NetMob 2026 — Full Program
October 14th–16th, Niterói, Rio de Janeiro state, Brazil
Wednesday, October 14th
Session 1: Mobility Foundations
Wednesday, October 14th · 09:00–10:00-
MC A behavioral census of US cities from interpretable mobility embeddings
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MC The power law in human mobility is a mixture artifact: evidence from a pandemic natural experiment
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MC The Hyperfractal Dimension: Measuring the Multi-Scale Structure of Urban Mobility
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MC Navigating decision points in mobility data
Keynote 1
Wednesday, October 14th, 10:30–11:30Beyond the Trace: GeoAI and Open Geodata as the Context Layer for Mobility Where the Map Runs Out
Chair of GIScience (Geoinformatics) at Heidelberg University, Germany.
Session 2: Data and Methods
Wednesday, October 14th · 11:30–12:45-
MC An Interactive Stop-Detection-Algorithm Tool for Comparison and Visualization
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MC Fastkit-Mobility: A High-Performance, DataFrame-Agnostic Library for Mobility Analysis
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MC Correcting socioeconomic bias in mobile phone mobility estimates
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MC Selection Bias in Phone-Based Migration Statistics: Evidence and Correction Strategies
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MC Identifying and characterizing dangerous road sections using vehicle telemetry and OpenStreetMap data
Session 3: Urban Life and Inequality
Wednesday, October 14th · 14:00–16:00-
MC People-Place Networks Reveal Economic Disparities in United States
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MC Digital Fingerprints of Multicultural Communities
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MC Amenity Proximity Redistributes Mobility Across Home, Workplace, and City Center: Evidence from Austria
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MC Planning for isolation? The role of urban form and function in shaping mobility in Brasília
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MC Beyond Proximity: Rethinking Urban Accessibility Through Human Mobility Patterns in United States
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MC Moving Unequally: Phone-Based Mobility Metrics Reveal Socio-Spatial Inequality in Mexico City
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MC The parenthood effect in urban mobility
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MC Measuring the Daytime POI-visit Impacts of Hybrid Work across U.S. Cities
Poster Session
Wednesday, October 14th · Coffee breaks-
MC GraniteMob: An AI Framework for Mobility Intelligence in the City of Niterói, Rio de Janeiro, Brazil
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MC Beyond Geographic Proximity: A Methodological Framework Informed by Mobility Data for Assessing Access to Specialized Hospital Services
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MC Mobile Data for Public Good: Sustainable Pathways within a Changing Mobile Ecosystem
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MC Using UAVs To Improve The Logistics Of Medical Supply Transport In Urban Areas
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MC Scalable multilayer urban social networks using Call Detail Records and census data
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MC Daily municipal bus demand forecasting in Niterói: combining weekly recurrence, calendar effects, and operational heterogeneity
Thursday, October 15th
Session 4: Health and Risk
Thursday, October 15th · 08:30–10:00-
MC A Multi-resolution Mobility-aware Framework for Dynamic Air Pollution Exposure Assessment
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MC Social media-based measures of social capital attenuate economic disparities in extreme weather evacuations and recovery
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MC Prediction of Infection Risk in an Epidemic Contact Network via Temporal Line Graph Representations
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MC The Effect of Mobility Trajectory Sparsity on Epidemic Modeling Outcomes
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MC Mobility Networks Reveal Association between Dynamic Food Environment and Chronic Cardiometabolic Diseases across U.S. Cities
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MC Transmission-aware mobility interventions for epidemic control
Keynote 2
Thursday, October 15th, 10:30–11:30From Digital Traces to Behavioral Insights: LLMs, Data Bias, and Fairness
Professor in Computer and Information Science at University of Maryland.
Session 5: Data Challenge
Thursday, October 15th · 11:30–12:45-
DC Privacy and anonymization of stochastic mobility trajectories from bus payment logs
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DC Unequal by Design: Bus Network Structure, Social Vulnerability, and Favela Access in Niterói
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DC Planned and experienced accessibility reveal contrasting diagnoses of transit poverty and inequality
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DC Edge on Wheels: Forecasting Bus Fleet Compute with Calibrated Uncertainty
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DC Transit Opportunity Landscapes Under Climate Stress: Spatial Equity, Vulnerability Evaluation, and the Usage–Accessibility Gap
Session 6: Behavioral Dynamics
Thursday, October 15th · 14:00–16:00-
MC Urban mobility network centrality predicts social resilience
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MC Spatiotemporal dynamics of adult content consumption: mapping traffic peaks and socioeconomic indicators
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MC Infrastructure Matters: Quantifying Measurement Bias in Mobile Phone Mobility Data
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MC Parental Activity Space Across Childcare Stages
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MC Invariant, elastic and plastic: how mobility reorganizes around a residential move
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MC Cross-Metropolitan Transferability of Behavior-based Dependency Networks
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MC Do tsunami evacuation drills reproduce real evacuation response? Evidence from paired events in coastal Chile
Poster Session
Thursday, October 15th · Coffee breaks-
DC Detecting bus delays and service anomalies in Niterói with autoencoder latent feature representations
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DC Demand-Weighted Reliability and Diagnostic Observability in Public Transport: A Multi-Source Alignment Approach
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DC Counterfactual Dispatch Regularization Reduces Passenger Waiting in Urban Bus Services
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DC A GPS-Based Framework to Distinguish Road-Network Congestion from Bus Operation in Niterói, Brazil
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DC The Impact of Precipitation on Public Transportation in Niterói, Brazil
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DC Assessing the Effects of Precipitation on Public Transportation Demand Through Eigenvector Analysis
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DC Spatial Analysis of Operational Discrepancies in Niterói's Municipal Bus System
Friday, October 16th
Session 7: Data Challenge and Behavioral Dynamics
Friday, October 16th · 08:30–10:00-
DC Impact of provided services and socio-demographic factors on bus accessibility: a Niterói case study
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DC Reaching the Stop, Reaching the City: Socio-Spatial Inequality in Public-Transport Access in Niterói (SDG 11.2.1)
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DC Urban Mobility and Demand Dynamics: A Telemetry and Ticketing Baseline for Niterói's Bus Network
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DC The Predictability of Bus Bunching and Who Pays for It: Evidence from Niterói, Brazil
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MC Comparing Gender-Labeled Urban Co-Visitation Networks Across U.S. Cities Using Google Places
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MC Leveraging mobility behavior to re-identify users
Keynote 3
Friday, October 16th, 10:30–11:30Accessibility and mobility data: two halves of a policy story
Head of Data Science at the Brazilian Institute for Applied Economic Research (Ipea) and visiting professor at the University of Toronto.
Session 8: AI and Privacy
Friday, October 16th · 11:30–12:45-
MC Large Language Models Create an Uneven Informational Layer over Cities
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MC Do LLM Agents Reproduce Human Mobility Laws?
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MC Predictability of Urban Park Visitation Behavior Using Context-Aware Fine-Tuned LLM Agents
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MC Some Users Are Easier to Re-identify: Evidence from Mobility Profiles and Embedding Geometry

2026

