Rachel Schutt
Dr. Rachel Schutt is the Senior Vice President of Data Science at News Corp, the publishing, news and information company, which is the publisher of The Wall Street Journal, New York Post, Times of London, The Australian; Harper Collins and Amplify.
Previously, Rachel was a statistician at Google Research and holds pending patents based on her work in the areas of social networks, large data sets, experimental design and machine learning. She is the co-author of the book “Doing Data Science” published by O’Reilly in October 2013 and based on this class. She is an adjunct professor in the Department of Statistics at Columbia University and a founding member of the Education Committee for the Institute for Data Sciences and Engineering at Columbia.
She earned her PhD in Statistics from Columbia University, a Masters degree in mathematics from NYU, and a Masters degree in Engineering-Economic Systems and Operations Research from Stanford University. Her undergraduate degree is in Honors Mathematics from the University of Michigan.
Kayur Patel
Dr. Kayur Patel works at Google Research, focusing on helping software engineers better use machine learning. His research interests are in human-computer interaction, software engineering, machine learning and information visualization. He studies how people apply machine learning to solve problems and build software. Guided by this research, he creates new development tools that help programmers more effectively use machine learning algorithms.
Kayur has a B.S. in Computer Science and Human Computer Interaction from Carnegie Mellon, a M.S. in Computer Science from Stanford, and a Ph.D. in Computer Science from the University of Washington. His graduate work was funded by grants from the National Science Foundation and Google, as well as fellowships from Microsoft Research and the Army Research Office. He is currently an Adjunct Assistant Professor at Columbia and is teaching Introduction to Data Science in the Fall of 2013.
