Skip to content. | Skip to navigation

Personal tools

This Logo Viewlet registered to Business4 Theme
You are here: Home / Events / WORLDCOMP'16 / Keynotes / Featured Keynote: Prof. Alfred Inselberg

Featured Keynote: Prof. Alfred Inselberg

Alfred Inselberg

 Data Science for High Dimensional Datasets
Prof. Alfred Inselberg
Tel Aviv University, Israel; University of California, Los Angeles
(UCLA); University of Southern California (USC);
Senior Fellow at the San Diego Supercomputing Center, California, USA

Author of "Parallel Coordinates: VISUAL Multidimensional Geometry"; his work is praised by Stephen Hawking among many others.

Date & Time: July 25 (Monday), 2016; 10:05am - 11:00am
LOCATION: East Ballrooms 6, 7, & 8



Data and Science are interwoven. Science derives from the analysis and interpretation of data leading to theories and their verification, more data and so on. Data Science studies this process and here we describe one of its powerful tools.

A dataset with M items has 2M subsets anyone of which may be the one satisfying our objective. With a good data display and interactivity our fantastic pattern-recognition defeats this combinatorial explosion by extracting insights from the visual patterns. This is the core reason for data visualization. With parallel coordinates the search for relations in multivariate data is transformed into a 2-D pattern recognition problem. We illustrate it on several real datasets (financial, process control, credit-score and one with hundreds of variables) with stunning results. A geometric classification algorithm yields the classification rule explicitly and visually. The minimal set of variables, features, are found and ordered by their predictive value. A model of a country’s economy reveals sensitivities, impact of constraints, trade-offs and economic sectors unknowingly competing for the same resources. An overview of the methodology provides foundational understanding; learning the patterns corresponding to various multivariate relations. These patterns are robust in the presence of errors and that is good news for the applications.  A topology of proximity emerges opening the way for visualization in Big Data.


AIfred received a Ph. D. in Mathematics and Physics from the University of Illinois (Champaign-Urbana) and stayed on as Research Professor. He then held senior research positions at IBM, where he developed a Mathematical Model of Ear (TIME Nov. 74), concurrently having joint appointments at University of California, Los Angeles (UCLA), University of Southern California (USC), Technion and Ben Gurion Universities. Since 1995 he is Professor at the School of Mathematical Sciences of Tel Aviv University. AI was elected Senior Fellow at the San Diego Supercomputing Center in 1996 and Distinguished Visiting Professor at Korea University in Seoul in 2008, and National University of Singapore 2011. He invented and developed the multidimensional system of Parallel Coordinates for which he received numerous awards and patents (on Air Traffic Control, Collision-Avoidance, Computer Vision, Data Mining).  His textbook on "Parallel Coordinates: VISUAL Multidimensional Geometry", Springer 2009, was praised by Stephen Hawking among many others. 

 More information available at:



« January 2017 »

  Past Events