<div dir="ltr"><p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US" style="font-size:22pt"> Call
for Papers</span></b></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"> </span></p><p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US" style="font-size:14pt">2016
IEEE International Conference on Big Data
(IEEE Big Data 2016)</span></b></p><p class="MsoNormal" style="text-align:justify"><span lang="IT"> </span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"><a href="http://cci.drexel.edu/bigdata/bigdata2016/"><span lang="IT">http://cci.drexel.edu/bigdata/bigdata2016/</span></a></span><span lang="IT"></span></p><p class="MsoNormal" style="text-align:justify"><span lang="IT"> </span></p><p class="MsoNormal" style="text-align:justify"><span lang="IT">Dec 5-8, 2016, Washington DC, USA</span></p><p class="MsoNormal" style="text-align:justify"><span lang="IT"> </span></p><p class="MsoNormal"><span lang="EN-US" style="font-size:11pt">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. </span><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif">The IEEE Big Data conference series
started in 2013 has established itself as the top tier research conference in
Big Data.</span><span lang="EN-US" style="font-size:11pt;font-family:Calibri,sans-serif"> </span><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif"> </span><span lang="EN-US" style="font-size:11pt;font-family:Calibri,sans-serif"></span></p><p class="" style="text-indent: -18pt;"><span lang="EN-US" style="font-size:11pt;font-family:Symbol">·<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif">The
first conference IEEE Big Data 2013 had more than 400 registered
participants from 40 countries (<span class=""> </span></span><span lang="EN-US"><a href="http://cci.drexel.edu/bigdata/bigdata2013/"><span style="font-size:11pt;font-family:Cambria,serif">http://cci.drexel.edu/bigdata/bigdata2013/</span></a></span><span class=""><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif">)</span></span><span class=""><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif"> and
the </span></span><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif">regular paper acceptance rate
is 17.0%.</span><span lang="EN-US" style="font-size:11pt;font-family:Calibri,sans-serif"></span></p><p class="" style="text-indent: -18pt;"><span lang="EN-US" style="font-size:11pt;font-family:Symbol">·<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif">The
IEEE Big Data 2015 had more than 780 registered participants from 49 countries (<span class=""> </span></span><span lang="EN-US"><a href="http://cci.drexel.edu/bigdata/bigdata2015/"><span style="font-size:11pt;font-family:Cambria,serif">http://cci.drexel.edu/bigdata/bigdata2015/</span></a></span><span class=""><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif">)</span></span><span lang="EN-US" style="font-size:11pt;font-family:Cambria,serif">, and regular paper acceptance rate is 16.8%.</span><span lang="EN-US" style="font-size:11pt;font-family:Calibri,sans-serif"></span></p><p class=""><span lang="EN-US" style="font-size:11pt;font-family:Calibri,sans-serif"> </span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"> The 2016 IEEE International
Conference on Big Data (IEEE Big Data 2016) 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. </span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:Verdana,sans-serif"> </span></p><p class=""><span lang="EN-US" style="font-size:12pt;font-family:'Times New Roman',serif">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. <b><i>Example
topics of interest includes but is not limited to the following</i></b>:</span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:Verdana,sans-serif"> </span></p><p class="MsoNormal" style="margin-left:18pt;text-align:justify"><span lang="EN-US">1.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Science and Foundations</span></p><p class="MsoNormal" style="margin-left:54pt;text-align:justify"><span lang="EN-US">a.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Novel Theoretical Models for
Big Data</span></p><p class="MsoNormal" style="margin-left:54pt;text-align:justify"><span lang="EN-US">b.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">New Computational Models for
Big Data </span></p><p class="MsoNormal" style="margin-left:54pt;text-align:justify"><span lang="EN-US">c.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Data and Information Quality for
Big Data</span></p><p class="MsoNormal" style="margin-left:54pt;text-align:justify"><span lang="EN-US">d.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">New Data Standards</span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"> </span></p><p class="MsoNormal" style="margin-left:18pt;text-align:justify"><span lang="EN-US">2.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Infrastructure</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">a.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Cloud/Grid/Stream Computing for
Big Data </span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">b.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">High Performance/Parallel Computing Platforms for Big Data</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">c.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Autonomic Computing and Cyber-infrastructure,
System Architectures, Design and Deployment</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">d.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Energy-efficient Computing for Big
Data</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">e.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Programming Models and
Environments for Cluster, Cloud, and Grid Computing to Support Big Data </span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">f.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Software Techniques and Architectures
in Cloud/Grid/Stream Computing</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">g.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Open Platforms</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">h.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">New Programming Models for Big
Data beyond Hadoop/MapReduce, STORM </span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">i.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Software Systems to Support Big
Data Computing</span></p><p class="MsoNormal"><span lang="EN-US"> </span></p><p class="MsoNormal" style="margin-left:18pt"><span lang="EN-US">3.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Management</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">a.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Search and Mining of variety of
data including scientific and engineering, social, sensor/IoT/IoE, and
multimedia data</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">b.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Algorithms and Systems for Big
DataSearch</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">c.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Distributed, and Peer-to-peer
Search</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">d.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Search Architectures, Scalability and Efficiency</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">e.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Data Acquisition, Integration,
Cleaning, and Best Practices</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">f.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Visualization Analytics for Big
Data </span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">g.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Computational Modeling and Data
Integration </span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">h.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Large-scale Recommendation Systems
and Social Media Systems</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">i.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Cloud/Grid/Stream Data Mining-
Big Velocity Data</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">j.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Link and Graph Mining</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">k.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Semantic-based Data Mining and
Data Pre-processing</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">l.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Mobility and Big Data</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">m.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Multimedia and Multi-structured
Data- Big Variety Data</span></p><p class="MsoNormal" style="margin-left:36pt"><span lang="EN-US"> </span></p><p class="MsoNormal"><span lang="EN-US"> </span></p><p class="MsoNormal" style="margin-left:18pt"><span lang="EN-US">4.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Search and Mining</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">a.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Social Web Search and Mining</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">b.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Web Search</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">c.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Algorithms and Systems for Big
Data Search</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">d.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Distributed, and Peer-to-peer Search</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">e.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Search Architectures, Scalability and Efficiency</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">f.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Data Acquisition, Integration,
Cleaning, and Best Practices</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">g.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Visualization Analytics for Big
Data </span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">h.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Computational Modeling and Data
Integration </span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">i.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Large-scale Recommendation Systems
and Social Media Systems</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">j.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Cloud/Grid/StreamData Mining-
Big Velocity Data</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">k.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Link and Graph Mining</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">l.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Semantic-based Data Mining and
