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Human-Systems Engineer | AR/VR | Humam-Autonomy Teaming | UAV Swarms | Aviation Enthusiast
An experienced researcher with a demonstrated history in research design and statistical analysis. Skilled in human factors engineering, data analysis, research design, artificial intelligence, and cognitive task analysis. A private pilot with a master's degree in Industrial and Organizational Psychology from the University of West Florida and researcher of explainable artificial intelligence (XAI) at the Institute for Human and Machine Cognition (IHMC). Currently a Ph.D. candidate in Human Factors Engineering at Virginia Tech.
Virginia Tech
Doctor of Philosophy - PhD, Human Factors Engineering
January 1, 2018 – January 1, 2021
University of West Florida
Master’s Degree, Industrial and Organizational Psychology
January 1, 2015 – January 1, 2017
University of West Florida
Bachelor’s Degree, Psychology
January 1, 2011 – January 1, 2015
Naval Surface Warfare Center Dahlgren Division
System Engineer
August 1, 2023 – Present
Dahlgren, Virginia, United States · On-site
Virginia Tech
Graduate Research Assistant
August 1, 2018 – August 1, 2023
IHMC
Artificial Intelligence Researcher
March 1, 2017 – August 1, 2018
Pensacola, Florida Area
University of West Florida
Graduate Admissions Assisstant Coordinator
August 1, 2015 – September 1, 2017
Building and Deploying Deep Learning Applications with TensorFlow
June 24, 2026 – Present
Learning Python
June 24, 2026 – Present
Private Pilot
Federal Aviation Administration
June 24, 2026 – Present
TensorFlow 2.0: Working with Images
June 24, 2026 – Present
Agile Project Leadership
June 24, 2026 – Present
Remote Pilot (Drone)
Federal Aviation Administration
June 24, 2026 – Present
Getting Started With Music Theory
Coursera
June 24, 2026 – Present
Python Data Analysis
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily academic and research-oriented, with a focus on human factors and explainable AI. While this aligns with certain aspects of ML engineering, the lack of diverse industry projects or team-based software development experience might indicate a different cultural fit than a typical product-focused ML engineering team. The breadth of skills is primarily academic and theoretical, with some foundational technical certifications.
Soft Skills & Operational Fit
The candidate's academic background and research experience suggest strong analytical, problem-solving, and critical thinking skills. The role as Graduate Admissions Assistant Coordinator implies communication and organizational abilities. However, specific operational fit for a fast-paced, production-oriented ML engineering role is not explicitly demonstrated through project work or detailed job descriptions.