posted by organizer: arindamp || 5758 views || tracked by 4 users: [display]

BigDF 2017 : IEEE International Workshop on Foundations of Big Data Computing

FacebookTwitterLinkedInGoogle

Link: http://hipc.org/foundations-of-big-data-computing-workshop/
 
When Dec 18, 2017 - Dec 18, 2017
Where Jaipur, India
Submission Deadline Aug 25, 2017
Notification Due Sep 20, 2017
Final Version Due Oct 3, 2017
Categories    algorithms   big data analytics   machine learning   high performance computing
 

Call For Papers

*******************************************************************************
CALL FOR PAPERS

IEEE International Workshop on Foundations of Big Data Computing (BigDF 2017)
In conjunction with HiPC 2017 (http://www.hipc.org)
December 18, 2017
Le Meridien, Jaipur, India

http://hipc.org/foundations-of-big-data-computing-workshop/
*******************************************************************************

What constitutes a “Big Data” problem? What application domains are best suited to benefit from Big Data analytics and computing? What are the traits and characteristics of an application that make it suited to exploit Big Data analytics? How can Big Data systems and frameworks be designed to allow the integration and analysis of complex data sets? How can research in Big Data Analytics benefit from the latest advances in supercomputing and High Performance Computing (HPC) architectures? The goal of this workshop is to address questions like these that are fundamental to the advancement of Big Data computing, and in the process, build a diverse research community that has a shared vision to advance the state of knowledge and discovery through Big Data computing.

Topics of interest include research contributions and innovative methods in the following areas (but not limited to):

* Scalable tools, techniques and technologies for Big Data analytics (e.g., graph and stream data analysis, machine learning and emerging deep learning methods)
* Algorithms and Programming Models for Big Data
* Big Data applications - Challenges and Solutions (e.g., life sciences, health informatics, geoinformatics, climate, socio-cultural dynamics, business analytics, cybersecurity)
* Scalable Big Data systems, platforms, services, and management
* Big Data toolkits, workflows, metrics, and provenance.

We invite paper submissions that describe original research contributions in the area of Big Data computing, and position papers that highlight the potential challenges and opportunities that arise in Big Data computing. We also invite short papers that describe work-in-progress original research.

Regular papers can be up to 8 pages long and short papers can be up to 4 pages long. All submissions will undergo rigorous peer-review by the technical program committee, and accepted manuscripts will appear in the HiPC workshop ("HIPCW") proceedings and will be indexed by IEEE digital library. Authors of the accepted manuscripts will be required to present their work at the workshop proceedings.

Paper Submission link: The paper submission opens July 1, 2017. Click on the following link for submitting your papers: https://www.easychair.org/conferences/?conf=hipcbigdf17

Authors can submit an abstract prior to submitting the full paper for review. The abstract is not mandatory but is recommended to help organizers plan the review phase in a timely fashion (i.e., authors can submit a full paper without having submitted an abstract). However, submissions with only full papers will be reviewed.

Organizing Committee:

* General Chairs: Dinkar Sitaram (PESIT), Ananth Kalyanaraman (Washington State University)
* Program Chairs: Madhu Govindaraju (SUNY Binghamton), Saumyadipta Pyne (IIPH, Hyderabad)
* Publicity Chair: Arindam Pal (TCS Research and Innovation)
* Proceedings Chair: Ren Chen, USC (HiPC proceedings chair)
* Industry Liaison: Vivek Yadav (FullStackNet, India)

Technical Program Committee:

Medha Atre, IIT Kanpur

Ariful Azad, Lawrence Berkeley National Laboratory

Biplab Banerjee, IIT Roorkee

Suren Byna, Lawrence Berkeley National Laboratory

Nabanita Das, Indian Statistical Institute

Oded Green, Georgia Institute of Technology

Manish Kurhekar, Visvesvaraya National Institute of Technology

Suresh Marru, Indiana University

Arindam Pal, TCS Research

Laks Raghupathi, Shell, India

Sudip Seal, Oak Ridge National Laboratory

Gokul Swamy, Amazon

Devesh Tiwari, Northeastern University

Abhinav Vishnu, Pacific Northwest National Laboratory

Yinglong Xia, Huawei Research America

Jaroslaw Zola, University of Buffalo

Related Resources

ADAH 2017   Advanced Data Analytics in Health
ICPR 2018   24th International Conference on Pattern Recognition
BigData Congress 2018   The 7th International Congress on Big Data
ECCV 2018   European Conference on Computer Vision
NCUL 2018   Call For Book Chapters: Natural Computing for Unsupervised Learning Springer (USA)
COLT 2018   Computational Learning Theory
ACIIDS 2018   10th Asian Conference on Intelligent Information and Database Systems
NAACL HLT 2018   The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
IEEE Trans SUSC 2019   IEEE Trans on Sustainable Computing (SI: Intersection of Computing and Communication Technologies with Energy Systems)
MLDM 2018   14th International Conference on Machine Learning and Data Mining MLDM 2018