Chief Data and Analytics Officer, TruValue Labs
Stephen leads TruValue Labs’ quantitative research team in applying artificial intelligence and machine learning techniques to create new financial signals from unstructured data. An industry leader in quantitative analytics, Stephen joined TruValue Labs from Thomson Reuters, where he spearheaded the company’s quantitative analytics offering, StarMine, and developed over 15 quantitative models. He has an extensive track record of successful predictive models using widely varying techniques across numerous domains.
He attended college at the Massachusetts Institute of Technology where he received his S.B. in Electrical Engineering and Computer Science. Stephen went on to receive his Masters and PhD in Engineering-Economic Systems from Stanford University, where he studied Decision Analysis under Prof. Ron Howard.
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 examine the following questions: What orientation do we need when building data products? What perspective does Decision Analysis give us when building data products? What perspectives other than Decision Analysis help us with data products? Panel Chair: Suhui Chen
Financial products and services are how we allocate resources in society. Decision Analysis and Data Science can play a critical role in the innovation of new financial products and services. This session will highlight financial innovation using DA and Data Science. Panel chair: Sheldon Bernard, Head of Decision Analysis at Procter & Gamble