A Career Built Around a Single Question
How do organizations become more intelligent?
That question has shaped nearly every decision I've made throughout my career. It has led me through software engineering, enterprise architecture, artificial intelligence, data engineering, business strategy, university teaching, and ultimately the study of human performance and organizational psychology.
Whether designing medical devices, modernizing defense systems, developing enterprise software, teaching graduate students, or coaching athletes, I have consistently found that technology alone rarely solves complex problems. Sustainable success comes from combining sound engineering, high-quality information, effective leadership, and an understanding of how people make decisions.
Professional Philosophy
I believe that information is one of an organization's most valuable strategic assets. Software systems, databases, artificial intelligence, and analytics all depend on the quality of the underlying data and the relationships that connect it. Organizations that treat data as a strategic enterprise asset—not merely an application byproduct—are better equipped to learn, adapt, innovate, and make informed decisions.
Much of my recent work has focused on enterprise data architecture, Digital Thread, and the idea that data architecture functions as cognitive infrastructure: the foundation through which organizations represent knowledge, support collaboration, enable artificial intelligence, and improve operational performance.
Experience
Over more than twenty-five years I have led software engineering, enterprise architecture, and technology organizations across defense, healthcare, medical devices, consulting, startups, and higher education. My experience spans software development, cloud computing, artificial intelligence, enterprise architecture, data engineering, systems integration, product development, technical leadership, and strategic planning.
In parallel with my engineering career, I have served as a university instructor, engineering mentor, executive advisor, and baseball coach, experiences that have reinforced the importance of leadership, communication, teaching, and continuous learning.
Education
Ph.D. — General Psychology (Performance Psychology)- Focused on leadership, decision-making, organizational learning, and the factors that enable individuals and teams to perform at their highest potential.
- Thesis: Project Semantic Web and the Resource Description Framework (RDF). Explored semantic technologies, ontologies, and knowledge representation, establishing a foundation for today's work in enterprise data architecture, semantic layers, Digital Thread, and artificial intelligence.
- Developed a strong foundation in scientific reasoning, mathematics, systems thinking, and software engineering, providing the analytical framework that has guided my technical career.
Educational Journey
My educational journey reflects the evolution of both my career and my understanding of what it takes to solve increasingly complex problems. Beginning with a foundation in physics and computer science, I learned to approach challenges through scientific reasoning, systems thinking, and software engineering. Graduate studies in engineering expanded that perspective, culminating in research on the Semantic Web and the Resource Description Framework (RDF), where I explored how knowledge can be formally represented and shared across systems-concepts that have become foundational to today's enterprise data architecture, semantic technologies, and artificial intelligence. As my career progressed into engineering leadership, I recognized that technology alone does not create exceptional outcomes; high-performing teams do. This realization led me to pursue doctoral studies in performance psychology, deepening my understanding of leadership, decision-making, motivation, and organizational learning. Together, these experiences have shaped my philosophy that solving real-world problems requires more than technical excellence—it requires integrating engineering, knowledge architecture, and human performance to build organizations capable of learning, adapting, and delivering meaningful results.Today
Today, my work spans the intersection of enterprise architecture, software engineering, data engineering, artificial intelligence, and organizational performance. At SAIC, I lead initiatives focused on modernizing aircraft maintenance systems through enterprise data architecture, Digital Thread, AI, and aircraft-centric data models that establish the foundation for future intelligent maintenance and operational decision support capabilities.
In parallel with my professional work, I continue to pursue academic research and thought leadership through the development of white papers and scholarly publications exploring topics such as Data Architecture as Cognitive Infrastructure, enterprise knowledge representation, semantic technologies, Digital Thread, organizational learning, and the role of enterprise data architecture in enabling artificial intelligence. My long-term objective is to bridge industry practice with academic research by developing frameworks that help organizations better understand how data, knowledge, technology, and human performance work together to create intelligent enterprises.
As an Adjunct Instructor in the Applied Data Science program at the University of San Diego, I teach graduate-level data engineering and design curriculum that prepares students to solve real-world engineering challenges using modern data platforms, cloud technologies, and AI-enabled workflows. Through research, writing, teaching, and engineering leadership, I strive to help organizations build systems that are not only technically capable, but also intelligent, adaptable, and centered on the people who design, operate, and depend upon them.