Pipeline Energy Expo 2018

Maria Araujo
Manager



Maria leads a team of engineers and scientists that are responsible for several areas of technologies related to the application of machine learning and data mining techniques in a variety of industries, including automotive, oil & gas, smart energy, space, manufacturing and transportation. Her team has been involved in initiatives to advance related big data technologies, primarily involving the application of data mining techniques to identify predictive aspects in large data sets for the enhancement or creation of decision support systems. Maria was the lead developer on the Smart LEak Detection (SLED) technology, which utilizes a combination of optical sensors (IR cameras) to create a technology that can reliably detect small leaks in hazardous liquids pipelines using convolutional neural networks. SLED was the recipient of an R&D 100 award by R&D Magazine in 2017. Maria is currently the PI on a U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) project that is focused on combining deep learning and machine vision techniques to detect methane leaks in oil & gas facilities. A few other initiatives of Maria’s team include the application of machine learning and big data techniques to detect anomalies and incidents using satellite imagery and predicting traffic conditions based on available sensor data in existing U.S. highways. Maria holds Bachelor of Science and Master of Science degrees in electrical engineering from the University of California, Los Angeles (UCLA). She is the recipient of an R&D 100 Award for the development the of the Smart LEak Detection (SLED) system and was named one of San Antonio’s Top 40 Under 40 in 2017 by the San Antonio Business Journal.

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