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About

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.

§Interactive map

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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.

A working principle

Choose the method and prototype fidelity that answer the question. More interface is not automatically more evidence.

A standing question

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.