Creative technologist with research and interaction-design depth
I make and study tools that help people understand complex systems, with a particular interest in human-AI interaction, creative software, and embodied interfaces.
The short version
My work crosses interaction design, UX research, accessibility, human-AI systems, and music technology. I prototype in code with AI coding tools when a working interaction can answer the question better than a static mockup, and I stay fluent in Figma when fidelity or collaboration calls for it.
The strongest evidence is specific: the Philz mobile study included 15 participants across five facilitator groups; the NPR audit covered 56 WCAG criteria and recorded tool-specific findings; SensorSynthFM is an in-progress physical-device capstone; and the Pittsburgh Ableton User Group has been running for a decade.
How the pieces connect
Music, community work, documentary research, UX, and AI systems are not separate identities. They are different ways of learning what a system asks of a person, then making the important boundary clearer.
Music, community, UX, and AI systems
Each domain supplies methods and constraints for the next. The connection is practical, not a destiny story.
Music taught pattern recognition. Community work taught me where people get stuck. UX gave me a way to see that clearly. AI systems design is where those threads meet.
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What the MS changed
I entered the program wanting to make cool technology. Research taught me that observation, interviewing, and analysis are how ideas are discovered before design begins. That shift is why I treat research as part of making, not a handoff that happens after the interface exists.
The program also clarified my breadth. UX is a tool in my toolkit, alongside writing, music, systems thinking, and code. I am building depth in interaction design and research without pretending that one job title describes the whole practice.
Choose the method and prototype fidelity that answer the question. More interface is not automatically more evidence.
How can a tool make people more productive, efficient, creative, and happier while keeping human judgment visible?
Before the MS
Documentary research shaped how I work with uncertainty. In title work, I traced ambiguous property and mineral-ownership records through documents, maps, GIS resources, and probate research, then reported the state of the evidence to stakeholders. I do not relabel that work as user research; I carry forward the habits of source discipline, uncertainty, and clear reporting.
Earlier work also included water-quality sensing, live-event rigging and lighting, print production, and gallery work. Those are supporting threads in a creative-technologist practice, not a claim of engineering specialization. Music remains a central domain: I produce electronic music, DJ, and treat curation as part of the practice. I have led the Pittsburgh Ableton User Group since 2015.
How I work now
I learn the domain, learn the users, and make the decision boundary visible. My English-writing and music background help me notice language, timing, and creative intent. My UX training gives those observations a research method.
Clarence is the public name for my long-running AI collaboration system. AI tools contribute code and drafts; I retain authority over product decisions, evidence gates, and public claims. The site discloses where assistance matters because authorship and accountability are part of the design problem.
Every problem has a solution. The work is finding the real problem first.
What is next
I expect to complete the Kent State MS in December 2026. I am pursuing roles where research, interaction design, human-AI interaction, and creative tools can inform a real product decision.