Data Pre-processing</span></p><p class="MsoNormal" style="margin-left:54pt"><span lang="EN-US">m.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Mobility and Big Data</span></p><p class="MsoNormal" style="margin-left:54pt;text-align:justify"><span lang="EN-US">n.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Multimedia and Multi-structured
Data- Big Variety Data</span></p><p class="MsoNormal" style="margin-left:54pt;text-align:justify"><span lang="EN-US"> </span></p><p class="" style="margin-left:18pt"><span lang="EN-US">5.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Big
Data Security, Privacy and Trust</span><span lang="EN-US"></span></p><p class="" style="margin-left:54pt"><span lang="EN-US">a.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Intrusion
Detection for Gigabit Networks </span><span lang="EN-US"></span></p><p class="" style="margin-left:54pt"><span lang="EN-US">b.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Anomaly
and APT Detection in Very Large Scale Systems</span><span lang="EN-US"></span></p><p class="" style="margin-left:54pt"><span lang="EN-US">c.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">High
Performance Cryptography </span><span lang="EN-US"></span></p><p class="" style="margin-left:54pt"><span lang="EN-US">d.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Visualizing
Large Scale Security Data</span><span lang="EN-US"></span></p><p class="" style="margin-left:54pt"><span class=""><span lang="EN-US">e.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span></span><span class=""><span lang="EN-US">Threat Detection using Big Data Analytics</span></span></p><p class="" style="margin-left:54pt"><span lang="EN-GB">f.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Privacy
Threats of Big Data</span></p><p class="" style="margin-left:54pt"><span lang="EN-GB">g.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Privacy
Preserving Big Data Collection/Analytics</span></p><p class="" style="margin-left:54pt"><span lang="EN-GB">h.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">HCI
Challenges for Big Data Security & Privacy</span></p><p class="" style="margin-left:54pt"><span lang="EN-GB">i.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">User
Studies for any of the above</span></p><p class="" style="margin-left:54pt"><span lang="EN-US">j.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Sociological
Aspects of Big Data Privacy</span><span lang="EN-US"></span></p><p class="" style="margin-left:54pt"><span lang="EN-US">k.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-GB">Trust
management in IoT and other Big Data Systems</span><span lang="EN-US"></span></p><p class="" style="margin-left:18pt;text-align:justify"><span lang="EN-US"> </span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"> </span></p><p class="" style="margin-left:18pt;text-align:justify"><span lang="EN-US">6.<span style="font-stretch:normal;font-size:7pt;font-family:'Times New Roman'">
</span></span><span lang="EN-US">Big Data Applications</span></p><p class="" style="margin:0cm 0cm 3.6pt 54pt;line-height:15.6pt;background-image:initial;background-repeat:initial"><span lang="EN-US" style="color:black">a.<span style="font-stretch:normal;font-size:7pt;line-height:normal;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="color:black">Complex Big Data
Applications in Science, Engineering,
Medicine, Healthcare, Finance, Business, Law, Education, Transportation,
Retailing, Telecommunication</span></p><p class="" style="margin:0cm 0cm 3.6pt 54pt;line-height:15.6pt;background-image:initial;background-repeat:initial"><span lang="EN-US" style="color:black">b.<span style="font-stretch:normal;font-size:7pt;line-height:normal;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="color:black">Big Data Analytics in
Small Business Enterprises (SMEs),</span></p><p class="" style="margin:0cm 0cm 3.6pt 54pt;line-height:15.6pt;background-image:initial;background-repeat:initial"><span lang="EN-US" style="color:black">c.<span style="font-stretch:normal;font-size:7pt;line-height:normal;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="color:black">Big Data Analytics in
Government, Public Sector and Society in General</span></p><p class="" style="margin:0cm 0cm 3.6pt 54pt;line-height:15.6pt;background-image:initial;background-repeat:initial"><span lang="EN-US" style="color:black">d.<span style="font-stretch:normal;font-size:7pt;line-height:normal;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="color:black">Real-life Case Studies
of Value Creation through Big Data Analytics</span></p><p class="" style="margin:0cm 0cm 3.6pt 54pt;line-height:15.6pt;background-image:initial;background-repeat:initial"><span lang="EN-US" style="color:black">e.<span style="font-stretch:normal;font-size:7pt;line-height:normal;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="color:black">Big Data as a Service</span></p><p class="" style="margin:0cm 0cm 3.6pt 54pt;line-height:15.6pt;background-image:initial;background-repeat:initial"><span lang="EN-US" style="color:black">f.<span style="font-stretch:normal;font-size:7pt;line-height:normal;font-family:'Times New Roman'">
</span></span><span lang="EN-US" style="color:black">Big Data Industry Standards</span></p><p class="" style="margin:0cm 0cm 3.6pt 54pt;line-height:15.6pt;background-image:initial;background-repeat:initial"><span lang="EN-US" style="font-family:Verdana,sans-serif">g.<span style="font-stretch:normal;font-size:7pt;line-height:normal;font-family:'Times New Roman'"> </span></span><span lang="EN-US" style="color:black">Experiences with Big Data Project Deployments</span><span lang="EN-US" style="font-family:Verdana,sans-serif"></span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:Verdana,sans-serif"> </span></p><p class="MsoNormal"><b><span lang="EN-US">INDUSTRIAL
