Benjamin Johnson is a senior analytics manager and program manager in the National Security Portfolio for Accenture Federal Services. His current work focuses on the application of artificial intelligence to improve the Department of Defense intelligence community products to provide enriched data for analysis. His most recent academic papers have focused on data fusion and reinforcement learning for satellite tasking. Prior to joining Accenture, Johnson served in the United States Army as a Signal Officer for 10 years serving in various combat divisions including the 25th Infantry Division and the storied 1st Armored Division, he was medically discharged in 2010 as a Captain. During his military tenure he helped create curriculum for the Army’s Advanced Network Analysis and Targeting (ANAT) program and served as the founding member of the West Point Social Network Analysis Club (SNAC). In addition, he was a critical member of the Army Technical Control and Analysis Element (ATCAE) tasked with conducting network analysis to conduct data-driven insights for countering improvised explosive devices (IED) in Afghanistan and Iraq. Johnson holds a master’s degree in data science from the Johns Hopkins University Whiting School of Engineering and a bachelor’s degree in mathematics from the United States Military Academy at West Point.
Education History
- B.S., Mathematics, United States Military Academy
- M.S., Data Science, Johns Hopkins University
Work Experience
Senior Program Manager, Accenture Federal Services
Publications
McCulloh, I. A., Johnson, A. N., Eyre, S. K., Johnson, B. A., (2010). Advance Network Analysis
and Targeting Course Guide, TRADOC Technical Guide, Joint Training Counter IED Operations
Integration Center (JTCOIC), Newport News, VA
Casey J. Richards, Nawal Valliani, Benjamin A. Johnson, Nelson Ka Ki Wong, Angelo Pennati, Amir K. Saeed, Benjamin M. Rodriguez. (2023). Multimodal Data Fusion using Signal/Image Processing Methods for Multi-Class Machine Learning, SPIE, SPIE Defense + Commercial Sensing Program, Orlando, FL, May, 2023.
Amir Saeed, Francisco Holguin, Alhassan S. Yasin, Benjamin A. Johnson, Benjamin M. Rodriguez. (2024). Multi-Agent and Multi-Target Reinforcement Learning for Satellite Sensor Tasking in Low Earth Orbit, IEEE, 2024 IEEE Aerospace Conference, Big Sky, Montana, March, 2024
Dzmitry Kasinets, Amir K. Saeed, Benjamin A. Johnson, and Benjamin M. Rodriguez “Layered convolutional neural networks for multi-class image classification”, Proc. SPIE 13034, Real-Time Image Processing and Deep Learning 2024, 130340H (7 June 2024); https://doi.org/10.1117/12.3014054
Avi Shekhar, Amir K. Saeed, Benjamin A. Johnson, and Benjamin M. Rodriguez “Derivation, optimization, and comparative analysis of support vector machines application to multi-class image data”, Proc. SPIE 13033, Multimodal Image Exploitation and Learning 2024, 1303308 (7 June 2024); https://doi.org/10.1117/12.3014060
Amir K. Saeed, Francisco Holguin, Alhassan Yasin, Benjamin A. Johnson, Benjamin M. Rodriguez. (2024). Improving Computational Complexity of Multi-Target Multi-Agent Reinforcement for Hyperspectral Satellite Sensor Tasking, National Harbor, Maryland, SPIE Defense + Commercial Sensing, April 2024
Courses
Algorithms for Data Science
685.621
|
|
|
|