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IEEE Big Data

The IEEE Big Data conference series has been around since 2013 and has established itself as a premier research conference in the field. IEEE Big Data 2019 was held in Los Angeles, CA on December 10-13, with close to 1200 registered participants from 48 countries. In 2018, IEEE Big Data conference was held in Seattle, WA and attracted close to 1000 participants from 46 countries. IEEE Big Data 2017 took place in Boston, MA from Dec 11-14.


Dr. Latifur Khan, a professor of computer science at The University of Texas at Dallas, is the recipient of the 2019 Institute of Electrical and Electronics Engineers (IEEE) Big Data Security Senior Research Award. The award honors his work in the areas of privacy and data security, which will be presented to him in May in Washington, D.C. He is currently working on a paper that examines how companies and other organizations can improve their privacy policies to protect user data.

For example, the workshop’s goal is to provide a timely venue for researchers and industry partners in the networking, communications, and privacy fields. Participants will discuss the benefits and drawbacks of big data techniques, and weigh trade-offs between privacy and security. This event will highlight advances in the field and provide a platform to exchange ideas. Here are some of the highlights from past workshops. Once the workshop concludes, the community can start developing a plan to improve its privacy policies.

IEEE Big Data conferences began in 2013 and have since established themselves as leading research forums on Big Data. The most recent, IEEE Big Data 2019, held Dec. 10-13 in Los Angeles, had a 16.7% paper acceptance rate and more than 1200 registered participants from 49 countries. The previous conference, IEEE Big Data 2013, took place Oct. 6-9 in Santa Clara. The first two conferences of the series were held in California, and had a high-profile attendance and acceptance rate.

IEEE’s Future Directions Big Data Initiative brings together leading researchers in big data from around the world to share cutting-edge research. Its multi-faceted Big Data initiative covers infrastructure, data management, privacy, and big data applications. Its goal is to foster knowledge transfer by providing a community for practitioners and researchers. The conference will provide extensive resources for researchers who are working on big data technologies. There are a lot of reasons to attend the Big Data Science Conference.

As the adoption of big data technologies in healthcare continues to rise, the threat of intrusion of patient privacy is an important concern. Big data analytics will need to be subject to data governance and security before exposing personal health information to analytics. As the healthcare industry is moving towards a value-based business model, privacy is more important than ever. For this reason, it is critical to create an effective big data governance strategy. There are many important steps involved in big data governance before it is exposed to analytics.


In May 2019, Dr. Latifur Khan, professor of computer science at The University of Texas at Dallas, was awarded the Institute of Electrical and Electronics Engineers (IEEE) Big Data Security Senior Research Award. The IEEE is the premier professional organization for technical experts. He was awarded the award at the IEEE Big Data Security conference in Washington, D.C., for his research on big data security. The award recognizes outstanding contributions in the area of multimedia big data analytics.

In the Spring of 2021, the lab had a successful semester. Its publications included contributions to IEEE Services Congress – SCC, ICDH, and IEEE Big Data Security on Cloud. The lab is now home to Dae-Young Kim, James Clavin, and Adithy Bandi, who all successfully defended their MS and PhD theses. Tao Zhang is a senior member of the IEEE, and also serves on a committee for the NSF’s proposal review process. In addition, he has served as the program chair for IEEE SmartCom and IEEE CS Cloud conferences.

Big data security is becoming a major concern for businesses as companies begin to store and analyze vast amounts of data. The volume of data generated by these systems is large and often difficult to store and retrieve. This data needs to be processed and translated into meaningful information for businesses, government, and customers. This paper explains some of the challenges, and provides an overview of data security architectures in a dynamic cloud environment. Besides discussing security architectures and how to implement them, the paper focuses on how to protect data and privacy in this dynamic environment.

Dr. Chen has extensive experience in the field of big data. His educational background includes a BEng degree from Nanjing University of Science and Technology. He later earned an MS and Ph.D. from New York University. His research is recognized by awards from IEEE, ACM, and AIS. He has published more than 70 peer-reviewed papers and has received the Nunamaker-Chen Dissertation Award in 2008.

Research ideas

IEEE Big Data has compiled a list of research projects for engineering and diploma students, including a study of machine learning mechanisms and Big Data methods. The list also features a number of research projects from the UMBC, which tackles big data challenges in remote sensing. These projects are an excellent way to gain insight into Big Data and its impact on the future of remote sensing. There are many ways to make your research interesting and useful.

The Government Track invites papers that focus on data utilization and open data. Potential research areas include data utilization scenarios, obstacles to big data usage, and data integration processes. Ideas on how to solve social issues, building a data ecosystem, and conducting comparative surveys before specific events are also welcome. Full-length papers are encouraged. There are no limitations to the size of these papers. Organizers plan to publish the best papers in a special issue of a leading scientific journal.

The IEEE BigData 2021 conference is designed to promote knowledge transfer and technological progress in the field of Big Data. It brings together leading researchers from around the world to identify and explore the 5 V’s of Big Data. This conference will focus on the deep scientific and technical nature of these problems, and provide insights into the future of data-driven decision-making. So, what are the best ways to approach Big Data? And how can we make this research more impactful?


Big data applications are used to gather and analyze huge amounts of data, such as those collected through social media, log files, sensors, and more. Such information can include text, images, video, and audio content, and can be combined with other types of data to make sense of it all. Often, big data applications also include multiple types of data in real-time. However, the most cited characteristic of big data is its volume.

Iee BigData 2021 will be a multidisciplinary conference for academicians, researchers, and healthcare data analysts to share their work and foster debate about big data in healthcare. These meetings aim to generate a common understanding of the emerging technologies and the applications that will be needed. The IEEE has established three tracks to promote Big Data applications and foster collaboration among these fields. The Industrial Track is a unique opportunity to present research results that are derived from actual industrial data.

Big data systems combine several systems in a distributed architecture. The central data lake may contain raw, preprocessed, and organized data. These applications are typically extremely demanding on the compute infrastructure. Luckily, there are several optimization algorithms and big data systems to choose from. There are also many different types of big data systems and big data applications, each with its own unique set of optimization parameters. A big data processing engine like Hadoop can handle a variety of different types of data.

IEEE BigData 2021 is an international conference that will gather leading researchers in the field and present the latest breakthroughs in Big Data. The conference focuses on big data analytics and visualization, big data management, and big data infrastructure. It also features special tracks for big data security, privacy, and science. You can expect to hear about big data research at this conference, so be sure to register! The event will feature numerous talks, panel discussions, and workshops.

Some of the biggest challenges associated with big data are related to interoperability. For example, it can be difficult to integrate big data from different government departments, which makes interoperability the most challenging challenge. Despite these challenges, big data can be used in many areas, including healthcare, finance, and manufacturing. It can help improve supply chains and optimize delivery routes. So, what are some of the most common Big Data applications?