Chief Analytics Officer leading data strategy for 90,000+ patients annually across New York City. Native macOS developer shipping privacy-first tools on the App Store. Driven by the belief that good technology should serve everyone.
Over 17 years building technology solutions across healthcare and public health in New York City.
I'm a healthcare analytics leader and epidemiologist who likes using technology to try and make the world a little bit better. My career has been defined by a single thread: building tools that solve problems for the people who need them most.
As Chief Analytics Officer at Urban Health Plan, one of the nation's largest federally qualified health center networks, I lead analytics, reporting, data exchange, and epidemiology for a patient population spanning the Bronx, Central Harlem, and Corona, Queens. I've built on-premise BI infrastructure from scratch, deployed production clinical AI systems - including a fine-tuned local LLM that triages diagnostic imaging consults and routes urgent findings to care teams - and been activated for the city's response to outbreaks including Ebola, COVID-19, Measles, M-Pox, and more, coordinating across state, local, and federal health departments.
Earlier in my career I designed and built the Hub - New York City's first real-time distributed population health surveillance system, published in JAMIA and cited 83 times in peer-reviewed literature, still running across 700+ practices citywide today.
Outside of work, I build native macOS applications - privacy-first developer tools and utilities, written in Swift, with zero telemetry and no subscription bloat. My app devPad reached #1 in paid developer tools on the Mac App Store. My latest project, CyberWriter, is an AI-integrated scientific documentation editor built collaboratively with Claude.
From building the city's first real-time health monitoring tools to leading AI initiatives and public health surveillance and analytics at one of the nation's largest FQHCs.
Privacy-first developer tools built in Swift. Fully sandboxed, zero telemetry, one-time purchase.
AI-Integrated
#1 Paid Dev Tools
Open Source
Get devPad, cyberWriter, and Anubis together at a discount
Anubis is fully open source - the benchmarking engine behind the App Store product, free for the community. The benchmark data is open too, because transparent results make everyone's decisions better.
Over 110 Stars on Github! A comprehensive local LLM testing and benchmarking suite optimized for Apple Silicon. Real-time token metrics, Arena mode for head-to-head model comparisons, and a unified Vault for managing models across Ollama, LM Studio, MLX, and any OpenAI-compatible endpoint.
All benchmark data is open sourced. Browse the community leaderboard to see how models stack up, or dive into the explorer to query raw benchmark results across hardware and configurations.
// Anubis - Benchmark Module struct BenchmarkResult { let model: String let backend: Backend let tokensPerSecond: Double let timeToFirstToken: TimeInterval let gpuUtilization: Float let memoryUsage: UInt64 } // Privacy-first. Always local. let telemetry = nil
Zero telemetry across every product. Your data never leaves your machine. App Store sandboxed to Apple's strictest standards.
No Electron wrappers. No web views pretending to be apps. Real macOS software built with SwiftUI and AppKit.
Paid apps are one-time purchase. No subscriptions, no accounts, no lock-in. Pay once and the software is yours. Anubis OSS is open source and free forever.
The Hub Population Health System: distributed ad hoc queries and alerts.
Developing public health clinical decision support systems (CDSS) for the outpatient community in New York City: our experience.
Study of electronic prescribing rates and barriers identified among providers using electronic health records in New York City.
I work with hospitals, health systems, and healthcare organizations on analytics strategy, data infrastructure, AI implementation, and quality reporting. If you have a problem that needs solving, let's talk.
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