Joel B. Predd
Overview
Biography
Joel Predd is an engineer at the RAND Corporation. His research has supported clients including the U.S. Office of the Secretary of Defense, Army, Navy, Air Force, and Department of Homeland Security, and it has addressed topics such as acquisition, border security, information security, operational analysis, and technology policy. Predd's methodological interests include machine learning and data visualization. Predd received his Ph.D. in electrical engineering from Princeton University.
Research Focus
Recent Projects
- Resource Allocation, Pattern Analysis, and Systematic Randomness: Assessing Possibilities for Border Security
- Implications of Open Architecture for the Aegis System
- On the Effect of Complexity on the Cost of Avionics
- Science and Technology for Decisive Squads
- Methodologies for Counter-IED Operational Analysis
Selected Publications
J. B. Predd, D. Osherson, S. R. Kulkarni and H. V. Poor, "A Collaborative Training Algorithm for Distributed Learning," IEEE Transactions on Information Theory, 55(4), 2009
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
J. B. Predd, S. L. Pfleeger, J. Hunker and C. Buford, "Insiders Behaving Badly," IEEE Security and Privacy, 6(4), 2008
J. B. Predd, D. Osherson, S. R. Kulkarni and H. V. Poor, "Consistency in Models of Distributed Learning Under Communication Constraints," IEEE Transactions on Information Theory, 52(1), 2006
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
