Organization profile

Organization profile

The mission of the Center for Big Data is to synergize expertise in various disciplines across the NJIT campus and build a unified platform that embodies a rich set of big data-enabling technologies and services with optimized performance to facilitate research collaboration and scientific discovery. Current research projects at the center focus on the development of high-performance networking and computing technologies to support big data applications. We are building fast, reliable data-transfer systems to help users in a wide spectrum of scientific domains move big data over long distances for collaborative data analytics. We are also developing high-performance workflow processes to manage the execution and optimize the performance of large-scale scientific workflows in various big data computing environments, including Hadoop/MapReduce and Spark. Furthermore, we are developing new machine-learning, data-mining and data-management techniques to address volume, variety, velocity, variability, and veracity challenges to enable big data analytics and predictive modeling in real-life applications. For example, we are developing a platform for analyzing user-contributed social media data to discover adverse drug effects, a leading cause of death. We are also developing data-driven methods to analyze web-page browsing behaviors to better understand user needs as well as the economics that sustain the free Web. These projects have been supported by the Leir Charitable Foundations, the National Science Foundation and Google.

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Collaborations and top research areas from the last five years

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  • A demonstrator for a real-time AI-FPGA-based triggering system for sPHENIX at RHIC

    Kvapil, J., Borca-Tasciuc, G., Bossi, H., Chen, K., Chen, Y., Corrales Morales, Y., Da Costa, H., Da Silva, C., Dean, C., Durham, J., Fu, S., Hao, C., Harris, P., Hen, O., Jheng, H., Lee, Y., Li, P., Li, X., Lin, Y. & Liu, M. X. & 11 others, Olvera, A., Purschke, M. L., Rigatti, M., Roland, G., Schambach, J., Shi, Z., Tran, N., Wuerfel, N., Xu, B., Yu, D. & Zhang, H., Feb 1 2024, In: Journal of Instrumentation. 19, 2, C02066.

    Research output: Contribution to journalArticlepeer-review

    Open Access
  • A Study of GDPR Compliance under the Transparency and Consent Framework

    Smith, M., Torres-Agüero, A., Grossman, R., Sen, P., Chen, Y. & Borcea, C., May 13 2024, WWW 2024 - Proceedings of the ACM Web Conference. Association for Computing Machinery, Inc, p. 1227-1236 10 p. (WWW 2024 - Proceedings of the ACM Web Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • BioReX: Biomarker Information Extraction Inspired by Aspect-Based Sentiment Analysis

    Gao, W., Gao, X., Chen, W., Foran, D. J. & Chen, Y., 2024, Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Proceedings. Yang, D.-N., Xie, X., Tseng, V. S., Pei, J., Huang, J.-W. & Lin, J.C.-W. (eds.). Springer Science and Business Media Deutschland GmbH, p. 129-141 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14648 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution