Presented By O'Reilly and Cloudera
Make Data Work
September 26–27, 2016: Training
September 27–29, 2016: Tutorials & Conference
New York, NY
Kim Montgomery

Kim Montgomery
Head of Analytics, GridCure

| Attendee Directory Profile

Kim Montgomery is the head of analytics at GridCure, where she works on predictive modeling for the utility industry. Kim has a broad applied mathematics background with expertise in both predictive modeling and differential equations. Previously, as a postdoctoral scholar at the University of Utah and as a visiting professor at the Rose Hulman Institute of Technology, she did mathematical biology research and taught applied mathematics. Her research has included using feedback control to stabilize solutions to differential equations, modeling hair cells in the inner ear, and studying signaling between retinal cells during development. She has completed more than 30 predictive modeling projects through Kaggle.com on topics such as predicting which used cars would be bad buys, predicting the jobs that would most interest a job seeker, and predicting the composition of soil from its spectral properties. She has been ranked 15th on Kaggle. She holds a PhD in applied mathematics from Northwestern University.

Sessions

4:35pm–5:15pm Thursday, 09/29/2016
Data-driven business
Location: 1 E 15/1 E 16 Level: Beginner
Tags: iot, energy
Kim Montgomery (GridCure)
Average rating: **...
(2.80, 5 ratings)
With the advent of smart grid technology, the quantity of data collected by electrical utilities has increased by 3–5 orders of magnitude. To make full use of this data, utilities must expand their analytical capabilities and develop new analytical techniques. Kim Montgomery discusses some ways that big data tools are advancing the practice of preventative maintenance in the utility industry. Read more.