Abstract

Unexpected progress may result when "key questions" are revisited from a computational viewpoint. 

We suggest to view 

Culture as "A collection of Semantic Abstractions that “describe” pseudo-stable Collective Behaviors that are the result of “Interactions” between Sets of Entities that physically share Temporal “Communication” Networks. 

Culture Analytics as the algorithmic and conceptual tools that we use to create "Semantic Abstractions" of Culture. 

This talk focus on a sample of algorithmic techniques that could be useful in the creation of "Semantic Abstractions" of Culture.

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Speaker's Bio Sketch

Bio Sketch: James Abello received the PhD degree in Combinatorial Algorithms from the University of California, San Diego, and the MS degree in Operating Systems from the University of California, Santa Barbara. He is the recipient of a University of California President's Postdoctoral Fellowship in Computer Science and has been recognized with teaching awards here at Rutgers (2016 Best Teaching award,  Computer Science Department) and previously at the University of California, Santa Barbara. 

James is the co-editor of External Memory Algorithms, Vol. 50 of the AMS-DIMACS series (with J. Vitter,1999) , The Kluwer Handbook of Massive Data Sets (with P. Pardalos and M. Resende, 2002) and Discrete Methods in Epidemiology (with Graham Cormode, 2006). He is founder member of the newly created International Culture Analytics Network supported by The Danish Council on Independent Research. He holds US patent 6781599 (with J. Korn from Google) on a “System and Method for Visualizing Massive Multidigraphs”.

James research focus has been on Algorithms and Data Structures, Massive Data Sets, Algorithm Animation and Visualization, Combinatorial and Computational Geometry, Discrete Mathematics, and some applications in Petroleum Engineering and Epidemiology. His works includes publications in Communications of the ACM, IEEE Transactions in Computer Graphics and Visualization, Theoretical Computer Science, Algorithmica, Discrete and Computational Geometry, SIAM Journal of Discrete Math, and Australasian Journal of Combinatorics.

James has lead the development of software systems like: MGV (A Massive Graph Visualizer, with J. Korn from Google), AGE (An Animated Graph Environment, with T. Veatch from the University of Toronto), Mirage (An Interpreted Language for Algorithm Animation, with C. Smith), A Quasi-Clique Extractor (with S. Sudarsky from Siemens Research - US), Graph View (with F. Van Ham from IBM - Netherlands), and CGV (with Christian Tominski from the University of Rostock, Germany).

James has held several academic positions and has been a senior member of technical staff at AT&T Shannon Laboratories, Bell Labs,  Senior Research Scientist at Ask.com, and DIMACS Research Professor. He is currently the director of the Master Program in Computer Science at Rutgers University and conceived, designed, and made operational a new Professional MS Degree in Data Science being launched this Fall 2017. James is currently a Co- PI on an NSF collaborative research grant titled: Human-Computer Graph Tele-discovery and Exploration(co-PI D. Chau, Georgia Tech). 

Information about some of James's research projects can be obtained by accessing http://www.mgvis.com    

James Abello, MSCS Director  
DIMACS Center for Discrete Mathematics and Theorethical Computer Science
Rutgers University 

A Calculus of Culture Network