@article{1db3476cfc144b2e97db159bdab038be,
title = "BETTER PERFORMANCE, HIGHER RELIABILITY, MORE SECURITY: RESEARCH HIGHLIGHTS FROM THE CENTER FOR ADVANCED ELECTRONICS THROUGH MACHINE LEARNING",
author = "Aydin Aysu and Xu Chen and Davis, \{W. Rhett\} and Lim, \{Sung Kyu\} and Paul Franzon and Madhavan Swaminathan and Elyse Rosenbaum",
note = "The Center for Advanced Electronics through Machine Learning, or CAEML, is an Industry-University Cooperative Research Center (IUCRC) supported by the National Science Foundation. The IUCRC program supports pre-competitive research that is of high interest to industry. CAEML{\textquoteright}s research mission is to utilize machine learning for the design of optimized microelectronic circuits and systems and to increase the efficiency of electronic design automation. The center{\textquoteright}s work is carried out by researchers at the University of Illinois Urbana-Champaign, Georgia Tech, and North Carolina State University. As part of NSF{\textquoteright}s IUCRC program, CAEML is additionally tasked with building the workforce by assigning university students to conduct industry-relevant research and helping those students to become skilled at collaboration and communication.",
year = "2022",
month = may,
language = "English (US)",
volume = "24",
pages = "34--36",
journal = "Electronic Device Failure Analysis",
issn = "1537-0755",
publisher = "ASM International",
number = "2",
}