My work operates at community and agency scale — not the project level. What follows is a view into the domains I work in, the problems I solve, and the capabilities I bring. Specific program details remain appropriately confidential where required.
Vast amounts of transit data exist in the public domain — ridership, on-time performance, accessibility metrics, funding flows. Almost none of it is synthesized into a view that actually serves the decision-makers who determine how agencies operate. I'm building the architecture and analytical frameworks to change that: centralizing disparate data sources, defining community impact metrics that sit alongside financial ones, and translating the output into formats that governance-level stakeholders can act on.
The animating question: what would transit policy look like if it were optimized for the communities it serves, rather than the balance sheets of the agencies running it?
Building AI/ML strategy and data architecture for the Hypersonics community — a domain with reach across Navy, DARPA, and NASA programs that generates enormous volumes of ground test, flight test, and modeling & simulation data. The challenge is not collecting data; it is making it retrievable and useful at the speed the mission demands.
Delivered a RAG-enabled system for the Navy HyperLink program ingesting hundreds of gigabytes of test and M&S data — reducing analysis timelines from months to seconds. Authoring technical whitepapers that define how next-generation architectures get built across this community.
Served as key data analyst, program manager, and technical point of contact across five programs totaling more than $35M in SBIR/STRATFI funding. Led a multidisciplinary team through comprehensive analysis of data types, storage architectures, compute requirements, and cost modeling to support unmanned aerial systems operations in contested environments.
Drove recommendations for data implementation architecture and explored ML pipelines for electric vertical take-off and landing vehicle analysis — contributing to the Secretary of the Air Force's Business Case Analysis.
Restarted and led the SSC Data Stewardship Group — linking 70+ key data stakeholders across SSC, the Department of the Air Force, and the US Space Force to synchronize enterprise data management, analysis, and catalog efforts. Drove the rewrite of the SSC Data Plan, aligning existing data strategy with DoD/DAF/USSF frameworks and establishing LOEs subsequently adopted as standards by two additional field commands.
Analyzed 69 Space Sensing programs to identify data facets and reduce stakeholder meeting overhead from 60 hours to zero in three months.
Limb salvage research is a nascent field — and the existing literature centers predominantly on older male patients. Young women are nearly absent. I am one of the youngest long-term limb salvage patients in the literature, and I've outlived the anecdotal five-year threshold by a significant margin while continuing to regain function.
The research is already running. A daily capacity instrument I built and operate myself is generating the longitudinal dataset: biometrics, subjective body signal, recovery load, and environmental variables, cross-referenced over time in a patient-generated record. The PhD formalizes what the instrument is already producing. The problem has always been clear. Now there is data.