CIRSS Seminar: Molham Aref

Molham Aref, Chief Executive Officer of RelationalAI, will give the talk, "Knowledge Is Power: The importance of relations in Artificial Intelligence."

Abstract: In this talk, I will make the case for a first-principles approach to machine learning over knowledge graphs that exploits recent developments in database systems and theory. The input to learning classification and regression models is typically defined by feature extraction queries over structured and semi-structured data sources.  Machine learning problems can be cast as reasoning over a knowledge graph by decomposing the learning task into a batch of aggregates over the feature extraction query and by computing this batch over the input knowledge graph. The performance of this approach benefits tremendously from structural properties of the data and of the feature extraction query; such properties may be algebraic (semi-ring), combinatorial (hypertree width), or statistical (sampling). This translates to several orders-of-magnitude speed-up over state-of-the-art systems.  I will demonstrate how the use of knowledge graphs can reduce human and machine effort in developing better models.

This work is based on collaboration with Hung Q. Ngo (RelationalAI), Mahmoud Abo-Khamis (RelationalAI), Ryan Curtin (RelationalAI), Dan Olteanu (Oxford), Maximilian Schleich (Oxford), Ben Moseley (CMU), and XuanLong Nguyen (Michigan) and other members of the RelationalAI team and faculty network.

Bio: Molham Aref is the Chief Executive Officer of RelationalAI. He has more than 28 years of experience in leading organisations that develop and implement high value machine learning and artificial intelligence solutions across various industries. Prior to RelationalAI he was CEO of LogicBlox and Predictix (now Infor), Optimi (now Ericsson), and co-founder of Brickstream (now FLIR). Molham held senior leadership positions at HNC Software (now FICO) and Retek (now Oracle).

For participation information, contact Janet Eke

This event is sponsored by Center for Informatics Research in Science and Scholarship