As one of the first data scientists to enter the then newly namely field, he helped develop a career path whereby scientists can apply academic rigor to an increasing number of industry areas. Examples include developing and deploying algorithms in the area of drug safety monitoring, enabling sharing of critical machine learnings across American, European and Asian life science organizations to that of Formula E racing, leading to champion standing in the New York, Santiago and Paris ePrixs. Moreover, co-authored the Field Guide to Data Science, the single most successful piece of thought leadership in Booz Allen Hamilton’s 100+ year history, which is used for pedagogy as well as a key reference to help unlock new discoveries in varied contexts: government research, industry applications and even startups.
Read More
Using algorithms to inform strategy
Read More
Today’s AI doesn’t just shuttle passengers and cargo. It wins races.
Read More
At the heart of drug safety is a question: do the benefits of a particular medicine outweigh its risks? …
Read More
An extensive amount of data derived from medical case reports regarding potential adverse events is subjected to manual review. Devising efficient strategies for identification and information extraction concerning potential adverse events are needed to support timely monitoring of the reports and decision making.
Read More
As task outstrips human capability, more software-driven aid comes to compliance
Read More