Predicting human gaze—especially in egocentric or driving scenarios—is fundamentally about modeling where people will attend next, not just where they are looking now. This thesis focus on designing and implementing a pipeline that integrates feature forecasting with a gaze prediction module, conduct experiments on egocentric datasets, and systematically evaluate the benefits of future-aware representations.

This thesis focuses on developing and evaluating visual segmentation methods for elevator components using a mobile robotic platform.

Scene understanding is crucial to advance autonomous robotic systems deployment in the real world. The selected student will focus on developing a framework for constructing 3DSGs capable of recording changes in dynamic environments as they occur.

We are currently seeking for a motivated and talented master’s student to work on discriminative filtering and feature extraction for classification of tactile signals.