Syed Kamrul Islam
Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211

When: Wednesday September 13, 2023 2:00 pm
Where: SERC 1013


Rapid development of sensor technologies, CMOS fabrication processes and wireless sensor network technologies have unlocked new and innovative applications of health monitoring systems. For long-term reliable detection of various biological signals in point-of-care health monitoring systems it is essential to provide adequate power savings for the associated electronic circuits. A solution for designing low-power and high-performance integrated circuits for readout electronics involves implementation of machine learning/deep learning algorithms into CMOS integrated circuits to process any type of physiological signals, including respiratory, ECG or EEG signals. Various machine learning models, such as deep learning architectures, have been employed to design intelligent healthcare systems. However, deploying these sophisticated and intelligent devices in real-time embedded systems with limited hardware resources and power budget is complex due to the requirement of high computational power in achieving a high accuracy rate. As a result, this creates a significant gap between the advancement of computing technology and the associated device technologies for healthcare applications. Power-efficient machine learning-based digital hardware design techniques have been introduced in this work for the realization of a compact design solution while maintaining optimal prediction accuracy. This has a potential to become a versatile signal processing hardware platform for biomedical instrumentation. Integrating machine learning functions and algorithms into a single CMOS integrated circuit and implementing it in a deep submicron CMOS process targeting very low power consumption will be a potential new approach to the development of future wearable medical devices and technologies.

Syed Kamrul Islam received B.Sc. degree in electrical and electronic engineering from Bangladesh University of Engineering and Technology (BUET), Dhaka, and the M.S. and Ph.D. degrees in electrical and systems engineering from the University of Connecticut, Storrs. He is currently serving as Professor and Chair of the Department of Electrical Engineering and Computer Science at the University of Missouri. His research interests include semiconductor devices, nanotechnology, bio-microelectronics and monolithic sensors. He has more than 100 publications in refereed journals, more than 150 papers in conference proceedings, and a number of invited talks. He also co-authored a book and 12 book chapters. Prior to joining the Department of Electrical Engineering and Computer Science at the University of Missouri in July 2018, he served as James W. McConnell Professor and Associate Head of the Department of Electrical Engineering and Computer Science at the University of Tennessee. In recognition of his teaching, research and related efforts at the University of Tennessee he received John W. Fisher Professorship, Eta Kappa Nu Outstanding Teacher Award, Moses E. and Mayme Brooks Distinguished Professor Award, College of Engineering Research Fellow Award, The Gonzalez Family Award for Excellence in Teaching, Tickle College of Engineering Teaching Fellow, University of Tennessee Citation for Research and Creative Achievement, Electrical and Computer Engineering Faculty of the year award and the Alexander Prize. He also received Outstanding Electrical Engineering Professor award at the University of Missouri.