Publications & Outside Writing

Streetsblog NYC · July 2026
Clinton Street between Delancey and Houston carries roughly 16,000 vehicles a day, 4 to 6 times its neighbors, because the Williamsburg Bridge off-ramp funnels traffic onto a narrow residential block that has seen over 100 crashes and multiple fatalities in a decade. Argues for a Low Traffic Neighborhood redesign that removes the Manhattan-bound off-ramp and redirects through-traffic to Essex and Allen while preserving local and emergency access, on a block where over 80% of residents don't own a car. Read at Streetsblog ↗

Vital City · June 2026
Examines how nearly all of NYC's post-pandemic job growth has concentrated in a single lower-paying sector, leaving the local economy fragile and the city budget squeezed from both ends. Lays out strategies the Mamdani administration can pursue to diversify the jobs base and revive high-paying employment. Read at Vital City ↗

With Sarah Sachs · Reboot Democracy · June 2026
How Block Party built a searchable archive of Manhattan Community Board 3's 20 years of public meeting records, using semantic search and summarization to make institutional knowledge accessible to residents and journalists. Argues that understanding the civic problem, more than the AI tooling, is what created the value. Read at Reboot Democracy ↗

With Sarah Sachs · NYC OMB Institute · July 2026
Walks the NYC Office of Management and Budget Institute through Block Party's community board archive, and the story of scaling the resolution engine from one board to eleven: source adapters, parser iterations, and the corpus as it stands today. View the slides ↗

With Sarah Sachs · NYC School of Data 2026 · March 2026
Explains what community boards are and why their resolutions matter, then shows how Block Party turned two decades of Manhattan Community Board 3 meeting records into a searchable public archive with semantic search and AI summarization. View the slides ↗

With Shin-ichi Fujita & Valerie Ramey · Working Paper · March 2024
Examines why U.S. unemployment rose only modestly despite a dramatic postwar contraction in federal spending, challenging standard models of aggregate demand. Applies panel data and decomposition methods to historical employment records.

Federal Reserve Bank of Philadelphia Research Brief · July 2020
Analyzed state-level COVID reopening decisions, identifying which industries were resuming operations at lowest reinfection risk. Informed policy discussions on phased reopening criteria during the pandemic.

With Wenli Li · Rutgers Real Estate Center · September 2018
Post-recession analysis of investor activity, price dynamics, and supply constraints in the NJ housing market using transaction-level data.

Journal of Politics & International Affairs, Ohio State · March 2019
Constructed a cross-national database linking educational attainment to income levels across developing economies; identified non-linear gradients in returns to schooling.

With Peter Slattery, PhD · MIT FutureTech · March 2024
Analyzes how training data volume, diversity, and quality have driven AI capability gains over successive model generations. Synthesizes literature on scaling laws and data efficiency to inform forecasts of future AI progress.

MIT FutureTech · 2024
Benchmarks generative AI economic forecasts against historical precedents from prior general-purpose technologies (electrification, computing). Argues current consensus estimates likely understate adjustment costs and overstate near-term aggregate productivity gains.