Author

F. Fakhrmoosavi

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Preprint Aug 2026

A Joint Information-Theoretic and Graph Learning Framework for Sensor Placement and Macroscopic Traffic State Reconstruction

This study develops a framework for preserving network-wide traffic information while reconstructing flow and density at unobserved links and the macroscopic fundamental diagram, enabling a broad range of sensor budgets in large-scale networks without strict limits on the number of sensors.

Ying Zhang, F. Fakhrmoosavi, Arash E. Zaghi · 0 citations

#artificial intelligence Review Sep 2025

Generating Individual Travel Diaries Using Large Language Models Informed by Census and Land-Use Data

Aggregate validation confirms the LLM's statistical representativeness and establishes a quantifiable metric of diary realism for future synthetic diary evaluation systems, demonstrating LLM's zero-shot viability and establishing a quantifiable metric of diary realism for future synthetic diary evaluation systems.

Sepehr Golrokh Amin, Devin Rhoads, F. Fakhrmoosavi et al. · arXiv.org · 1 citation