Advances in Causal Analytics: Discovering the WHYs In Your Data

Abstract

The next revolution of data science is causal analytics. While traditional statistical analysis techniques allow us to find correlations in our data and predict some future behaviors, they cannot tell us anything about the actual causes and effects. For instance, although we observe strong correlations in the data, we still have no way of telling if the rooster's crowing causes the sun to come up, or vice versa!

New advances in causal discovery and causal inference enable us to identify which input factors impact the outcomes using the same datasets. As an example, consumer product demand models built using these methods enable business analysts to find complex causal relationships among pricing strategies, marketing campaigns, purchasing behaviors, etc. This talk will discuss some recent developments in the field and demonstrate a new tool called Inguo, which is currently being launched in the US. We will also describe plans for new opportunities to participate in this interesting endeavor.

Bio

John Murray PhD is a business venture investor and a visiting scientist at SJSU. He is a technical adviser at Inguo, the causality analytics startup. John recently retired from the Computer Science Laboratory at SRI International, where he directed numerous research programs in formal software verification, computer games studies, machine learning, etc. He holds engineering degrees from Dublin Institute of Technology, the University of Michigan, and Stanford.

Ryo Kaneko is Director of Innovations at NEC X, the new technology accelerator in Palo Alto where he developed the original vision for Inguo. He has an extensive background in international business development and technical product management at NEC Corporation and GE Digital. His degrees in business administration and electrical engineering are from UC Berkeley and Sophia University, Japan.

Talk time and location

September 24, 2019 @ 1:30PM in MH 225