Equipe BD
Equipe BD
Laboratoire d'InfoRmatique en Images et Systèmes d'information
UMR 5205 CNRS/INSA de Lyon/Université Claude Bernard Lyon 1/Université Lumière Lyon 2/Ecole Centrale de Lyon

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Big Data: Parameter Analysis and Implementation in Hadoop Platform

Qui: 
Prasan Kumar Sahoo
Quand: 
Thursday, July 23, 2015 - 11:00 to 12:30
Où: 
Salle de réunion du Liris, bâtiment Nautibus, 2° étage, Université Lyon 1

Parameter analysis and future disease prediction of health related Big Data are still in an informative stage due to the diversified bulky health care data, which is generated with greater speed. In this talk, data collection architecture and parameter analysis methods of healthcare Big Data will be discussed. Real implementation of ECG batch data in single cluster Apache Hadoop through the MapReduce framework will be presented.

Short Bio:

Prasan Kumar Sahoo received B. Sc. degree in Physics with Honors and M.Sc. in Mathematics from Utkal University, India. He received M.Tech. degree in Computer Science from the Indian Institute of Technology (IIT), Kharagpur, India in 2000, and 1st Ph.D. in Mathematics from Utkal University, India in 2002. He got his 2nd Ph. D. in Computer Engineering from National Central University, Taiwan in 2009. He has worked as a research Engineer in Software Research Center, Taiwan, Associate Professor in the department of Information Management, Vanung University, Taiwan since 2003 and Adjunct Associate Professor in National Taiwan University of Science and Technology. He is currently Director of International Affairs and Associate Professor in the department of Computer Science and Information Engineering, Chang Gung University, Taiwan and heads the Future Ubiquitous Networking Lab. He has served as the Program Committee Member of several IEEE, ACM and international conferences and reviewer of several international journals including IEEE TPDS, IEEE TWC etc. His current research interests include Big Data analytics, Cloud Computing and SDN and IoT related to modeling and performance analysis.