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Make Data Work
Oct 15–17, 2014 • New York, NY
Andy Terrel

Andy Terrel
President, NumFOCUS

Website | @aterrel

Andy is a computational scientist with experience implementing distributed, large data applications. Currently serveing as the Chief Science Officer at Continuum Analytics, he leads the Blaze team taking the Python data stack to the next generation of scalable tools. Andy also works with numerous data scientists in academia and industry helping architect systems for interacting with large data resources. In his research, he is known for creating novel algorithms to speed implementations of mathematical models on the world’s largest supercomputers.

Andy received his Computer Science PhD at the University of Chicago in 2010. He has held research positions at Argonne National Lab, Sandia National Lab, Institute of Computational Engineering and Sciences at The University of Texas-Austin, and the Texas Advanced Computing Center. In industry, Andy served as lead developer at Kove, Inc. during its early stages, where he helped bring a record breaking SAN disk array to market. Andy also has also worked with big data financial applications during a brief tenure with Enthought, Inc.

Andy is a passionate advocate for open source scientific codes. To this end, he is a board member of the NumFOCUS foundation and has been involved in the wider scientific Python community since 2006. Andy has contributed to numerous projects in the scientific stack and hopes push for data to become a first class object for scientists worldwide.

Sessions

9:00am–5:00pm Wednesday, 10/15/2014
Data Science
Location: 1 E12/1 E13
Fernando Perez (Lawrence Berkeley National Laboratory and UC Berkeley), Brian Granger (Cal Poly San Luis Obispo), Andy Terrel (NumFOCUS), 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.
10:30am–11:00am Thursday, 10/16/2014
Office Hour
Location: Table E
Andy Terrel (NumFOCUS)
Andy leads the Blaze team, taking the Python data stack to the next generation of scalable tools, so he’s a great person to ask about parallel computing, and anything to do with the Python programming language, including high performance Python. Read more.