Monday 20 October 2014

Call for Participation: Workshop on Collaborative Methodologies to, Accelerate Scientific Knowledge Discovery in Big Data (CASK) 2014 -- co-located with IEEE BigData 2014 on 10-27-2014 in Bethesda, Maryland, USA

CALL FOR PARTICIPATION

1st International Workshop on Collaborative Methodologies to
Accelerate Scientific Knowledge Discovery in Big Data (CASK)

Co-located with the IEEE Int. Conf. on Big Data (BigData) 2014 
October 27, 2014, Bethesda, Maryland 20814, USA

Homepage: http://bigscientificdata.org/

========================= HIGHLIGHTS =========================
Keynote Speaker: 
        Joel Saltz
                Cherith Professor and Founding Chair 
                Department of Biomedical Informatics
                Stony Brook University

Invited Speakers: 
        William Tang (Princeton Plasma Physics Lab)
        Alex  Szalay (John Hopkins University)

Panel: "Big Data and Big Impact through Collaboration and Education"
        Joel Saltz (Stony Brook)
        William Tang (Princeton)
        Alex Szalay (John Hopkins)

========================= PROGRAM =========================
1:00PM: Introductions
1:15PM: Keynote Talk "Integrative Multi-scale Analysis in Biomedical Informatics"
        by Joel Saltz, Stony Brook University
2:00PM: Invited Talk "Extreme-scale Computing and Big Data Challenges In Fusion Energy"
        by William Tang, Princeton University
2:30PM: Wise Technology in Big Data Handling
3:00PM: Break
3:30PM: Invited Talk by Alex Szalay, John Hopkins University
4:00PM: An Axiomatic Inspection of the Behavior of Topic Models with Data Aggregation 
4:30PM: Panel "Big Data and Big Impact through Collaboration and Education"
        by Joel Saltz (Stony Brook), William Tang (Princeton), Alex Szalay (John Hopkins)
5:30PM: Conclusions

===================== WORKSHOP CHAIRS ======================
* Chen Jin (Palantir Technology)
* Ioan Raicu (Illinois Institute of Technology)
* Scott Klasky (Oak Ridge National Laboratory)

-- 
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Ioan Raicu, Ph.D.
Assistant Professor, Illinois Institute of Technology (IIT)
Guest Research Faculty, Argonne National Laboratory (ANL)
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Data-Intensive Distributed Systems Laboratory, CS/IIT
Distributed Systems Laboratory, MCS/ANL
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Editor: IEEE TCC, Springer Cluster, Springer JoCCASA
Chair:  IEEE/ACM MTAGS, ACM ScienceCloud
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Cel:      1-847-722-0876
Office:   1-312-567-5704
Email:    iraicu@cs.iit.edu
Web:      http://www.cs.iit.edu/~iraicu/
Web:      http://datasys.cs.iit.edu/
LinkedIn: http://www.linkedin.com/in/ioanraicu
Google:   http://scholar.google.com/citations?user=jE73HYAAAAAJ    
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