This talk focuses on a novel approach to machine learning for efficient big data processing within a system dominated by mobile devices. The proposed solution achieves this by utilizes custom, lean, and modular lambda functions to perform machine learning.
This talk answers many of the following questions: Why is smart grid technology essential for improved energy sustainability? What are the limitations of current electric power technology? What is smart grid technology and how may it address these limitations? Why is a balanced approach to the problem of energy sustainability best? The accompanying paper may be downloaded here.
This talk was recorded from one of Dr. Deese's conference on the paper downloadable below:
 A. Deese, C. O. Nwankpa, S. Coppi, T. Nugent; "A Practical, Hybrid Approach to Faster-Than Real-Time Power System Analysis and Control;" 19th World Congress of the International Federation of Automatic Control; August 2014.
This interview was televised on NBC10 Philadelphia on January 29, 2016. Click on picture to begin video in external window.