Big Data: Search, Retrieval, Analytics, Modeling and Informatics | College of Information Sciences and Technology
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Big Data: Search, Retrieval, Analytics, Modeling and Informatics

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About: Rapid advances in technologies for collecting data leading to the transformation of many historically data poor disciplines, e.g., biological sciences, health sciences, social sciences into increasingly data-rich disciplines. This has led to exponential increases in the volume, velocity, and variety of data, i.e., “big data”. New discoveries are increasingly driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of natural and built systems from big data. The emerging focus on Big Data is concerned with the exploration, development, and applications of scalable algorithms, infrastructures, and tools for organizing, integrating, retrieving, analyzing,and visualizing, large, complex, heterogeneous data.

Creative applications of big data analytics are enabling biologists to gain insights into how living systems acquire, encode, process, and transmit information; neuroscientists to uncover the neural bases of cognition; health scientists to not only diagnose and treat diseases but also help individuals make healthy choices; economists to understand markets; security analysts to uncover threats to national security; social scientists to study the evolution and dynamics of social networks; and scholars to gain new understandings of literature, arts, history, and cultures through advances in the digital humanities. 

Areas of Strength: Some areas of strength in Big Data in the college include information retrieval and search, scalable machine learning, learning predictive models, semantic complex event processing (CEP) from distributed, heterogeneous data, big data privacy and security, discovery Informatics, and big data applications in informatics (including Health Informatics, Security Informatics, Social Informatics).

Faculty: Lee Giles, Vasant Honavar, Sharon Huang, Jessie Li, Fenglong MaPrasenjit Mitra, Anna SquicciariniJames Wang, Suhang Wang, Amulya Yadav, Zihan Zhou