EPSRC CDT in Data Science - Distinguished Lecture by Molham Aref, CEO of RelationalAI

TITLE: Relational Artificial Intelligence

DATE: Monday, 27th May 2019

TIME: 4-5pm followed by Drinks Reception

LOCATION: G07, Informatics Forum, School of Informatics

SPEAKER: Molham Aref, Chief Executive Officer of RelationalAI

ABSTRACT: In this talk, Molham Aref will make the case for a first-principles approach to machine learning over relational databases that exploits recent development in database systems and theory. The input to learning classification and regression models is defined by feature extraction queries over relational databases. He casts the machine learning problem as a database problem by decomposing the learning task into a batch of aggregates over the feature extraction query and by computing this batch over the input database. The performance of this approach benefits tremendously from structural properties of the relational 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.

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).

PRIVACY STATEMENT

Information about you: how we use it and with whom we share it.

We will use your personal data to allow us to process your registration, communicate with you and obtain your feedback about the event. We are processing the information about you for these purposes because by registering for the conference, you are entering into a contractual agreement for us to do so. In order to facilitate online bookings for our events, we use Eventbrite - a third party service which is not operated by the University of Edinburgh. Details of Eventbrite's privacy policy can be found here.

We will not share information about you with any other third party. We will hold the personal data you provided us for 6 months. We do not use profiling or automated decision-making processes.

If you have any questions about the privacy policy for this event, please contact datascience@inf.ed.ac.uk .

If you have queries about the University of Edinburgh's privacy policy go here.