The overarching goal of Enabling Technologies and Innovation Consortium is to create a research and education environment to support cross-cutting technologies across three core disciplines: the umbrella of (1) computer and engineering science research specifically in a form of machine learning and high performance computing (HPC) will support and enhance (2) advanced manufacturing and (3) nuclear detection technologies. We are looking to employ predictive strategies to enhance our understanding of tomorrow’s needs in nuclear nonproliferation.
This ONR funded project involves research groups at MIT, Northeastern University, and UCLA. The goal is to develop algorithms for detection, recognition and object/agent/event categorization for multi-agent tasks in complex, uncertain and dynamic environments. Algorithms should exploit multiple sensors mounted on various platform with mobility and/or control, to infer a representation of the environment suitable for agents to interact both with it and within it.
Detection of special nuclear material (SNM) is of critical interest to US Homeland Security as only a small quantity of such material is required to create a weapon with great destructive capability. Current technologies utilizing passive detection are susceptible to simple countermeasures such as shielding of the SNM with material with large atomic number (high Z).