Abbrevation
ISQED
City
Santa Clara
Country
United States
Deadline Paper
Start Date
End Date
Abstract

Papers are requested in the following areas<br>A pioneer and leading multidisciplinary conference, ISQED accepts and promotes papers related to the manufacturing, design and EDA&#046; Authors are invited to submit papers in the various disciplines of high level design, circuit design (digital, analog, mixed&#8211;signal, RF), test &amp; verification, design automation tools; processes; flows, device modeling, semiconductor technology, advance packaging, and biomedical &amp; bioelectronic devices&#046; All past Conference proceedings &amp; Papers have been published in IEEE Xplore digital library and indexed by Scopus&#046;<br>Electronic Design<br>System&#8211;level Design, Methodologies &amp; Tools<br>IOT &amp; Smart Sensors &#8211; Technology and Design<br>FPGA Architecture, Design, and CAD<br>IC Package &#8211; Design Interactions &amp; Co&#8211;Design<br>Advanced 3D ICs &amp; 3D Packaging<br>Robust &amp; Power&#8211;conscious Circuits &amp; Systems<br>Emerging/Innovative Process &amp; Device Technologies and Design Issues<br>Design of Reliable Circuits and Systems<br>Embedded Systems Design<br>Cyber&#8211;Physical Systems – Design, Methodologies &amp; Tools<br>Design Automation and IP<br>IP Design, quality, interoperability and reuse<br>Design Verification and Design for Testability<br>Physical Design, Methodologies &amp; Tools<br>EDA Methodologies, Tools &amp; Flows<br>Manufacturing, Semiconductor Processes and Devices<br>Design&#8211;Technology Co&#8211;Optimization<br>Design for Manufacturability/Yield &amp; Quality<br>Effects of Technology on IC Design, Performance, Reliability, and Yield<br>Hardware and System Security<br>Hardware Attacks – Detection, Threat Modeling &amp; Defense<br>Hardware&#8211;Based Security Primitive Design<br>Trusted Design Automation, Tools &amp; Information Flow<br>Cognitive Computing in Hardware<br>Hardware Accelerators for Machine/Deep Learning Algorithms<br>Algorithmic Optimizations for General Purpose Computing<br>ML Partitioning from Cloud to Sensor&#8211;node<br>