• Diversity Statement

    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 UC Davis community shares these sentiments.

  • Hardware Security

    GATE lab Study various aspects of Hardware Security

  • Neuromorphic Computing

    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 intellectual property.

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Neuromorphic HW Design

Neuromorphic 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.

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Applied Machine Learning and Learning Security

Applied learning in digital design offers many opportunities for optimization. Learning security deals with protecting the learning model against adversarial examples.

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Internet of Things

The Internet 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.

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About GATE Research Group

Dr. 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.

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Journal and Conference Publications
Million USD Grants Received
Research members at GATE lab

Dr. Sasan

Dr. Sasan joined the University of California, Davis, in 2021. He is currently an Associate Professor in the Department of Electrical and Computer Engineering. Dr. Sasan's research spans hardware security, machine learning, neuromorphic computing, low-power design, approximate computing, and the Internet of Things (IoT).

  1. 2021-Present

    Associate Professor

    Electrical and Computer Engineering Department
    University of Califorrnia Davis, Davis, California, USA
  2. 2016-2021

    Associate Professor

    Electrical and Computer Engineering Department
    George Mason University, Fairfax, Virginia, USA
  3. 2014-2016

    Sr. Scientist

    VLSI Technology Group
    Qualcom Co., San Diego, California, USA
  4. 2010-2014

    Sr. Scientist

    Office of CTO, Ceneter of ARM Excellence
    Broadcom Co., Irvine, California, USA
  5. 2010


    Electrical and Computer Engineering
    University of California, Irvine, USA
  6. 2006


    Electrical and Computer Engineering
    University of California, Irvine, USA
  7. 2005

    B.Sc. (Summa Cum Laude)

    Electrical and Computer Engineering
    University of California, Irvine, USA