Modeling Motorcyclist-Pedestrian Near Misses: A Multiagent Adversarial Inverse Reinforcement Learning Approach. - Gabriel Lanzaro; Tarek Sayed; Rushdi Alsaleh (J. Comput. Civ. Eng., 2022)

Comparing the Crash Risk of Vehicle-Pedestrian Interactions using Autonomous Vehicle Data. - Gabriel Lanzaro; Chuanyun Fu; Tarek Sayed (IV, 2023)

Enforcing Traffic Safety: A Deep Learning Approach for Detecting Motorcyclists' Helmet Violations Using YOLOv8 and Deep Convolutional Generative Adversarial Network-Generated Images. - Maged Shoman; Tarek Ghoul; Gabriel Lanzaro; Tala Alsharif; Suliman A. Gargoum; Tarek Sayed (Algorithms, 2024)

Optimizing Pedestrian Safety in Real-Time: An Extreme Value Theory-Based Reinforcement Learning Framework. - Gabriel Andrade Lanzaro; Tarek Sayed (ITSC, 2025)

Evaluating driver-pedestrian interaction behavior in different environments via Markov-game-based inverse reinforcement learning. - Gabriel Lanzaro; Tarek Sayed (Expert Syst. Appl., 2025)