I
Mechanistic foundation
Understand physiology
Clinically meaningful models of the systems that support muscle function and movement.
PhysiologPhysical therapist · Scientist · Educator
Building a more explicit path from evidence to clinical judgment.
I study how physiology, causal knowledge, and uncertainty can be represented computationally—then used to support transparent reasoning about individual patients.
The premise
Clinical reasoning needs infrastructure.
Scientific papers tell us about populations. Clinical practice asks what is likely true—and what to do next—for one person.
My work examines the space between those two forms of knowledge. It brings together three decades in physical therapy, clinical physiology, cardiovascular research, causal analysis, and education with an emerging program in knowledge representation and scientific AI.
How the program fits together →The program at a glance
Mechanism. Evidence. Inference.
II
Population knowledge
Represent the evidence
Curated causal knowledge with provenance, uncertainty, disagreement, and scientific review.
Models4PTIII
Individual reasoning
Ask what follows here
Patient-specific models, Bayesian inference, belief revision, and inspectable explanations.
Inference EngineExplore
A portfolio organized for reading.
01
Research program
The intellectual architecture connecting physiology, population knowledge, and individual inference.
02Projects
Implemented work, prototypes, and future-facing initiatives—described at their actual stage of maturity.
03Publications
A complete CV-derived bibliography of 99 papers, abstracts, presentations, books, chapters, and other publications.
04About
Clinical, academic, editorial, and leadership experience underlying the present research program.
Public writing
The Peripatetic Physical Therapist
Essays and reflections for a broader audience on physical therapy, education, science, institutions, and the ideas encountered along the way.
Read on Substack