Machine Learning Applications for Energy Efficiency and Customer Care

Ben Packer, Justine Kunz, and other assorted Opower Data Scientists

With the world’s largest residential energy dataset at our fingertips, Opower is uniquely situated to use Machine Learning to tackle problems in demand-side management. Our communication platform, which reaches millions of energy customers, allows us to build those solutions into our products and make a measurable impact on energy efficiency, customer satisfaction, and cost to utilities.

In this talk, we will survey several Machine Learning projects that we’ve been working on. These projects vary from predicting customer propensity to clustering load curves for behavioral segmentation, and leverage supervised and unsupervised techniques.

Ben Packer is the Principal Data Scientist at Opower. Ben earned a bachelor's degree in Cognitive Science and a master's degree in Computer Science at the University of Pennsylvania. He then spent half a year living in a cookie factory before coming out to the West Coast, where he did his Ph.D. in Machine Learning and Artificial Intelligence at Stanford.

Justine Kunz is a Data Scientist at Opower. She recently completed her master’s degree in Computer Science at the University of Michigan with a concentration in Big Data and Machine Learning. Now she works on turning ideas into products from the initial Machine Learning research to the production pipeline.

SCHEDULE:
-- 6.30pm: light refreshments
-- 7.00pm: talk