Juan Ignacio
Fulponi

Context

Traditional household travel surveys are expensive and infrequent. This body of work develops methodologies to estimate origin-destination matrices from mobile phone and GPS data, enabling near-real-time understanding of urban mobility patterns across multiple Latin American cities.

Data

• Mobile phone CDR data (Veraset, Meta/Facebook)
• GPS traces and location data
• GTFS transit feeds, Waze traffic reports
• Census and socioeconomic data

Methodology

• Large-scale spatial data pipelines using Apache Spark and Sedona
• Trip detection and OD estimation algorithms
• Modal split estimation and validation against survey data
• Spatial econometric and ML models for mobility pattern characterization

Key Results

• Generated OD matrices for Buenos Aires, Bogota, and 17+ Latin American cities
• Enabled data-driven transport planning for metropolitan authorities
• Contributed to open-source toolkit for geospatial data processing

Context

Understanding gender differences in mobility is essential for equitable transport systems. This project leveraged large-scale data to map women's travel patterns in Buenos Aires, identifying systemic barriers and informing gender-responsive policy.

Data

• Large-scale mobility datasets for Buenos Aires metropolitan area
• Census and socioeconomic data, disaggregated by gender
• Public transit network and service data

Methodology

• Gender-disaggregated mobility indicator construction
• Spatial analysis of trip patterns, distances, and mode choices
• Statistical modeling of accessibility gaps

Key Results

• Identified significant gender gaps in trip patterns, distances, and mode choices
• Mapped spatial disparities in women's access to employment and services
• Provided evidence-based recommendations for gender-responsive transport policy

Context

The COVID-19 pandemic disrupted urban mobility worldwide. This project analyzed the recovery trajectories of two major cities, identifying how different communities and transport modes bounced back—and what changed permanently.

Data

• Multi-source mobility data (pre- and post-pandemic)
• Public transit ridership and service data
• Socioeconomic and demographic indicators by zone

Methodology

• Time series analysis of mobility recovery patterns
• Spatial pattern recognition across neighborhoods
• Comparative urban analysis between city typologies

Key Results

• Documented asymmetric recovery patterns across neighborhoods and income groups
• Highlighted lasting changes in commuting behavior and mode choice
• Informed post-pandemic transport planning strategies

Context

Urban congestion imposes massive economic costs, and ride-hailing services add complexity to the equation. This project combines congestion cost estimation in Buenos Aires and Lima with causal analysis of ride-hailing's impact on traffic, bridging academic research and policy.

Data

• Traffic sensor data and Waze reports
• GPS data and ride-hailing trip records
• GTFS transit data, road network data
• Socioeconomic and land-use indicators

Methodology

• Causal inference using econometric identification strategies
• Machine learning models for congestion prediction
• Cost-benefit analysis framework
• Geospatial data fusion from heterogeneous sources

Key Results

• Estimated socioeconomic costs of congestion for Buenos Aires and Lima
• Evaluated the causal impact of ride-hailing on urban congestion levels
• Produced actionable policy recommendations adopted by city agencies

Context

Official statistics are the backbone of evidence-based policy, yet accessing and processing them programmatically remains a barrier for researchers and analysts. I am committed to bridging this gap—building open-source tools that lower the friction between national statistical offices and the data science community, and modernizing institutional data workflows from within.

istatR — R Package on CRAN

• Author and maintainer of istatR, an R package published on CRAN that provides a clean interface to the ISTAT (Italian National Institute of Statistics) API
• Enables users to discover available datasets, explore their structure and dimensions, and retrieve statistical data directly into R
• Built on httr2, xml2, dplyr, and tibble for a tidy, modern workflow
• Apache 2.0 licensed—fully open source and community-driven

INDEC Modernization

• Led the modernization of production workflows at INDEC (Argentina's National Statistics Institute) as Product Owner
• Migrated legacy statistical processes to reproducible pipelines using SQL, R, and C#
• Improved data quality, traceability, and turnaround time for national statistics releases

Open-Source Contributions

• Contributed to the World Bank Development Data Partnership open-source toolkit for geospatial data processing
• Built reproducible R/Python pipelines for automated reporting at the IDB, designed for reuse across partner organizations
• Advocate for open data standards and transparent, reproducible analytical workflows in public institutions

Teaching

• Transport economics: demand analysis, pricing, regulation, and welfare evaluation
• Applied econometrics: causal inference, spatial econometrics, panel data methods
• Quantitative methods for urban and regional analysis
• Data science workflows applied to transport: Python, R, GIS

Research — Public Sector

• World Bank: OD matrix estimation, congestion costing, gendered mobility, post-COVID recovery analysis
• Inter-American Development Bank: urban freight innovation, mobile-phone mobility analytics across 17+ cities
• INDEC (National Statistics Institute): modernization of national statistics production, product ownership
• City of Buenos Aires: feasibility studies and cost-benefit evaluations for urban transit

Research — Private Sector

• REDAS Engineering: infrastructure impact evaluations, geospatial econometric methods for transport planning (Italy)
• ALEPH SRL: HSR and road investment assessment, demand forecasting, network simulation (Italy)
• Uber: causal impact of ride-hailing on urban congestion using econometric and ML models

Academic Background

• MSc in Transport Economics, Planning & Operations — Universidad Pablo de Olavide, Seville
• BA in Economics (Honors) — Universidad de Buenos Aires
• Thesis on congestion economics (grade: 10/10)
• 8 publications in journals, conferences, and international policy outlets