Environment & Safety Gas Processing/LNG Maintenance & Reliability Petrochemicals Process Control Process Optimization Project Management Refining
HomeAuthorsDisantis, J.

Disantis, J.

Seeq, Seattle, Washington

Joseph Disantis is a Senior Applied ML Scientist at Seeq. He has more than 15 yr of experience working in research and development with energy companies to solve high-value business problems by leveraging time series data. Prior to joining Seeq, he developed patented technologies at Marathon Oil Company related to synthetic fuel production and drilling rig control systems. DiSantis also has experience building successful data science teams focused on applied ML across the upstream domain.

Data, algorithms and collaboration combine for machine-learning success

Hydrocarbon Processing / October 2022
Seeq: Venkat, A.  |  Zakeri, S.  |  Disantis, J.
Ithaca Energy: Johnstone, A.
allnex: Martin, J.
Environment & Safety / Maintenance & Reliability / Petrochemicals / Process Control / Process Optimization / Refining / Engineering & Design / Environment / Equipment / Information Systems / Loss Prevention / Safety / Americas / Europe

Process manufacturers are investing significant resources in machine-learning (ML) to increase reliability, profitability and sustainability in their operations—saving millions of dollars in short periods of time through increased efficiency.

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