Speaker: Dr. Md Sakib Hasan, Assistant Professor, ECE, University of Mississippi
Topic: “Brain-Inspired, Energy-Efficient AI Hardware Using Beyond-CMOS Emerging Devices”
Abstract: Modern artificial intelligence (AI) is inspired by cognitive functions of the human brain through artificial neural networks. However, today’s AI models differ fundamentally from their biological counterparts. While they enable powerful capabilities, they impose substantial power and energy costs during both training and inference, which is often orders of magnitude higher than the human brain. Closing this efficiency gap will require neural computing frameworks that more closely reflect the mechanisms and constraints of biological computation.
In this talk, Dr. Hasan will present recent advances from his group on brain-inspired, energy-efficient computing enabled by emerging materials and devices, including biomolecular memristors and memcapacitors, resistive RAM (RRAM), and ferroelectric FETs (FeFETs). It will highlight a hardware–algorithm co-design approach that enables a transition from conventional von Neumann digital architectures to mixed-signal, in-memory computing platforms by leveraging the intrinsic device physics of these beyond-CMOS technologies. These synergistic developments offer a promising pathway toward scalable, low-power neural computing and the next generation of intelligent systems.
Biography: Dr. Md Sakib Hasan is an Assistant Professor of Computer Engineering in the Department of Electrical and Computer Engineering at the University of Mississippi. He joined the department in Fall 2019 and has served as the Graduate Program Coordinator since Fall 2025. He earned his B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology (BUET), Dhaka, in 2009, and his Ph.D. in Electrical Engineering from the University of Tennessee, Knoxville, in 2017. His research interests span brain-inspired computing and energy-efficient AI hardware, emerging devices, hardware security, nonlinear dynamical systems, and analog, mixed-signal, and digital VLSI design.
The Research Presentation is open to the public free of charge.
*For further information, please contact Dr. Liudong Xing via email at lxing@umassd.ed
Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
Liudong Xing
5089998883
lxing@umassd.edu