Yang (Cindy) Yi

Virginia Tech

Yang (Cindy) Yi is a tenured associate professor in the Bradley Department of Electrical and Computer Engineering (ECE), Virginia Polytechnic Institute and State University (Virginia Tech), USA, where she is also the director of the Multifunctional Integrated Circuits & Systems (MICS) Group. Over the past 18 years, she has been working on various research topics in integrated circuits, neuromorphic computing, high performance computing and communication at Texas A&M University, IBM, Freescale, Intel, Texas Instruments (TI), University of Missouri Kansas City, University of Kansas (KU), and Virginia Tech. She has 180 publications in international journals, conference proceedings, and book chapters to her credit. Eleven of her papers have been selected for various best paper awards. Dr. Yi has received numerous awards for her research and service, including 2023 Institute of Electrical and Electronics Engineers (IEEE)  Featured Author, 2020 Jeffress Trust Research Award, 2019 Virginia Tech College of Engineering Faculty Fellow and Virginia Tech Institute for Critical Technology and Applied Science (ICTAS) Junior Faculty Award, 2018 National Science Foundation (NSF) CAREER Award, a United States Air Force (USAF) Summer Faculty Fellowship, 2016 University of Kansas (KU) Miller Professional Development Award for Distinguished Research, NSF CISE Research Initiation Initiative (CRII) Award, NSF EPSCoR First Award, USAF Summer Faculty Fellowship, 2015 KU Miller Scholar Award, KU New Faculty General Research Award, Air Force Research Lab (AFRL) Visiting Faculty Research Fellowship, University of Missouri (MU) Academic Program Faculty Scholar, and 2014 MU Outstanding Service Award.

Yang (Cindy) Yi

2books edited

3chapters authored

Latest work with IntechOpen by Yang (Cindy) Yi

Dive into the cutting-edge world of Neuromorphic Computing, a groundbreaking volume that unravels the secrets of brain-inspired computational paradigms. Spanning neuroscience, artificial intelligence, and hardware design, this book presents a comprehensive exploration of neuromorphic systems, empowering both experts and newcomers to embrace the limitless potential of brain-inspired computing. Discover the fundamental principles that underpin neural computation as we journey through the origins of neuromorphic architectures, meticulously crafted to mimic the brain’s intricate neural networks. Unlock the true essence of learning mechanisms – unsupervised, supervised, and reinforcement learning – and witness how these innovations are shaping the future of artificial intelligence.

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