Track</span></b></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US">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. </span><span lang="EN-US">We accept full
papers (up to 10 pages) and extended abstracts (2-4 pages).</span></p><p class="MsoNormal" style="text-align:justify"><i><span lang="EN-US" style="font-size:11.5pt"> </span></i></p><p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US">Student Travel Award</span></b></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US">IEEE Big Data 2016 will offer<b> student travel </b>to student
authors (including post-docs) </span></p><p class="" style="margin-left:54pt;text-align:justify"><span lang="EN-US"> </span></p><p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US">Journal Publication </span></b></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US">A set of about 10 papers will be
selected for a fast-track review and then published at the IEEE Transactions on
Big Data.</span><span lang="EN-US" style="font-family:Verdana,sans-serif"></span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:Verdana,sans-serif"> </span></p><p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US">Conference Co-Chairs:</span></b><span lang="EN-US"></span></p><p class="MsoNormal"><span lang="EN-US">Dr. Sudarsan Rachuri, DoE, USA</span></p><p class="MsoNormal"><span lang="EN-US">Prof. Lyle Ungar, University of
Pennsylvania, USA</span></p><p class="MsoNormal"><span lang="EN-US">Prof. Philip S. Yu, University of Illinois
at Chicago, USA<br>
<br>
</span></p><p class="MsoNormal"><b><span lang="EN-US">Program
Co-Chairs:</span></b><span lang="EN-US"></span></p><p class="" style="margin:0cm 0cm 0.0001pt"><span lang="EN-US">Prof. James Joshi, University of Pittsburgh,
USA</span></p><p class="" style="margin:0cm 0cm 0.0001pt"><span lang="EN-US">Prof. George </span><span lang="EN-US">Karypis, University of
Minnesota, USA</span></p><p class="" style="margin:0cm 0cm 0.0001pt"><span lang="EN-US">Prof. Ling Liu, Georgia Institute
of Technology, USA</span></p><p class="" style="margin:0cm 0cm 0.0001pt"><span lang="EN-US"> </span></p><p class="MsoNormal"><b><span lang="EN-US">Industry and Government Program
Committee Chairs</span></b></p><p class="MsoNormal"><span lang="EN-US">Dr. Ronay Ak NIST, USA</span><span lang="EN-US"></span></p><p class="MsoNormal"><span lang="EN-US">Dr. Rama Govindaraju, Google,USA</span></p><p class="MsoNormal"><span lang="EN-US">Dr. Toyotaro Suzumura, IBM Research, USA</span></p><p class="MsoNormal"><span lang="EN-US">Dr. Yinglong Xia, Huawei Research America,
USA</span></p><p class="MsoNormal"><span lang="EN-US"> </span></p><p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US">BigData Steering Committee
Chair:</span></b></p><p class="MsoNormal" style="text-align:justify"><span lang="DE">Prof. Xiaohua Tony Hu, Drexel University,
USA, <a href="mailto:xh29@drexel.edu">xh29@drexel.edu</a> </span></p><p class="MsoNormal" style="text-align:justify"><b><span lang="DE"> </span></b></p><p class="MsoNormal" style="text-align:justify"><b><u><span lang="EN-US">Paper Submission</span></u><span lang="EN-US">:</span></b></p><p class=""><span lang="EN-US">Please
submit a full-length paper (up to </span><b><span lang="EN-US" style="color:red">10 page IEEE 2-column format</span></b><span lang="EN-US">) through the online submission
system. </span><span lang="EN-US"></span></p><p class=""><span lang="EN-US"><a href="https://wi-lab.com/cyberchair/2016/bigdata16/scripts/submit.php?subarea=BigD">https://wi-lab.com/cyberchair/2016/bigdata16/scripts/submit.php?subarea=BigD</a></span><span lang="EN-US"></span></p><p class=""><span lang="EN-US">Papers should be formatted to IEEE Computer Society
Proceedings Manuscript Formatting Guidelines (see link to "formatting
instructions" below).<br>
</span><span lang="EN-US" style="font-size:9pt;font-family:Arial,sans-serif"><br>
</span><strong><span lang="EN-US">Formatting Instructions</span></strong><span lang="EN-US"><br>
8.5" x 11" (<a href="ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.doc">DOC</a>,
<a href="ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.pdf">PDF</a>)
<br>
<a href="ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_Latex8.5x11x2.zip" target="_top"><strong><span style="color:rgb(0,28,81)">LaTex Formatting Macros</span></strong></a></span></p><p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US">Important Dates:</span></b></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"> </span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US">Electronic submission of full papers: July 25, 2016</span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US">Notification of paper acceptance: Oct 9, 2016</span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US">Camera-ready of accepted papers: Nov 5, 2016</span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US">Conference: Dec 5-8, 2016</span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"> </span></p><p class="MsoNormal" style="text-align:justify">
</p><p class="MsoNormal" style="text-align:justify"><span lang="EN-US"> </span></p></div>
<br>
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