National Semiconductor Technology Center

Keysight Technologies' proposed project, "AI for Accelerating RFIC Design Efficiency, Innovation, and Optimization for U.S. Competitiveness," seeks to automate complex design tasks using AI-driven tools. The Keysight team, drawing on expertise from major commercial and defense companies, universities, and innovative startups, aims to make the AI-enhanced workflow accessible to designers of all experience levels. By driving automation, optimization, and generation of advanced and unique RFIC designs, the project will improve the productivity and competitiveness of participating members in the U.S. semiconductor industry and, itself, become a key framework for innovation.

Princeton University's proposed project, "IMAGINE: Inverse Methods and Generative AI for Algorithmic and Non-intuitive Design Explorations in RFICs," focuses on rapid, automated design and optimization from specifications to layout. The project aims to reduce design time and cost while discovering novel design spaces that enhance RFIC performance. The team, comprising top researchers from academia and industry, employs deep learning and generative AI to create predictive models and designs for complex RFICs.

UT Austin's proposed project, "GENIE-RFIC: Generative ENgine for Intelligent and Expedited RFIC Design,” targets both Silicon (Si) Complementary Metal Oxide Semiconductor (CMOS) RFICs and Gallium Nitride (GaN) Monolithic Microwave Integrated Circuits (MMICs). The AI-driven tools will perform rapid "inverse" designs based on target specifications, optimizing circuit topologies and parameters. The proposal features a strong team from academia and industry, a clear commercialization plan with Electronic Design Automation (EDA)/foundry/RFIC partnerships, and strategies for risk mitigation. The project aims to enhance RFIC design productivity and produce optimized, non-intuitive solutions.

ITC will use anticipated funding to launch the Enhanced Access to the Semiconductor Industry in Idaho (EASII) program. The initiative will provide support services to 430 participants in semiconductor workforce training programs in order to increase program completion rates and facilitate smoother transitions into semiconductor jobs.

Texas A&M will use anticipated funding to empower its WAVE-CHIP project. The project will equip more than 7,500 individuals in the semiconductor workforce with critical hardware verification skills, directly addressing the industry’s pressing need for qualified engineers.

MCCCD will use anticipated funding to expand its semiconductor technician training offerings and launch the Maricopa Accelerated Semiconductor Training (MAST) program, building on the success of the Quick Start program.

The UCLA Samueli School of Engineering will use anticipated funding to establish the Center for Education of Microchip Designers (CEMiD), which will provide comprehensive training in analog and digital chip design to engineering students and practicing engineers.

AFTEF will use anticipated funding to expand a partnership with Micron to implement an Advanced Technology Framework in high schools across New York, Michigan, and Minnesota. The program aims to equip students with the skills needed for careers in the microchip industry, fostering talent and bridging the gap between education and industry demands.

RIT will use anticipated funding to implement the Broadening Research and Inter-Disciplinary Graduate Education (BRIDGE) for Microelectronics program, with the goal to train 555 students at the bachelor’s and master’s degree levels, and through a new online certificate program, across microelectronics-related educational tracks.

Led by The Grainger College of Engineering at the University of Illinois Urbana-Champaign, the Illinois Semiconductor Workforce Network (ISWN) will use anticipated funding to address the critical shortage of skilled professionals in the U.S. semiconductor industry.