Presents a novel architecture for robot learning of haptic interaction, achieving robust object class estimation and enhancing haptic interaction efficiency.
Explores perception in deep learning for autonomous vehicles, covering image classification, optimization methods, and the role of representation in machine learning.
Introduces a project-based course in communications and robotics, emphasizing practical projects and independent learning to prepare students for real-world challenges.
Explores trajectory forecasting in autonomous vehicles, focusing on deep learning models for predicting human trajectories in socially-aware transportation scenarios.
