AI/ML Engineer · Data Scientist · Independent Researcher
I design and build AI, machine learning, and NLP systems — and I bring an unusually wide set of questions to the work. The technical and the contemplative aren't opposites. They're the same curiosity flowing through different channels.
Custom model development, NLP pipelines, semantic embeddings, conversational AI, BERT-style architectures, and agentic systems. I've built production-grade AI systems in healthcare, cybersecurity, IoT, and education contexts.
End-to-end data science — from raw, messy sources to clustering, classification, visualization, and insight delivery. Fluent in Python-based scientific stacks, experienced with both structured and unstructured data at scale.
White papers, architecture documentation, and interdisciplinary essays. I bring genuine academic rigor — including peer-reviewed publications — to technical writing engagements across science and philosophy.
A family coordination AI built on a privacy-first architecture — using locally-running Python code rather than cloud LLMs to analyze personal data. Includes a personalized family profile engine that tailors the agent's recommendations to each household.
View project →A novel theoretical framework treating cancer through an information-theoretic lens, published in Biosystems. Bridges computational thinking with oncology.
Read paper →An exploration of how structural information is encoded in DNA sequences, proposing a theoretical framework for structure encoding that bridges genomics and information theory.
Read paper →
"I've spent my career at the intersection of intelligent systems and human meaning — building tools that work, and asking why they should."
I'm a data scientist, AI/ML engineer, and independent researcher based in Burlington, MA. My work spans from production NLP pipelines to peer-reviewed papers on quantum metaphysics and evolutionary biology. I believe the deepest engineering questions are ultimately philosophical ones — and I pursue both with equal seriousness.