Doctor of Philosophy in Electrical and Computer Engineering - Machine Learning and Artificial Intelligence

Rochester Institute of Technology

In the past decade, advances in algorithms, computer architecture and processing power have led to giant strides in the development of computers that are capable to learn by themselves how to solve a problem and of applications that make use of this ability.These technologies, collectively known as machine learning (ML) or artificial intelligence (AI), are engendering new revolutionary technologies and new approaches to solve difficult contemporary problems. Our faculty and students are actively involved in this process of revolutionary creation with projects in areas that include:Neuromorphic devices and circuits, and brain-inspired architectures and algorithms for energy-efficient AI.Tensor-methods for deep learning and tensor analysis of big and multi-modal data.Applications of machine learning to wireless communications, network management, and dynamic spectrum access, sharing and sensing.Reliable learning in adversarial environments and trustworthy AI hardware.Deepfake detection.Self-driving vehicles.Smart warehouses.Computer vision, object recognition and tracking.Human-Robot interaction and collaboration.Deep learning algorithms for machine intelligence and AI applications.Biologically inspired learning models for multi-agent and complex system

Kate Gleason College of Engineering