Columbia University

System Inc.

Victor Shih

Paul Sajda

David Jangraw

Adam Bly

Mehdi Jamei

Sonakshi Bose Roy

Lisa Strausfeld

Sameer Saproo

David Kang

A system and associated methods for organizing, representing, finding, discovering, and using data. Embodiments represent information and data in the form of a data structure termed a Feature Graph, that includes nodes and edges, where the edges serve to connect a node to one or more other nodes. A node in a Feature Graph may represent a variable, such as a measurable object, characteristic, or factor of a study. An edge in a Feature Graph may represent a measure of a statistical association between a node and one or more other nodes. Datasets that demonstrate or support the statistical association or measure the associated variable may be accessed through an identifier in a Feature Graph. An application may traverse a Feature Graph and aggregate and process data associated with a set of nodes or edges.

Systems and methods for organizing, finding, and using data

The present disclosure relates to systems and methods for providing a hybrid brain-computer-interface (hBCI) that can detect an individual's reinforcement signals (e.g., level of interest, arousal, emotional reactivity, cognitive fatigue, cognitive state, or the like) in and/or response to objects, events, and/or actions in an environment by generating reinforcement signals for improving an AI agent controlling the environment, such as an autonomous vehicle. Although the disclosed subject matter is discussed within the context of an autonomous vehicle virtual reality game in the exemplary embodiments of the present disclosure, the disclosed system can be applicable to any other environment in which the human user's sensory input is to be used to influence actions within the environment. Furthermore, the systems and methods disclosed can use neural, physiological, or behavioral signatures to inform deep reinforcement learning based AI systems to enhance user comfort and trust in automation.

Systems and methods for deep reinforcement learning using a brain-artificial intelligence interface

Growing community of inventors

New York, NY, United States of America

Victor Shih