Math is proof. Given enough data—and today, we have plenty—we can know. “The right information in the right place just changes your life,” said Stewart Brand. But your life won’t change by itself. Bruce Mau defines design as “the human capacity to plan and produce desired outcomes.” Math informs; design compels. Which matters more? A well-designed collection of flawed information—or an opaque, hard-to-parse, but unerringly accurate model? From mobile handsets to social policy, we need both good math and good design. Which is more critical? The Great Debate series returns to Strata. In this Oxford-style debate, two opposing teams take opposing positions. We poll the audience, and the teams try to sway opinions. It’ll be a fast-paced, sometimes irreverent look at some of the core challenges of putting data to work.
Dr. Gray obtained degrees in Applied Mathematics and Computer Science from Berkeley and a PhD in Computer Science from Carnegie Mellon, and is an Associate Professor at Georgia Tech and CTO of Skytree, Inc. His research focuses on scaling up all of the major practical methods of machine learning (ML) to massive datasets. He began working on this problem at NASA in 1993 (long before the current fashionable talk of “big data”). His large-scale algorithms helped enable the Top Scientific Breakthrough of 2003, and have won a number of research awards. He served on the National Academy of Sciences Committee on the Analysis of Massive Data and frequently gives invited tutorial lectures on massive-scale ML at top research conferences and agencies.
Monica Rogati is one of the founding members of the LinkedIn product data science team. She leads a team of data scientists and turns data into products, actionable insights and (news) stories.
Monica obtained her PhD in Computer Science from Carnegie Mellon, where she focused on text mining and applied machine learning. At LinkedIn, she pioneered data driven products with multi-million dollar business impact.
When she doesn’t build recommender systems, Monica finds stories in the LinkedIn data about the most overused buzzwords, trending job titles, entrepreneur DNA, promotion cycles for Millennials and first names that tend to succeed. Her stories appeared in thousands of media outlets – from the Wall Street Journal & The Economist to NPR & CNN all the way to Real Simple & Howard Stern.
Monica is currently leading a team of data scientists who advance LinkedIn’s data products.
Julie Steele is the Content Editor for Strata at O’Reilly Media. She is co-author of Beautiful Visualization and Designing Data Visualizations. She finds beauty in exploring complex systems, and thinks in metaphors. She is particularly drawn to the visual medium as a way to understand and transmit information.
Julie holds a Master’s degree in Political Science (International Relations) from Rutgers University in Newark. She lives in New York City, where she cooks, reads, designs, and practices yoga. You can find her blogging occasionally for O’Reilly Radar, or on Twitter.
Doug VanderMolen is Chief UX Architect of ClearStory Data. Before joining ClearStory Data, Doug led the user experience for Google Analytics, Google AdWords and other Google Ads products. Doug’s designs have helped millions of people intuitively understand and utilize data to make key decisions. Prior to Google, Doug was a key member of the team at MeasureMap, which was acquired by Google in 2006. He received his Masters of Design from the Institute of Design.
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