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Make Data Work
Oct 15–17, 2014 • New York, NY
Travis Oliphant

Travis Oliphant
Founder/CEO, Continuum Analytics, Inc.


Travis Oliphant has a Ph.D. from the Mayo Clinic and B.S. and M.S. degrees in Mathematics and Electrical Engineering from Brigham Young University. Since 1997, he has worked extensively with Python for numerical and scientific programming, most notably as the primary developer of the NumPy package, and as a founding contributor of the SciPy package. He is also the author of the definitive Guide to NumPy.

Travis was an assistant professor of Electrical and Computer Engineering at BYU from 2001-2007, where he taught courses in probability theory, electromagnetics, inverse problems, and signal processing. He also served as Director of the Biomedical Imaging Lab, where he researched satellite remote sensing, MRI, ultrasound, elastography, and scanning impedance imaging.

From 2007-2011, Travis was the president at Enthought, Inc. During his tenure there, the company grew from 15 to 50 employees, and Travis worked with well-known Fortune 50 companies in finance, oil-and-gas, and consumer-products. He was involved in all aspects of the contractual relationship, including consulting, training, code-architecture, and development.

As CEO of Continuum Analytics, Travis engages customers in finance, consumer products, and oil and gas, develops business strategy, and helps guide technical direction of the company. He actively contributes to software development and engages with the wider open source community in the Python ecosystem by serving as a director of the Python Software Foundation and past director of Numfocus.


9:00am–5:00pm Wednesday, 10/15/2014
Data Science
Location: 1 E12/1 E13
Fernando Perez (University of California at Berkeley), Brian Granger (Cal Poly San Luis Obispo), Andy Terrel (Bold Metrics), Peter Wang (Continuum Analytics), Jake Vanderplas (eScience Institute, University of Washington), Olivier Grisel (Inria & scikit-learn), Travis Oliphant (Continuum Analytics, Inc.), William McKinney (Cloudera), Trent Nelson (Continuum Analytics), Kayur Patel (Google), Kester Tong (Google)
Average rating: ****.
(4.43, 14 ratings)
Python has become an increasingly important part of the data engineer and analytic tool landscape. Pydata at Strata provides in-depth coverage of the tools and techniques gaining traction with the data audience, including iPython Notebook, NumPy/matplotlib for visualization, SciPy, scikit-learn, and how to scale Python performance, including how to handle large, distributed data sets. Read more.