Chief Data Scientist, Schlumberger
Dr. Neil Eklund is one of the foremost scientists in the field of Asset Health Management, and an experienced technologist in the space of data science, industrial analytics, and machine learning, with over 20 years experience in developing fielded solutions to practical industrial problems. Neil is one of the founders of the Prognostics and Health Management Society, the preeminent professional association in the AHM field, and continues to serve on its board of directors. He was the first Editor in Chief of the International Journal of Prognostics and Health Management, responsible for both launching the journal and establishing it as the premier publication for AHM academics and practitioners to disseminate their research findings. Neil is also an active standards author within the International Standards Organization (ISO) in the field of diagnostics and prognostics for complex machinery.
For the last two years, Neil has served as the Chief Data Scientist for Schlumberger, the world’s leading provider of technology for reservoir characterization, drilling, production, and processing to the oil and gas industry. Neil transformed the AHM program at Schlumberger, establishing the first successful deployed Internet of Things application in the oil industry which generated $20MM+ in the first three months of operation. For the 12 years prior to that, Neil was a research scientist in the Machine Learning laboratory of General Electric Global Research, where he gained deep technical experience across multiple industry segments, including Aerospace, Energy, Healthcare, Oil & Gas, Financial, and Rail. Additionally, Neil has worked closely with a wide range of external customers include Defense Advanced Research Projects Agency (DARPA), National Aeronautics and Space Administration (NASA), Lockheed Martin, ExxonMobil, Ford Motor Company, and Boeing.
Neil holds both a Ph.D. and a Masters degree from Rensselaer Polytechnic Institute. He holds eight patents, with another nine pending, and over 70 technical publications. Neil was a graduate-level university Machine Learning instructor for six years, and continues to teach classes for Schlumberger and the PHM Society.