Senior Member Technical Staff, Salesforce
Brad Powley has extensive experience in engineering and strategy consulting. He works for Salesforce, designing and building data products that deliver insights to customers through machine learning and distributed graph processing. As a consultant, he managed engagements in energy, life sciences, real estate, IT, and manufacturing, helping his clients make better strategic decisions. He has also practiced the disciplines of mechanical design, manufacturing, and systems engineering in the context of high-volume consumer electronics products and a global supply chain.
Brad completed his PhD in Management Science and Engineering at Stanford, advised by Prof. Ron Howard. His thesis, Quantile Function Methods for Decision Analysis, set the theoretic foundation for a set of probability distributions particularly well-suited for Decision Analysis and other applications. He is particularly interested in the intersection of artificial intelligence and human decision making.
This panel will tackle the following questions on data science and decision analysis: How can Data Science complement DA? How does Data Science alter our engagement with DA? What are the challenges DA organizations need to tackle in order to leverage Data Science? Panel Chair: Dr. Brad Powley
This panel will tackle the following questions: How does DA change the way DS gets done? What are we getting through DA that makes DS more powerful? Panel Chair: Dr. Brad Powley