Machine Learning and Data Science Applications for Physical Assets

Wednesday, December 8, 2021

Farshad Miraftab

Co-Founder, Panterra AI


What does it mean to be a data-driven organization? How can machine learning and data science begin to support critical decisions in your organization? In this presentation, Farshad will showcase the analytical and machine learning techniques that are deployed in first-class software companies and how they can be used in organizations that manage critical assets. In this presentation, you’ll you’ll see how a data-driven organization may have potentially averted the 1986 Challenger Space Shuttle Disaster, how to probabilistically evaluate if a mitigation program resulted in meaningful change, and finally how open source data can be used to quantify safety and financial risk for natural gas pipelines are a few of the examples that will be discussed both qualitatively and quantitatively. Lastly, lessons learned in data analytics, such as, ignoring the most dangerous equation in the world, will be shared to help our teams build stronger data intuition and avoid common pitfalls when solving complex business problems.

Farshad Miraftab is a data-driven professional with nearly 10 years of experience leading teams to scale decisions for both the energy and software industry using machine learning, statistical modeling and probabilistic programming. Farshad specializes in building novel predictive models to support asset risk quantification, resource/budget optimization, anomaly detection, revenue forecasting, and causal inference modeling. He a published author for Towards Data Science where he writes on topics related to data science and analytics to drive business intelligence and decision-making. He also advises organizations who are beginning their digital transformation journey to build their end-to-end data team and infrastructure.