Peyman Najafirad (Paul Rad) Ph.D

Peyman Najafirad (Paul Rad) Ph.D

Associate Professor, Information Systems and Cyber Security

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Related Projects

Dr. Paul Rad started his career as a computer architect by founding Data Processing Corp, overseas before moving to the United States, and later held product and services leadership roles at Data Concepts and Dell Inc. He has numerous published articles on enterprise solutions and holds several U.S. patents in the fields of virtualization, clustering, software engineering and quality assurance. Paul holds a Master of Computer Architecture from Sharif University and a Master of Computer Science from University of Texas at San Antonio. Paul has been a strong supporter of connecting university and industry in order to build the future workforce. He is a standing committee member of Quantitative Literacy at University of Texas at San Antonio.

Educational Background:

Ph.D., The University of Texas at San Antonio

Field of Study:

Data Analytics and Artificial Intelligence (AI)

Areas of Research Interest:

Decision Making and Autonomy
Machine Learning Algorithm
Distributed Real-Time Computing


Miraftabzadeh, Seyed Ali, Paul Rad, Kim-Kwang Raymond Choo, and Mo Jamshidi. "A privacy-aware architecture at the edge for autonomous real-time identity reidentification in crowds." IEEE Internet of Things Journal 5, no. 4 (2017): 2936-2946.

Polishetty, Rohith, Mehdi Roopaei, and Paul Rad. "A next-generation secure cloud-based deep learning license plate recognition for smart cities." In 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 286-293. IEEE, 2016.

Rad, Paul, Mehdi Roopaei, Nicole Beebe, Mehdi Shadaram, and Yoris Au. "AI Thinking for Cloud Education Platform with Personalized Learning." In Proceedings of the 51st Hawaii International Conference on System Sciences. 2018.

Silva, Samuel Henrique, Paul Rad, Nicole Beebe, Kim-Kwang Raymond Choo, and Mahesh Umapathy. "Cooperative unmanned aerial vehicles with privacy preserving deep vision for real-time object identification and tracking." Journal of Parallel and Distributed Computing 131 (2019): 147-160.

Das, Arun, Paul Rad, Kim-Kwang Raymond Choo, Babak Nouhi, Jonathan Lish, and James Martel. "Distributed machine learning cloud teleophthalmology IoT for predicting AMD disease progression." Future Generation Computer Systems93 (2019): 486-498.

De La Torre, Gonzalo, Paul Rad, and Kim-Kwang Raymond Choo. "Implementation of deep packet inspection in smart grids and industrial Internet of Things: Challenges and opportunities." Journal of Network and Computer Applications(2019).