Engineering leadership · Machine learning · Healthcare

I make complex systems comprehensible.

I lead engineering teams and build machine learning systems that ground their claims in sources you can check. My research sits where cognitive science meets software: measuring comprehension, then engineering for it.

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Why it matters

Working alone and unfunded in a research course, I converged on the same grounded architecture the industry landed on for explaining medical records to patients. Now I’m looking for the problems the giants won’t solve.

Read the MedLit case study →

Selected work

Work that ships with its evidence

All projects →

MedLit

Grounded health-literacy platform: FHIR records in, plain-language explanations out, at a chosen reading level, with citations. Labs are interpreted deterministically, never by the model.

Converged on the architecture the industry landed on

FHIRRAGFastAPINext.jsDocker

mat73-reader

The only Python library that reads MATLAB table objects from v7.3 HDF5 files. Reverse-engineered the undocumented MCOS format that every existing tool fails on.

752 tables decoded from a 3.8 GB research dataset

PythonHDF5pandasPyPI

Cognitive Load Dashboard

Eye-tracking based cognitive load classification grounded in Cognitive Load Theory. Random Forest pipeline with a live dashboard; paper revision in progress.

F1 0.897 against a 0.70 target

scikit-learnEye trackingFlaskResearch

The standard

Every system I ship can show where its claims came from.

Grounded retrieval instead of open-ended generation. Deterministic code paths where correctness is non-negotiable. Reading levels measured on the output, never assumed from the prompt.

Claims with receipts

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macro F1

cognitive load classifier, held-out test set

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tables decoded

by mat73-reader, the only Python tool that can

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grounded sources

behind every MedLit explanation

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LLM calls

in MedLit lab interpretation

Building something at this intersection?

I’m always up for a conversation about machine learning in healthcare, cognitive science research, engineering leadership, or the startup scene in New England.

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