The authors propose assessing the defense acquisition system's ability to overcome the operational problems outlined in the 2018 National Defense Strategy, discuss why the approach is valuable, and suggest next steps.
Sep 20, 2021
Joel B. Predd is a senior engineer at the RAND Corporation. The substantive breadth of Predd's personal research includes topics of force development, acquisition and technology development, including recent projects on the long-term trends affecting U.S. power projection operations; the operational-industrial competitions in a protracted war; missile defense for an uncertain future; implications of mosaic warfare for requirements, resourcing and acquisition; concept options land-based fires in power projection scenarios; naval shipbuilding and munitions industrial base. From mid-2018 to early-2022, Predd served as Director of the NSRD Acquisition and Technology Policy Center (ATP), where has oversee a period of growth in the breadth and depth of RAND's portfolio of force development, technology and acquisition research for Office of the Secretary of Defense (OSD), the Joint Staff, the Combatant Commands and international sponsors. Predd spent fiscal year 2013 working in OSD (Policy) as a force development analyst, supporting Policy leadership in activities related to the 2014 Quadrennial Defense Review and the Strategic Choices Management Review. Prior to joining RAND, Predd earned a Ph.D. in electrical engineering from Princeton University on topics of machine learning, wireless networks, and probabilistic judgment aggregation. He has a B.S. in electrical engineering from Purdue University.
J. B. Predd, D. Osherson, S. R. Kulkarni and H. V. Poor, "Distributed Learning for Decentralized Inference in Wireless Sensor Networks," IEEE Signal Processing Magazine, Special Issue on Distributed Signal Processing in Wireless Sensor Networks, 2006
J. B. Predd, R. Seiringer, E. J. Lieb, D. Osherson, H. V. Poor, and S. R. Kulkarni, "Probabilistic Coherence and Proper Scoring Rules," IEEE Transactions on Information Theory, 55(10), 2009
J. B. Predd, D. Osherson, S. R. Kulkarni and H. V. Poor, "Aggregating Forecasts of Chance from Incoherent and Abstaining Experts," Decision Analysis, 5(4), 2008