Ehsan Ahmadi — accepted AI-conference papers

2026

CAPS: Context-Aware Priority Sampling for Enhanced Imitation Learning in Autonomous Driving

Hamidreza Mirkhani, Behzad Khamidehi, Ehsan Ahmadi, Mohammed Elmahgiubi, Weize Zhang, Fazel Arasteh +3

ICRA 2026poster

In this paper, we introduce Context-Aware Priority Sampling (CAPS), a novel method designed to enhance data efficiency in learning-based autonomous driving systems. CAPS addresses the challenge of imbalanced datasets in imitation learning by leveraging Vector Quantized Variational Autoencoders (VQ-V…

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2026

RLFTSim: Realistic and Controllable Multi-Agent Traffic Simulation via Reinforcement Learning Fine-Tuning

Ehsan Ahmadi, Hunter Schofield, Behzad Khamidehi, Fazel Arasteh, Jinjun Shan, Lili Mou +2

CVPR 2026

Supervised open-loop training has been widely adopted for training traffic simulation models; however, it fails to capture the inherently dynamic, multi-agent interactions common in complex driving scenarios. We introduce RLFTSim, a reinforcement-learning-based fine-tuning framework that enhances sc

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2025

Curb Your Attention: Causal Attention Gating for Robust Trajectory Prediction in Autonomous Driving

Ehsan Ahmadi, Ray Coden Mercurius, Soheil Alizadeh, Kasra Rezaee, Amir Rasouli

ICRA 2025

Trajectory prediction models in autonomous driving are vulnerable to perturbations from non-causal agents whose actions should not affect the ego-agent's behavior. Such perturbations can lead to incorrect predictions of other agents' trajectories, potentially compromising the safety and efficiency o

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