Reza Jafari

Reza Jafari is a Collegiate Associate Professor of Computer Science at the Virginia Tech Innovation Campus. He previously served as faculty and program director of the ECE program at East Coast Polytechnic University and as a professional lecturer in the data science program at George Washington University. His research focuses on data mining, statistical modeling, machine learning/deep learning for prediction/classification, recurrent neural networks, and stability analysis of neural-based systems.

Education:

• Ph.D., Computer and Electrical Engineering, Oklahoma State University (2012)
• M.S., Applied Mathematics, Oklahoma State University (2011)
• M.S., Mechatronics, American University of Sharjah (2005)
• B.S., Engineering, University of Tehran (2001)

Research Interests: Jafari's work spans data analytics, statistical forecasting, machine learning, and neural networks. He emphasizes practical applications, such as temporal forecasting using deep learning and stability analysis of control systems. His contributions include advancements in recurrent neural networks and their hardware implementations.

Publications: His recent work includes comparative studies of deep learning architectures for temporal forecasting (2025), precision robotics control (2024), and stability analysis of neural network-based controllers (2023). These studies highlight a trend toward integrating traditional methods with modern machine learning techniques.

Awards:

• Innovator of the Year Award (2014)
• Innovator of the Year Award (2016)

Professional Roles: Jafari has served as a peer reviewer for IEEE Transactions, IJCNN, and Automatic Control. His research bridges theoretical foundations and applied systems, with a focus on interdisciplinary solutions in data science and engineering.