UC San Diego Computer Scientist Honored for Excellence in Semiconductor Design Research

UC San Diego Computer Scientist Honored for Excellence in Semiconductor Design Research

“Research drives game-changing innovations in semiconductors and the countless technologies they enable,” said John Neuffer, president and CEO of SIA, which represents US leadership in semiconductor manufacturing, design, and research. The award winners are “advancing American innovation and helping to make the world smarter, more efficient, and better connected,” he said.

Neuffer also highlighted the importance of recent enactment of the CHIPS and Science Act, which provides critical semiconductor manufacturing incentives and research investments. This federal research funding will complement existing large investments from the semiconductor industry, which plows about one-fifth of revenue into research and development. Robust investments in research, including semiconductor research, are vital to maintaining our country’s technological edge, according to the SIA and SRC.

“SRC is excited to select, in close collaboration with our industry members, Professor Tajana Rosing for the University Research Awards in semiconductor design,” said Dr. Todd Younkin, President and CEO of SRC, a non-profit consortium that works with industry, government and academia partners on university research on behalf of its members. “She joins a distinguished lineup of past award winners based on their incredible contributions into the semiconductor industry.”

rosing is the director of the System Energy Efficiency Lab at UC San Diego. Her research interests are in energy-efficient computing, cyber-physical and distributed systems. Inspired by the human brain, Rosing’s research work on hyperdimensional computing systems has been accelerated using GPUs, field-programmable gate arrays (FPGAs), and processing in memory and storage to handle high-dimensional vectors in data-intensive applications, including for genomics, COVID-19 analysis, mass spectrometry, machine learning, recommendation systems, and many other applications.

Her approaches are delivering impressive accuracy in learning from big data with excellent performance, extreme energy efficiency and robustness.

Her work has also had practical applications to optimize data analysis both in the cloud, at the edge and in the Internet of Things, resulting in systems that are significantly more energy efficient. Her recent projects include federated and distributed learning in the Internet of Things, optimization and deployment of sensing and actuation for the Smart Cities, power, thermal and reliability management for the datacenters and mobile systems, and many others.

Rosing is a fellow of both Institute of Electrical and Electronics Engineers (IEEE) and Association for Computing Machinery (ACM).

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