Study learning engineering
LENS — Learning Engineering for Next-Generation Systems — launches Fall 2026 inside the Johns Hopkins M.Ed. in Learning Design and Technology. Built for people moving between technical practice and learning design.
Johns Hopkins University Applied Physics Laboratory
William Gray-Roncal, PhD
Learning is the through-line — patterns in brains, in machines, and in minds. Giving everyone a chance to participate, and to thrive.
I'm a principal research engineer at Johns Hopkins APL and a faculty member at Johns Hopkins, working across defense, space, biomedical, and learning systems.
See the research For students Get in touch
- Neuro & connectomics
- AI & data
- Defense & space
- Learning engineering
- Workforce
- Public health
- ~500students mentored
- 3,009citations · h-index 21
- 9sponsored programs led or co-led
One method, six domains
The blend is the point
Learning is what connects the six: how brains encode it, how machines approximate it, how people acquire it under pressure. The method underneath is constant — systems engineering plus measurement, applied to a reconstruction pipeline, a clinical dataset, a research team, or a learner.
- Neuro & connectomics Mapping brains at synaptic scale — and building the archives that share the maps.
- AI & data Computer vision and graph analysis that scale from a laptop to a petabyte.
- Defense & space Systems engineering for national-security sponsors, from satellites to decision support.
- Learning engineering Treating human capability as something you can specify, measure, and improve.
- Workforce Cohort programs that widen who gets to do science.
- Public health The same measurement discipline, turned on clinical data.
Three ways in
Where this goes next
Do research with us
CIRCUIT, MERIT, and PISTA are cohort programs built on one premise: judge the work, not the pedigree. Roughly 500 students mentored, whose cohorts contributed to reconstructions published in Nature.
Collaborate
Sponsored research and consortium work across connectomics, petabyte data infrastructure, and the measurement of human performance — currently co-PI on NIH BRAIN CONNECTS.
Selected work
A few things worth reading
2025
2023
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Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients ★
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An Immersive Curriculum to Develop Computational Science and Research Skills in a Cohort-Based Internship Program ★
2022
All 90 publications, talks and posters → · Writing & press →