Michael’s prime research interest is in the field of deep learning and its applications to computer vision and robotics.
Michael’s research focuses on developing convolutional neural network (CNN) models for semantic understanding of videos and its application to robot perception, robot learning, and human-robot interaction.
Research interests
- Computer Vision, Interactive Intelligent Systems, Artificial Intelligence, Human-Robot Interaction, Machine Learning
