Sumeet Trehan

Director Applied Machine Learning, ExxonMobil

Sumeet has held various staff and leadership roles focusing on Applied ML at ExxonMobil. Previously, he was at Stanford University where his PhD focused on using Applied ML to solve real world energy problems.

Past sessions

Equipment maintenance log of the global fleet is traditionally maintained using legacy infrastructure and data models, which limit the ability to extract insights at scale. However, to impact the bottom line, it is critical to ingest and enrich global fleet data to generate data driven guidance for operations. The impact of such insights is projected to be millions of dollars per annum.

 

To this end, we leverage Databricks to perform machine learning at scale, including ingesting (structured and unstructured data) from legacy systems, and then sifting through millions of nonlinearly growing records to extract insights using NLP. The insights enable outlier identification, capacity planning, prioritization of cost reduction opportunities, and the discovery process for cross-functional teams.

In this session watch:
Sumeet Trehan, Director Applied Machine Learning, ExxonMobil

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Sumeet Trehan