Several categories of graduate faculty exist at George Mason University. Current Mason tenured and tenure-track faculty are automatically granted active graduate faculty status and maintain that status throughout their employment as tenure-line faculty. Please see the list of CEC’s tenured and tenure-track graduate faculty below. CEC and Provost-appointed non-tenured/tenure-track graduate faculty can be found in the database located on the Provost’s Office website.
Meet the College of Engineering and Computing Tenured and Tenure-Track Graduate Faculty
Assistant Professor, Department of Statistics
Research Interests: Bayesian inference, deep learning, deep generative models, high-dimensional statistics, scalable algorithms, causal inference, survival analysis
Assistant Professor, Department of Computer Science
Research Interests: Cryptography, privacy, and data security
Assistant Professor, Department of Cyber Security Engineering
Research Interests: Analog Cryptography and Sensor Fusion; Sensor Hardware, Micro-architectural, and Embedded System Security; Machine Learning, Artificial Intelligence, Memory System Security, Low-power Intelligent Hardware and Algorithms; Designing Algorithms and Systems
Assistant Professor, Department of Mechanical Engineering
Research Interests: Additive Manufacturing, Tribology, Multiscale Contact and Interface Mechanics, High Temperature Materials, Thin Films/Coatings, Surface Engineering, Failure Mechanics
Associate Professor, Department of Electrical and Computer Engineering
Research Interests: Electronics
Associate Professor / Tenured
Research Interests: Artificial Intelligence and Machine Learning, Educational Technology, Human-Centered Computing
Professor, Bioengineering and Mechanical Engineering
Research Interests: Stroke, cerebral aneurysms, blood flow, image-based modeling, patient-specific modeling, computational fluid dynamics, hemodynamics, modeling medical devices
Professor, Department of Systems Engineering and Operations Research
Research Interests: Information fusion, Bayesian networks, distributed sensor networks, decision making under uncertainty, explainable AI