Sijae Brown

Float Health

Boulder, Colorado, United States

• Drove end-to-end automation of a high-variance staffing process by developing the Automated Nurse Selector, turning tacit operational knowledge into a zero-touch workflow.
• Automated compliance guardrails and supply quality with continuous multi-state license verification and behavior-feedback loops for marketplace reliability.
• Spearheaded zero-to-one development of Float's proprietary eChart, establishing a core clinical data layer that powers 100% of patient visits.
• Partnered with product leadership to launch the Float Nurse App, moving workforce coordination from ad hoc SMS scheduling to a scalable React-based platform.
• Led migration to secure HIPAA-compliant document management, reducing PHI sharing time from 8 minutes to seconds.
• Led strategy for Invoicing and Payout Automation with Stripe integrations that schedule nurse payouts and trigger pharmacy invoices from eChart submission.
• Reduced billing operations time by over 75% by automating billing for over 85% of visit volume.

Upstream Tech

Boulder, Colorado

• Investigated hydrologic drivers of climate-induced streamflow variability using snowpack, precipitation, soil moisture, and teleconnection indices.
• Built evaluation metrics and diagnostic visualizations in model assessment dashboards for reproducible basin and forecast-horizon comparisons.
• Presented seasonal hydroclimate forecasting research under climate-change scenarios at the 2022 AGU Chapman Conference.

Lockheed Martin Space

Colorado

• Developed and evaluated object detection and classification models on large geospatial sensor datasets to reduce false detection throughput.
• Adapted state-of-the-art detection architectures for domain shift, sparse labeling, and sensor-specific artifacts under operational constraints.
• Led two internal applied AI research programs end-to-end, including technical execution, transition planning, and customer demonstrations.
• Directed cross-division collaboration across three Lockheed organizations to integrate multi-source detection and fusion algorithms and execute live flight demonstrations.

Lockheed Martin Aeronautics

F-35 and Advanced Development Programs

• Served as Technical Lead and Project Manager for a multi-agent deep imitation learning system using LSTM-based architectures for sequential decision modeling.
• Led technical white paper development for JAIC and DARPA submissions, translating prototype outcomes into formal program proposals.
• Advanced single-agent imitation learning algorithms for the Vega Project from concept to validated demonstration.
• Contributed to formal validation of safety-critical mission system software in controlled test environments.