Before getting into the details of this project I would like to add some supporting context. This project had to do with the topic of trafficking in all forms. The idea was to utilize natural language processing models to analyze conversations between potential traffickers or their associated organizations and identify common trends in their language. Contrary to previous efforts of this nature we were specifically discouraged from training our models on preprocessed data. For one gathering preprocessed data is exceptionally difficult and on top of that it is known that traffickers will almost never refer to their actions in plain text and will instead use coded language to communicate. This is where my project comes in. I was tasked with creating a tool that would be able to quickly sift through conversational data and pick out word phrases that are used at some frequency in the data. Next, the tool would need to display this information in an intelligible manner which was achieved through the use of Elasticsearch and Kibana. The tool was designed to be user-friendly and efficient, providing a powerful resource for analysts to identify potential trafficking activities and patterns in conversational data. A supporting server was created using Flask which housed our models and posted their output to our Elasticsearch instance. My team and I used docker containers to ensure that our project was easily deployable and scalable. By the end of my internship we were able to present a working prototype of our tool to our leads and they were very pleased with the results.

Collaborated with a dedicated team to author a comprehensive research paper for FEMP, focusing on the security risks associated with integrating cloud architectures with IT/OT infrastructures in federal facilities. This research serves to provide critical insights and recommendations to enhance the cybersecurity posture of federal energy management systems.

Served as the lead software developer for a project with the United States Army, creating a game using the Next.js web framework. The game simulated various cyber attack scenarios, providing an engaging platform for users to develop and test their problem-solving skills in real-time, enhancing the Army's cybersecurity training and readiness.

Leveraged my proficiency in VMware vSphere administration and PowerCLI scripting to automate routine tasks and streamline operations. Successfully deployed over 10,000 machines per semester, showcasing my strong capabilities in managing large-scale virtual environments. Implemented effective resource allocation strategies to optimize cloud infrastructure utilization, supporting approximately 1,000 students per semester. Ultimately my efforts contributed to an improved learning experience for students at my university.

Instructed high school students in digital forensics fundamentals, covering topics from custom steganography capture-the-flag challenges to using forensic tools like FTK and industry-standard tools like Magnet AXIOM. Created interactive scenarios and environments using Raspberry Pi 4s and virtual environments through Cyberlab, providing students with hands-on experience in digital forensics.

Served as an instructor at the NSA's GenCyber Summer Camp, where I taught Python programming to 250-300 Girl Scouts and high school teachers over the course of one week. I designed engaging lessons on fundamental programming concepts, empowering students with the skills necessary to develop programs that control and fly DJI Tello EDU Drones through a custom training course.