Cybersecurity Research Team Lead, Upland IN
- Performed cybersecurity networking research and analvsis for Taylor University on behalf of Lockheed Martin Advanced Technology Labs

- Adversarial Security Research: Conducted cybersecurity research using adversarial and defensive methodologies to evaluate system behaviors, security assumptions, and resilience within controlled environments.

- Traffic Interception and Analysis Tooling: Applied industry-standard tooling (Wireshark, mitmproxy, Apache, OpenSSL, Frida) to observe, instrument, and analyze network communications as part of security validation and research workflows.

- Secure Protocol and Trust Model Evaluation: Studied and tested secure communication concepts—including TLS workflows, certificate trust chains, and encryption boundaries—to understand potential failure modes and defensive next steps.

- Research Leadership and Technical Oversight: Led a student research team, guiding technical exploration, ensuring documentation, validating approaches, and ensuring work remained compliant with nondisclosure and ethical research constraints.

- Documentation and Stakeholder Reporting: Produced high-level technical documentation and delivered briefings that translated adversarial research insights into defensible, non-sensitive findings for industry stakeholders.

Data Scientist for Taylor University on behalf of Kratos Defense, Upland IN

- Project objective: Determine a machine learning model that minimized false positives and verified the company's current method for identifying potential paths for intersecting courses for client satellites based on the data provided.

- Collaborative Model Architecture Development: Worked closely with senior leadership to validate problem framing, iterate on model architecture decisions, and ensure alignment between client requirements and machine learning implementation strategies.

- Model Analysis and Profiling: Implemented and evaluated multiple machine learning approaches—including K-Means clustering, Isolation Forests, and Convolutional Neural Networks—to characterize data distributions and identify anomalous behavioral patterns.

- Data Normalization and Preprocessing: Designed and executed data cleansing, transformation, and normalization workflows to convert raw client datasets into model-ready inputs consumable by multiple machine learning architectures.

Full Stack Developer for PocketDorm, Upland IN
- Designed and implemented full-stack RESTful API, database connections in postgreSQL, and dynamic functionality with Vue.js
- Presented functioning web app to peers showcasing the range of work completed
- Web application was functional within 2 months
- Learned new technologies on the fly and adapted to rising bugs and issues in the codebase

Front-End Developer for Canary, Waltham and Williamstown MA
- Translate client mockups into functional web pages using: HTML/CSS and JavaScript
- Clearly and effectively communicated with clients and team members
- Exposure to development with unfamiliar technologies, such as Flutter and Yarn