Software engineering · Machine learning · Data systems

At work   /   Languages and tools   /   AI & philosophy   /   Projects for fun

I’m a software engineer at Fannie Mae and a master’s student in Computer Science and AI at Boston University. I’ve worked as a full stack web developer, machine learning researcher, and data systems engineer.

That experience informs how I examine the mathematical, computational, architectural, and human dimensions of a problem space. I move between levels of abstraction to trace how assumptions at one level shape decisions and constraints at another. At BU, I’m deepening the mathematics and computer science behind that approach, particularly model evaluation and AI system reliability.

My work centers on the architecture and performance of data-intensive systems: reducing coupling, managing model lifecycles, and translating research implementations into maintainable production software.

I’ve led architectural rewrites, implemented custom machine learning solutions, and separated model platforms from the applications that consume them. Recent work combines parallel data transfer and solver execution in AWS with automated, LLM-assisted integration and testing as research models evolve.

I’ve worked with these across research, production systems, and personal projects:

AI connects my interest in systems thinking with questions about intelligence and agency. Agent orchestration is one practical example: how shared context, tools, feedback, and human judgment shape the behavior of interacting agents. Understanding that behavior means moving between levels of abstraction, from individual model decisions to the organization of the larger workflow.

My interests in mathematics, history, language, and philosophy have developed together over many years, alongside my engineering work. Questions about formal models lead into questions about meaning; questions about intelligence lead into questions about agency and the social and historical contexts that shape those ideas.

I read Immanuel Kant, Georg Wilhelm Friedrich Hegel, Alfred North Whitehead, their critics and successors, and other cross-disciplinary thinkers whose work serves as a lightning rod for fundamental questions about knowledge, nature, freedom, and experience. Those questions spill over into everything else, from how I understand a technical problem to how I make sense of ordinary life.

These are works in progress, mostly growing out of things I wanted to use myself.

concept-relay · Learning from conversations
A local-first companion that turns concepts from AI conversations into editable flashcards, linked back to the evidence in the original conversation. It combines local model inference, a searchable concept library, and review before export.

discogs-helper · Records and discovery
Imports collection data and gathers Discogs marketplace listings to help organize a record collection and find new music on physical formats. Vue/TypeScript, a Fastify API, and browser automation support filtering and ranking listings.

homelab-hometown · A town for a homelab
An interface-builder concept for managing locally hosted software through a 2D, interactive, multiuser town. I’m exploring what that spatial metaphor could make easier to understand and use.

vinyl-beatmatch · A closer look at DJ practice
An audio-analysis prototype that captures turntable or mixer inputs, displays waveforms and tempos, and assesses whether two streams are beatmatched. Session history and a local fingerprint catalog help recognize tracks and review practice sessions and sets.