Co-PI · 2023–2028
- Neuro & connectomics
NIH CONNECTS Mouse Connectome
Scaling circuit analysis and reconstruction
Research
Sponsored programs at APL, and the tools and data they produced.
Sponsored programs
Led or co-led at APL
Funded by NIH, DARPA, IARPA, and DoD.
Key Personnel · 2023–2026
- Neuro & connectomics
NIH CONNECTS High Throughput Imaging Research Grant
Key Personnel · 2018–2028
- Neuro & connectomics
- AI & data
NIH bossDB (R24MH114785)
Petabyte-scale data storage and community collaboration for connectomics and precision medicine
PI · 2021–2023
- Neuro & connectomics
BENCHMARK (NIH R01MH126684)
Community standards for high-resolution connectomics
PI · 2020–2021
- AI & data
- Neuro & connectomics
TITAN (DARPA AIE)
Low-shot learning algorithms inspired by insect neural connectivity
Technical Lead · 2017–2022
- Neuro & connectomics
- AI & data
IARPA MICrONS
Algorithms for cubic millimeter mammalian neuroscience; scene parsing methods for operator-focused environments
PI · 2017–2020
- Neuro & connectomics
- AI & data
NIH SABER (R24MH114799)
Reproducible cloud processing pipelines for neuroscience
Technical Lead · 2020–2021
- AI & data
- Neuro & connectomics
NeuroAI Engines
Translating biological neural computation to next-generation ai algorithms
Current Research
- Learning engineering
- Defense & space
Human cognitive performance
Quantitative measures of operator capability in complex operational contexts
Software & datasets
Tools and data
Infrastructure, tools, and teaching artifacts — most open source, all built to be used by someone other than their author.
Data infrastructure
- Neuro & connectomics
- AI & data
bossDB
The Brain Observatory Storage Service and Database — petabyte-scale storage and delivery for volumetric neuroscience, serving the connectomics community as shared infrastructure.
Software
- Neuro & connectomics
- AI & data
DotMotif
A query language and engine for finding subgraph motifs in connectomes — ask structural questions of a brain network without writing a traversal.
Curriculum & datasets
- Workforce
- Neuro & connectomics
NeuroTrailblazers
Training and mentorship for nanoscale connectomics: ten technical units from electron-microscopy basics through NeuroAI analysis, a curated journal club, and hands-on work against real datasets including MICrONS and FlyWire. Built for three audiences at once — students, the mentors supporting them, and programs adopting the model.
Software
- AI & data
- Learning engineering
ExpertTrace
An AI mentor working from an operational knowledge corpus — symptom to fault to corrective action, plus the tacit cues experts never write down — that probes a learner through a live scenario at a chosen level of expertise. It assesses on unfamiliar scenarios, because repeating a known pattern is not transfer.
Software
- Learning engineering
Calibrated Judgment
Grades an argumentative essay twice — once from the finished text, once from the transcript of the AI dialogue behind it — and reports the gap between them. Every score is anchored to a verbatim quote, and criteria a model should not settle alone route to the instructor, whose override becomes calibration data.
Teaching tool
- Learning engineering
- AI & data
LLM101
Next-token prediction explained at five depths, so a reader can take the level they can actually use rather than the one the author found interesting. The build is written up beside it as a worked example of designing for a capability instead of for coverage.
Sandbox
- AI & data
POP
A soap-bubble physics sandbox: shape a wand, watch the film billow and deform in moving air, then run the whole thing backwards — fit an ellipse to a photo of a real bubble and read the wind speed back out of the shape it left.
Community
- Learning engineering
Learning Engineering Commons
A shared reading list, tool directory, practice library, events calendar, and community roster for people doing learning engineering.
Recognition & service
Selected awards and service
Awards
- Nexus Convening Award, Johns Hopkins University (2024)
- Light the FUSE Award, JHU Applied Physics Laboratory — Team award, Trailblazer CIRCUIT team (2020 awards cycle) (2021)
- Fast Company World Changing Ideas — finalist, CIRCUIT, education category (2020)
- REDx Imagine Award, JHU Applied Physics Laboratory — AI and connectomics (2018)
- Hart Prize Award for Best Research Project, JHU Applied Physics Laboratory (2014)
- Outstanding Young Alumni Award, Greeneville City Schools Education Foundation — CORE Champions Awards, cited in part for co-founding the APL College Prep program (2017)
- Volunteer of the Year Award, Howard County, Maryland (2014)
- Diversity Leadership Award, Johns Hopkins University (2009)
Service
- Co-organizer, AI Synergy Summit, Johns Hopkins University (2025)
- Workshop Moderator & Presenter, Toward Agentic and Multimodal AI Systems, AAAI (2021)
- Symposium Organizer & Presenter, Toward Petascale and Exascale Connectomics, BRAIN Initiative Meeting (2020)
- Workshop Co-organizer & Moderator, BigNeuro 2017: Analyzing brain data from nano to macroscale, NeurIPS (2017)
- Workshop Organizer, BigNeuro 2015: Making sense of big neural data, NIPS (2015)
Working together
Collaboration
Open to sponsored research, consortium roles, and co-investigator work across connectomics, large-scale data infrastructure, and the measurement of human performance. Reach him at wgr@jhu.edu.