SEMINAR: Dr. Ryan Hafen – Purdue University – Visualisation of large complex data with Trelliscope

Date:  Wednesday, 14 October 2015

Time:
6:00pm – 6.30pm: Refreshments

6:30pm – 7.30pm: Lecture
7:45pm – onward: Dinner

Venue: Carslaw Lecture Theatre 373, Level 3, Carslaw Building, University of Sydney.

Dr. Ryan HafenPurdue University

Visualisation of large complex data with Trelliscope

Trelliscope is an R-based tool for detailed, flexible, interactive visualization of large complex data.  Trelliscope is based on Trellis Display, an effective approach to visualizing complex data in which data are broken into subsets, the same visualization method is applied to each subset, and the results are arranged in a grid for viewing.  Trelliscope extends Trellis Display by allowing the analyst to break potentially very large data sets into many subsets, apply a visualization method to each subset, and then interactively sample, sort, and filter the panels of the display on various quantities of interest, called cognostics.  Trelliscope provides a system for specifying displays and cognostics against large data sets, as well as an interactive web-based viewer for exploring the displays.  Trelliscope is part of a larger project, Tessera, which aims to provide a framework for deep analysis of large complex data.  In this talk, I will provide an overview of Tessera, discuss some details of Trelliscope, and provide examples of large-scale displays, including a display of hundreds of gigabytes of financial data with one million panels.  More information is available at http://tessera.io.

Biography of Dr. Ryan Hafen
Ryan Hafen is a statistical consultant and a remote adjunct assistant professor in the Statistics Department at Purdue University.  Ryan’s research focuses on methodology, tools, and applications in exploratory analysis, statistical model building, and machine learning on large, complex datasets.  He is the developer of the datadr and Trelliscope components of the Tessera project, as well as the rbokeh R visualization interface to the Bokeh plotting library.  Prior to his work as a statistical consultant, Ryan worked at Pacific Northwest National Laboratory doing applied work on large complex data spanning many domains, including power systems engineering, nuclear forensics, high energy physics, biology, and cyber security.  Ryan has a B.S. in Statistics from Utah State University, M.Stat. in Mathematics from University of Utah, and Ph.D. in Statistics from Purdue University.  More information about Ryan is available at http://ryanhafen.com.

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