Automating Data Science
Developing technology to automate the creation of machine learning pipelines to solve a wide variety of data driven modeling problems.
A novel knowledge organization system that integrates concepts of causality, factual knowledge and meta-reasoning into a model-driven knowledge graph representation to provide situational awareness.
A Multi-modal Open World Grounded Learning and Inference project to build a system that can answer a wide range of common sense questions posed using either an image or natural language, about everyday intuitive phenomena such as abduction, analogy, causality, agency, physics, and social interactions.
Integrating Scientific Models
Model Integration through Knowledge-Rich Data and Process Composition.
An information integration tool that enables users to quickly and easily integrate data from a variety of data sources including databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs.
Knowledge Graph for Business
Creating a public resource containing knowledge about businesses, their products, and their patents as well as the relationships between them, such as customer, competitor or supplier.
Exploiting Context in Cartographic Evolutionary Documents to Extract and Build Linked Spatial-Temporal Datasets.
Scoring Scientific Research
Developing automated techniques for evaluating scientific claims and assessing the confidence of their reproducibility and applicability.