Benjamin Rodriguez

Dr. Benjamin M. Rodriguez is a Johns Hopkins University faculty leader in data science, data analytics, and artificial intelligence, combining cutting-edge research with real-world applications in complex systems and national security. As Chair of the Information Systems Engineering Program and Co-Chair of the Data Science Program at the Johns Hopkins Whiting School of Engineering, he drives innovation in graduate education, shaping curricula that prepare professionals to lead in data science, information systems, artificial intelligence, machine learning, and advanced analytics.

At the Johns Hopkins University Applied Physics Laboratory (JHU/APL), Dr. Rodriguez serves as Principal Professional Staff, directing multidisciplinary teams that develop complex systems, machine learning algorithms, and intelligent analytics frameworks for space-based sensing, air systems, force design modeling, and test & evaluation. His research focuses on data fusion, intelligent system design, pattern recognition, autonomous decision-making, and modeling & simulation, with expertise across a wide range of sensing technologies.

Through his dual roles in research and academia, Dr. Rodriguez integrates AI and data-driven engineering to accelerate innovation, strengthen mission systems, and cultivate the next generation of leaders in data science, information systems, artificial intelligence, and data analytics at Johns Hopkins University.

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, Erhan Guven, PhD, Vy Vu, and Benjamin M. Rodriguez, PhD, Agentic AI for Intelligent and Collaborative Air Traffic Control Agentic AI for Intelligent and Collaborative Air Traffic Control, SPIE Defense+ Commercial Sensing, National Harbor, MD, April, 2026 (Submitted)

Amir K. Saeed, Alhassan Yasin, PhD, Benjamin A. Johnson, Erhan Guven, PhD, and Benjamin M. Rodriguez, PhD, Bayesian Network Guided Vulnerability Analysis of Detection, Fusion Continuity, and Sensor Handoffs for Aircraft Custody in Terminal Airspace, SPIE Defense+ Commercial Sensing, National Harbor, MD, April, 2026 (Submitted)

Amir K. Saeed, Alhassan Yasin, Benjamin A. Johnson, and Benjamin M. Rodriguez, PhD, GoDSAT-AT: An RL-Enabled, Multi-Sensor M&S Framework for Persistent Aircraft Custody in Terminal Airspace, SPIE Defense+ Commercial Sensing, National Harbor, MD, April, 2026 (Submitted)

Kyle Beach, Amir K. Saeed, Alhassan Yasin, Benjamin A. Johnson, and Benjamin M. Rodriguez, PhD, DataOps-to-Decision: Reproducible Analytics for Multi-Sensor Aircraft Tracking with GoDSAT-AT, SPIE Defense+ Commercial Sensing, National Harbor, MD, April, 2026 (Submitted)

Xiaohu Wang, Amir K. Saeed, Benjamin A. Johnson, and Benjamin M. Rodriguez, PhD, Melanoma detection, Latent variable modeling, Multimodal learning, Patient-level representation, Convolutional neural networks (CNNs), Pretrained models, Medical image analysis, SPIE Defense+ Commercial Sensing, National Harbor, MD, April, 2026 (Submitted)

Kyle Beach, Amir K. Saeed, Benjamin A. Johnson, and Benjamin M. Rodriguez, PhD, Swing Shape Analysis: Leveraging Bat Tracking Data for Baseball Performance Insights, International Conference on Kinesiology, Exercise and Sport Sciences (Submitted)

Amir K. Saeed, Alhassan Yasin, Nicholas A.V. Realyuo, Alhassan Yasin, Benjamin A. Johnson, and Benjamin M. Rodriguez, PhD, GoDSAT: Reinforcement Learning Based Satellite Constellation Sensor Tasking Framework, IEEE Aerospace Conference, Big Sky, Montana, March, 2026 (Submitted)

Devin J Ullerick and Dzmitry Kasinets, Jayeeta Ghosh, Dilshad Akkam Veettil, Amir K. Saeed, Benjamin A. Johnson, Benjamin M. Rodriguez. (2025). Transformer-Based Image Captioning as a Framework for Defense Applications. Orlando, FL, SPIE Defense + Commercial Sensing 2025 Program, April, 2025

Amir K. Saeed, Devin J Ullerick, Benjamin A. Johnson, Benjamin M. Rodriguez. (2025). Enhancing Situational Awareness Through Hybrid Learning: Fusing Supervised and Unsupervised Techniques for Defense Applications. Orlando, FL, SPIE Defense + Commercial Sensing 2025 Program, April, 2025

Amir K. Saeed, Anthony Trautman, Chris Windle, Benjamin M. Rodriguez. (2025). Connecting Disparate Modeling and Simulation Studies Through Design of Experiments, Surrogate Modeling, and Bayesian Networks. Orlando, FL, SPIE Defense + Commercial Sensing 2025 Program, April, 2025

Amir K. Saeed, Anthony Trautman, Chris Windle, Benjamin M. Rodriguez. (2025). A Systematic Framework for Design of Experiments in System Design: Establishing Order and Relevance in First-Order Analysis. Orlando, FL, SPIE Defense + Commercial Sensing 2025 Program, April, 2025

Amir K. Saeed, Matthew Walsh, Anthony Trautman, Dylan Payne, Garrett Gallaher, Benjamin M. Rodriguez. (2025). Ensuring Accurate Navigation Solution in GPS-Denied Scenarios with Machine Learning, IEEE, 2025 IEEE Aerospace Conference, Big Sky, Montana, March, 2025

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

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