Shimeng Yu is a full professor of electrical and computer engineering at Georgia Institute of Technology. He received the B.S. degree in microelectronics from Peking University in 2009, and the M.S. degree and Ph.D. degree in electrical engineering from Stanford University in 2011 and 2013, respectively. From 2013 to 2018, he was an assistant professor at Arizona State University. He is elevated for the IEEE Fellow for the contributions to non-volatile memories and in-memory computing.

In response to the escalating computational demands of today's AI applications, specialized hardware accelerators are emerging as pivotal facilitators for enhancing system-level energy efficiency. This presentation advocates for a cross-layer co-design methodology aimed at advancing AI hardware and 3D IC designs. Specifically, we will unveil a prototype chip design featuring in-memory computing with resistive memories (RRAM), alongside a groundbreaking approach for ultra-low power charge-domain computation utilizing programmable non-volatile ferroelectric capacitors (nvCap).