
GATE lab is committed to practicing inclusion, cultivating diversity, and rejecting discrimination in any form. GATE lab is eager to recruit new members of all races, ethnicities, religions, sexual orientations, and skin colors. The entire GMU community shares these sentiments.
Gate lab engages in the study of efficient learning models, learning model security, and implementation of Neuromorphic Hardware READ MORE
Hardware is the root of trust! Secrets are stored in Hardware! Hardware also embeds valuable intellectual property. Hardware security is the science of building trust, protecting secrets, and protecting the IP.
Read MoreNeuromorphic HW design is the science of architecting HW solutions for efficient execution of learning models to widen the application of learning models in low-power mobile, embedded, & edge IoT devices.
Read MoreApplied Learning in digital design brings many opportunities for optimization. Learning security deals with protecting the learning model against adversarial examples.
Read MoreInternet of Things is the enabler of pervasive computing and ambient intelligence. The IoT research topics investigated in the GATE lab include low energy computing, IoT security, and user privacy.
Read MoreDr. Avesta Sasan manages the Green, Accelerated, and Trustworthy Engineering (GATE) laboratory. Research of this laboratory spans hardware security, Neuromorphic hardware design, applied-learning for digital and VLSI design, and low power, trusted, and privacy-preserving IoT Solutions.
Read MoreDr. Sasan joined George Mason University in 2016. He is currently serving as an Associate Professor in the Department of Electrical and Computer Engineering. He also servers as the Associate Chair for Research at the Electrical and Computer Engineering Department at GMU. Dr. Sasan's research spans hardware security, machine learning, neuromorphic computing, low power design, approximate computing, and the Internet of Things (IoT).
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