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Rochester Data Science Consortium

Consortium photo

The Rochester Data Science Consortium is a partnership between two of the largest employers in the Finger Lakes region that will give New York State a competitive advantage in this growing field. It combines the world-class research capacity of the University of Rochester with Harris Corporation’s spirit for innovation to address the great big data challenges of our time.

Harris Corporation is a leading technology innovator, serving both government and commercial markets in areas such as tactical communications, electronic warfare, avionics, air traffic management, space and intelligence, and weather systems. Thanks to previous support from New York State and IBM, the University of Rochester is a national supercomputing leader and home to the New York State Center of Excellence in Data Science, as well as the Health Sciences Center for Computational Innovation

On September 14, 2017, Governor Andrew Cuomo announced $20 million in state support from the Upstate Revitalization Initiative for the project, which included the construction of Wegmans Hall and was a highlighted priority in the Finger Lakes Forward strategic plan. In addition, Empire State Development had committed another $2.5 million for the project, which was previously awarded through multiple capital grants from the Finger Lakes Regional Economic Development Council.

The University has identified data science as the centerpiece of its strategic plans. The University created undergraduate and graduate degree programs in data science and is helping train technical specialists, managers, clinicians, and others versed in the field of data science.

A strong suit for both the University and Harris is their core strengths in optics, imaging, and photonics. The new consortium will build off this and is expected to have an initial focus on three main areas:

  • Multi-Intelligence Correlation/Analytics and Deep Learning will evaluate advanced techniques such as deep learning to structure and label data and data analytics to extract information, trends, and correlations within the datasets.
  • Transportation Analytics will combine this information with weather, traffic, and other sources to evaluate the social economic impacts on companies, regions, people, and government.
  • Connected City Analytics will look at how datasets may be used for applications in commerce, law enforcement, and urban development.