Doctor of Philosophy in Computing and Information Sciences- Artificial Intelligence

Rochester Institute of Technology

Our research efforts aim to understand the nature of visual perception so that we can create more visually intelligent machines. This is enabled via fundamental concepts in reasoning, prediction, supervised, semi-supervised and unsupervised learning, and stochastic optimization techniques. Our research involves (i) fundamental computer vision topics such as video analytics, detecting humans and their poses from images, object detection and tracking, etc (ii) computer vision applications such as medical image analysis, understanding social dynamics from videos of human interactions, collision detection in self-driving cars, and other vision-related regression problems in videos and (iii) the intersection of computer vision and graphics where we aim to model realistic avatars that interact more naturally with humans. We are constantly pushing the boundaries in applying computer vision techniques to a myriad of problems such as 3D reconstruction of the heart from MRI images deception detection from visual cues, understanding group interactions such as in a volleyball game, improving STEM classroom learning through video analytics, and other such problems.

Golisano College of Computing and Information Sciences