Sep 9–12, 2019
Peter Bailis

Peter Bailis
Founder and CEO | Assistant Professor, Sisu | Stanford University

Website

Peter Bailis is the founder and CEO of Sisu, a data analytics platform that helps users understand the key drivers behind critical business metrics in real time. Peter is also an assistant professor of computer science at Stanford University, where he coleads Stanford DAWN, a research project focused on making it dramatically easier to build machine learning-enabled applications. He holds a PhD from the University of California, Berkeley, for which he was awarded the ACM SIGMOD Jim Gray Doctoral Dissertation Award, and an AB from Harvard College in 2011, both in computer science.

Sessions

2:35pm3:15pm Wednesday, September 11, 2019
Location: LL21 A/B
Secondary topics:  Machine Learning
Peter Bailis (Sisu | Stanford University)
Average rating: ****.
(4.62, 13 ratings)
Despite a meteoric rise in data volumes within modern enterprises, enabling nontechnical users to put this data to work in diagnostic and predictive tasks remains a fundamental challenge. Peter Bailis details the lessons learned in building new systems to help users leverage the data at their disposal, drawing on production experience from Facebook, Microsoft, and the Stanford DAWN project. Read more.

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