Big Data 2019 : IEEE International Conference on Big Data

  in Conferences   Posted on June 29, 2019

Conference Information

Submission Deadline Monday 19 Aug 2019 Proceedings indexed by :
Conference Dates Dec 9, 2019 - Dec 12, 2019
Conference Address Los Angeles, United States
Conference & Submission Link http://bigdataieee.org/BigData2019/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Guide2Research Overall Ranking: 99
Category Rankings
Machine Learning & Arti. Intelligence 28
Databases & Information Systems 21
Biomedical & Medical Informatics 2

Google Scholar H5-index:
33

Conference Call for Papers

2019 IEEE International Conference on Big Data (IEEE Big Data 2019)
http://bigdataieee.org/BigData2019/
December 9-12, 2019, Los Angeles, CA, USA

In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data.

The first conference IEEE Big Data 2013 had more than 400 registered participants from 40 countries ( http://bigdataieee.org/BigData2013/) and the regular paper acceptance rate is 17.0%.
The IEEE Big Data 2017 ( http://bigdataieee.org/BigData2017/ , regular paper acceptance rate: 17.8%) was held in Boston, MA, Dec 11-14, 2017 with close to 1000 registered participants from 50 countries.
The IEEE Big Data 2018 ( http://bigdataieee.org/BigData2018/ , regular paper acceptance rate: 19.7%) was held in Seattle, WA, Dec 10-13, 2018 with close to 1100 registered participants from 47 countries.

The 2019 IEEE International Conference on Big Data (IEEE BigData 2019) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications.

We solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. The conference adopts single-blind review policy. We expect to have a very high quality and exciting technical program at Los Angeles this year.
Example topics of interest includes but is not limited to the following:
1. Big Data Science and Foundations
Novel Theoretical Models for Big Data
New Computational Models for Big Data
Data and Information Quality for Big Data
New Data Standards

2. Big Data Infrastructure
Cloud/Grid/Stream Computing for Big Data
High Performance/Parallel Computing Platforms for Big Data
Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
Energy-efficient Computing for Big Data
Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
Software Techniques and Architectures in Cloud/Grid/Stream Computing
Big Data Open Platforms
New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
Software Systems to Support Big Data Computing

3. Big Data Management
Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
Big Data Search Architectures, Scalability and Efficiency
Data Acquisition, Integration, Cleaning, and Best Practices
Visualization Analytics for Big Data
Computational Modeling and Data Integration
Large-scale Recommendation Systems and Social Media Systems
Cloud/Grid/Stream Data Mining- Big Velocity Data
Link and Graph Mining
Semantic-based Data Mining and Data Pre-processing
Mobility and Big Data
Multimedia and Multi-structured Data- Big Variety Data

4. Big Data Search and Mining
Social Web Search and Mining
Web Search
Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
Big Data Search Architectures, Scalability and Efficiency
Data Acquisition, Integration, Cleaning, and Best Practices
Visualization Analytics for Big Data
Computational Modeling and Data Integration
Large-scale Recommendation Systems and Social Media Systems
Cloud/Grid/StreamData Mining- Big Velocity Data
Link and Graph Mining
Semantic-based Data Mining and Data Pre-processing
Mobility and Big Data
Multimedia and Multi-structured Data-Big Variety Data

5. Ethics, Privacy and Trust in Big Data Systems
Techniques and models for fairness and diversity
Experimental studies of fairness, diversity, accountability, and transparency
Techniques and models for transparency and interpretability
Trade-offs between transparency and privacy
Intrusion Detection for Gigabit Networks
Anomaly and APT Detection in Very Large Scale Systems
High Performance Cryptography
Visualizing Large Scale Security Data
Threat Detection using Big Data Analytics
Privacy Preserving Big Data Collection/Analytics
HCI Challenges for Big Data Security & Privacy
Trust management in IoT and other Big Data Systems

6. Hardware/OS Acceleration for Big Data
FPGA/CGRA/GPU accelerators for Big Data applications
Operating system support and runtimes for hardware accelerators
Programming models and platforms for accelerators
Domain-specific and heterogeneous architectures
Novel system organizations and designs
Computation in memory/storage/network
Persistent, non-volatile and emerging memory for Big Data
Operating system support for high-performance network architectures

7. Big Data Applications
Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
Big Data Analytics in Small Business Enterprises (SMEs)
Big Data Analytics in Government, Public Sector and Society in General
Real-life Case Studies of Value Creation through Big Data Analytics
Big Data as a Service
Big Data Industry Standards
Experiences with Big Data Project Deployments

INDUSTRIAL Track

The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages).
Student Travel Award

IEEE Big Data 2019 will offer student travel to student authors (including post-docs)
Paper Submission

Please submit a full-length paper (up to 10 page IEEE 2-column format) through the online submission system.
Paper Submission Page
Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to \”formatting instructions\” below).

Formatting Instructions
8.5\” x 11\” (DOC, PDF)
LaTex Formatting Macros
Important Dates
Electronic submission of full papers: August 19, 2019
Notification of paper acceptance: Oct 16, 2019
Camera-ready of accepted papers: Nov 10, 2019
Conference: Dec 9-12, 2019

Conference Co-Chairs
Dr. Roger Barga : Amazon.com, USA
Prof Carlo Zaniolo : UCLA, USA

Program Co-Chairs
Dr. Chaitanya Baru : San Diego Supercomputer Center/Univ. of California San Diego, USA
Dr. Jun (Luke) Huan : Baidu Big Data Lab, China
Prof. Latifur Khan : University of Texas at Dallas, USA

Vice Chairs in Big Data Science and Foundations
Prof. Jingrui He : UIUC, USA
Prof. Wenqing Hu : Missouri S&T University, USA
Vice Chairs in Big Data Infrastructure
Prof. Hanghang Tong : UIUC, USA
Dr. Yinglong Xia : Huawei, USA
Vice Chairs in Big Data Management
Prof. Christopher Jermaine : Rice University, USA
Prof. Yongluan Zhou : Univ. of Copenhagen, Denmark
Vice Chairs in Big Data Search and Mining
Prof. Quanquan Gu : UCLA, USA
Prof. Aditya Prakash : Virginia Tech, USA
Vice Chairs in Big Data Security, Privacy and Trust
Prof. Dongwon Lee : Penn State University, USA
Prof. Julia Stoyanovich : New York University, USA
Vice Chairs in Hardware/OS Accelerating for Big Data
Prof. Sang-Woo Jun, UC Irvine, USA
Prof. Harry Xu, UCLA, USA
Vice Chairs in Big Data Applications
Prof. Xia Ning : Ohio State University, USA
Prof. Tim Weninger : Univ. of Notre Dame, USA
Industry and Government Program Committee Co-Chairs

Dr. Ronay Ak : NVIDIA, USA
Dr. Yuanyuan Tian : IBM Almaden Research Center, USA

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