Benjamin Rodriguez

Benjamin M. Rodriguez has a background in statistical signal processing with a focus on data science, intelligent systems and machine learning. His current work duties include research and development in algorithms development, data processing, information retrieval, intelligent system design, recognition techniques, and fusion of multiple data sources, including sensor data for pattern association, decision making and tracking. He has worked on projects related to target identification using SAR, Hyperspectral and Panchromatic imagery along with facial recognition, fingerprint matching, voice recognition, web crawling, and breaking encoded messages within transmitted signals. He also has conducted research in radar, lidar, and optical sensors for target recognition/tracking using generated features, feature preprocessing techniques, classification models and fusion methods. Other areas of his research include pattern recognition using image, signal, and video processing techniques for face recognition, finger print matching, anomaly detection and voice recognition. His software engineering experience includes Unix, Linux, and Window operating systems and programming using assembly, C/C#/C++, ENVI IDL, Java, Matlab, Python and R. Dr. Rodriguez is also a full time Johns Hopkins University – Applied Physics Laboratory (JHU-APL) Principal Professional Staff since 2008.

Education History

• Ph.D, Electrical and Computer Engineering – Statistical Signal Processing, Air Force Institute of Technology

Work Experience

Principal Professional Staff, JHU Applied Physics Laboratory

Publications

Amir K. Saeed, Benjamin M. Rodriguez. (2024). Leveraging Deep Learning for Data Processing to Improve Discriminative Modeling Capabilities, National Harbor, Maryland, SPIE Defense + Commercial Sensing, April 2024

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

Avi Shekhar, Amir K. Saeed, Benjamin A. Johnson, Benjamin M. Rodriguez. (2024). Derivation, optimization, and comparative analysis of support vector machines application to multi-class image data, National Harbor, Maryland, SPIE Defense + Commercial Sensing, April 2024

Dzmitry Kasinets, Amir K. Saeed, Benjamin A. Johnson, Benjamin M. Rodriguez. (2024). Layered convolutional neural networks for multi-class image classification, National Harbor, Maryland, SPIE Defense + Commercial Sensing, April 2024

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

Amir Saeed, Francisco Holguin, Jonathon Gabriel, Alhassan S. Yasin, Benjamin M. Rodriguez. (2023). Reinforcement Learning Application to Satellite Constellation Sensor Tasking, SPIE, SPIE Defense + Commercial Sensing Program, Orlando, FL, May, 2023.

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.

Cindy Gonzales, Benjamin M. Rodriguez. (2022). An Empirical Study of Digital Signal Filtering to Improve Alzheimer’s Disease Detection, SPIE, Applications of Machine Learning 2022, San Diego, California, August, 2022.

Professional Organizations

Tau Beta Pi Honor Society
Eta Kappa Nu Honor Society
The Society of Mexican American Engineers and Scientists
IEEE