Patrick Bangert

Vice President, Artificial Intelligence Samsung

Patrick Bangert, SPE, is the Vice President of Artificial Intelligence with Samsung.
He founded and served as CEO of Algorithmica Technologies, a machine learning company specializing in oil and gas applications. After a few research positions at Los Alamos National Laboratory and NASA’s Jet Propulsion Laboratory, Bangert became assistant professor of applied mathematics at Jacobs University Bremen in Germany. In 2005, he founded Algorithmica to bring the machine learning methods down from the ivory tower into practice. He holds a PhD degree in applied mathematics from University College London.

Data & Analytics

Workshop Cracks Open Subsurface Data

SPE’s 2021 Open Subsurface workshop tackled the ins and outs of open source, open data, and open access.

February 15, 2022 • Patrick Bangert • Data Science and Digital Engineering
AI/machine learning

Four Points Can Improve Your Odds of AI Success

ODDS—organization, due diligence, data, and scrub. These four important steps can make sure you are ready to implement artificial intelligence in a way that leads to a successful project.

November 30, 2020 • Patrick Bangert • Data Science and Digital Engineering
Data & Analytics

Digital Begets Digital?

Work from home is the new normal. Digital tools have come to the rescue. The questions that is going around the industry is: Will the increased reliance on digital technologies in the workplace generate increased adoption of the digital transformation?

October 21, 2020 • Patrick Bangert • Data Science and Digital Engineering
AI/machine learning

How Much Science Is There in a Data Science Project?

Recently, the hype around artificial intelligence and machine learning caused several people to ask me how much of a project is actual machine learning. Based on man-hours spent on the project, I estimate that only about 5% of the effort is spent directly on data-science-related activities.

February 2, 2020 • Patrick Bangert • Data Science and Digital Engineering
Data & Analytics

The Case for Collaboration: Data Science Is Done Best When an Operator Works With a Data Scientist

Studies conducted through collaboration between an operator that knows the physical reality and a data-science company that knows the best machine-learning methods yield good practical results.

May 22, 2019 • Patrick Bangert • Data Science and Digital Engineering
Data & Analytics

What Difference Does 99% Accuracy Make Over 95%? Not Much

Instinctively, we feel that greater accuracy is better and all else should be subjected to this overriding goal. This is not so. While there are a few tasks for which a change in the second decimal place in accuracy might actually matter, for most tasks, this improvement will be irrelevant.

February 27, 2019 • Patrick Bangert • Data Science and Digital Engineering
Data & Analytics

The Ecosystem of Machine Learning Is Much Larger Than Algorithms

The ecosystem in which an algorithm must live in order to deliver value must be viewed as a whole. The algorithm can be viewed like a car’s engine. It’s rather important, but it’s not a car yet.

February 27, 2019 • Patrick Bangert • Data Science and Digital Engineering