.

Engineered a Java automation script that scanned and validated over 10,000 client documents, identifying missing data and print process errors to eliminate 3+ days of manual QA work per release cycle.

Automated regression testing with Selenium and Cucumber to verify accuracy of client-facing print statements, boosting reliability and reducing release defects by 25%.

Researched Regular Expression Denial of Service (ReDoS) vulnerabilities in Snort, analyzing over 1,000 regex patterns across community and registered rule sets to identify inefficient or vulnerable expressions.

Developed a Python script to parse and batch-process Snort rule files through a Java-based ReDoS evaluation tool built by a graduate researcher, improving testing efficiency by approximately 70%.

Created a testing environment by compiling Snort from source, enabling reproducible experiments and transferring the setup to a PhD researcher for extended evaluation.

Developed and maintained a responsive website using JavaScript, HTML, and CSS, increasing user engagement by 30% through an improved user interface and experience.

Boosted client inquiries by 20% through innovative features, maintaining an average of 50 visitors per month.

Leveraged AWS for hosting and domain management, improving loading speed by 25% and achieving 100% cross-platform compatibility across desktop, tablet, and mobile devices.