In-Memory Computing Hardware Accelerators for Data-Intensive Applications (PDF)

> 100Watt (IA-64), to mobile embedded processor low power sub 1 watt (xscale). He has over 16 years of industrial experience in microprocessor design, emphasizing memory, low power circuit, and physical design. Baker earned his Ph.D. from the University of Texas at Austin in 2008, his M.S. degree from Arizona State University, Tempe, and BS degree from the University of New Mexico, Albuquerque, all in ECE. His research interests include VLSI, power-efficient computing, embedded memory and in-memory computing, neuromorphic computing, emerging technology such as Memristor, STTRAM, hardware accelerators for Cyber-Physical Systems and AI. He is also engaged in a microwatt range computing platform for wearable electronics and WSN focusing on energy harvesting, power management, and power conversion, including efficient dc/dc, ac/dc converters. Baker authored/co-authored over 200 referred journals and conference proceedings, >3 books, >18 US patents, multiple invited seminars/panelists, and the presenter of >3 conference tutorials, including one tutorial on Energy harvesting and Power management for WSN at the 2015 (ISCAS). Baker is an associate editor for IEEE Access, IEEE Transaction on VLSI (TVLSI), and Scientific Reports journals. Dr Mohammad participates in many technical committees at IEEE conferences and reviews for TVLSI, IEEE Circuits and Systems journals. He has received several awards, including the KUSTAR staff excellence award in intellectual property creation, IEEE TVLSI best paper award, 2016 IEEE MWSCAS Myrill B. Reed best paper award, Qualcomm Qstar award for excellence on performance and leadership. SRC Techon best session papers for 2016 and 2017. 2009 Best paper award for Qualcomm Qtech conference and Intel Involve in the community award for volunteer and impact on the community.



Yasmin Halawani is a Postdoctoral Fellow at Khalifa University in Abu Dhabi, UAE.