The delivery of electric power has become synonymous with utility, and the expectation of always-on, always-available electricity has permeated the consumer psyche from telephone to Internet connectivity. While electrification has earned the distinction of the greatest engineering achievement of the 20th century by the National Academy of Engineering, utilities have been slow to integrate modern data science and robust analytics despite a wide-scale deployment of high-fidelity sensors across the grid. The way that engineers and scientists from these industries see the world—as composed of models derived from first principles—hinders change. In contrast, data scientists forgo the benefit of understanding how the data arose and instead accept the data “as is,” taking a purely data-driven approach.
Sean Murphy argues that the electric grid that started as a deterministic machine governed by well-known and understood mathematical equations has transformed into a probabilistic system, a fundamentally different beast. Sean explains the key drivers prompting this metamorphosis and explores the radical implications for operations, regulations, and management in these industries. Sean then expands his argument to illustrate similar patterns in other commercial and industrial fields.
Sean Patrick Murphy serves as the chief data scientist for PingThings, an Industrial Internet of Things (IIoT) startup bringing advanced data science and machine learning to the nation’s electric grid. He also advises several startups and provides learning-analytics consulting for EverFi. Previously, he served as the chief data scientist at a series A-funded healthcare analytics firm and the director of research at a boutique graduate educational company.
Sean is a founder and board member of Data Community DC, an 8,000-member community of data practitioners, and leads the 1,500+ member Data Innovation DC MeetUp, which focuses on the use of data for value creation. He has degrees in math, electrical engineering, and biomedical engineering, as well as an MBA from Oxford. Sean completed his graduate work in biomedical engineering at Johns Hopkins University and stayed on as a senior scientist at the Johns Hopkins University Applied Physics Laboratory for over a decade, where he focused on machine learning, anomaly detection, image analysis, and high-performance and cloud-based computing. Sean graduated from the DC inaugural class of the Founder Institute, completed Hacker School in New York City, and serves as a judge and mentor for Venture for America.
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