Scrofani - Title

Jim W. Scrofani, PhD

Associate Professor
Department of Electrical and Computer Engineering
More info on Jim Scrofani


Magdi Kamel


“The ‘Google-ification’ of the world has created a domain of now and the challenge for data collection via detecting anomalies through inference must become just as rapid … We can’t afford to continue the bean counting approach to intelligence.”





The research here talks about applications of interest involved in Data Sciences, data mining, an analysis of Global Assessment tool data, Big Data and military decision making, and predicting IED attacks.
Kamel - Accordian

State of the Multi-INT Community

A unique, and loosely coupled, field of expertise that has organically grown out of a national security imperative to quickly leverage the benefit of integrating multiple sources of intelligence across the intelligence value stream.

Lacks processes for identifying and prioritizing strategic research investments

Requires a discipline enabler to promulgate research and advance development and deployment of new technologies

Is absent of high-quality education and training programs to enable development of human capital.

CMIS is established to:

  • Conduct and facilitate advanced Multi-INT research
  • Expand the breadth and depth of national Multi-INT research capacity
  • Develop high-quality Multi-INT academic programs
  • Facilitate and advance cohesion among Multi-INT practitioners
  • Research Outcomes
  • Academic Programs
  • Community of Interest

The CMIS Strategic Research Plan has been formulated so that the activities of the Center provide NPS and the sponsor community with research outcomes that advance the state-of-the-art in Multi-INT and intelligence integration and, ultimately, have profound and enduring impacts on the missions of the Department of Defense and Intelligence Community.

  • Provide national Multi-INT research leadership.
  • Expand the number, breadth, and depth of researchers conducting high-value Multi-INT research. 
  • Introduction to the tools, methods, applications and practice of Big Data
  • One-year distance learning-based curriculum
    • Four-course sequence
    • One course / quarter
    • Separate data management and analytics tracks
  • Electives address Multi-INT distinctive