The mathematical and algorithmic foundations of AI underpin its remarkably broad applications. Penn researchers are exploring why AI methods work when they do, why they fail, and discovering the fundamental principles that will enable the next generation of AI algorithms.
AI Foundations
AI Theory
Mathematicians, statisticians, theoretical computer scientists and engineers at Penn are studying the mathematical, statistical, and computational foundations of AI/DS algorithms to understand why they work when they do, why they fail, and discover fundamental principles that will enable the development of the next generation of AI/DS algorithms.
Computer Vision
Computer scientists and engineers at Penn are developing algorithms for automatically extracting information from images and video, such as detecting and segmenting objects in an image, recognizing human actions in a video, reconstructing 3D scenes, answering questions about an image or video, generating an image from text, etc.
Natural Language Processing
Computer scientists and engineers at Penn are developing algorithms for automatically extracting information from text, summarizing text, answering questions about a document, translating text from one language to another, generating new next, etc.
Robotics
Computer scientists and engineers at Penn are developing algorithms that allow robots to navigate and interact with a 3D environment, including algorithms for motion planning, reasoning under uncertainty, control, etc.
