RESEARCH

Research at a Glance

In Low-Power Integrated Circuits and Embedded Systems Laboratory (LPiNS-Lab) our research goal is to use low-power algorithms, artificial intelligence, and machine learning to model and design energy-efficient integrated circuits and computer hardware architectures. Foundational and applied work extends across diverse audiences and applications. For example, our real-time, wearable biomedical devices detect sleep apnea in adults and premature infants and predict when pregnant women are at increased diabetes risk. Other “smart” devices seamlessly engage directly with the internet to support individuals and businesses. In short, our laboratory (1) develops energy-efficient algorithms for machine learning on hardware, (2) designs low-power integrated circuits and devices for critical healthcare applications, and (3) models and designs cyber-physical systems that integrate sensors.

Research Experience

Graduate Research (University of Missouri) : 08/2018-05/2023

Developing ML/Artificial-Intelligence Integrated Circuit Design for Biomedical Applications

Designing Low-Power ML/Artificial-Intelligence Hardware Architectures

Designing and Developing Non-Invasive Biomedical System for Healthcare Applications

Undergraduate Research (United International University): 01/2016-12/2017

Implemented NC-FET Characteristics Model in Verilog

Studied and Analyzed Different Characteristics of NC-FET Model using MATLAB

Other Research Involvement

Analyzing and Developing Low-Power Digital Hardware Components for ML/AI Models using VHDL

Measuring Voltage Matching using Machine-Learning in DC-DC Boost Converter

Developing SPICE Model of Electrical Impedance Analyzer for Detection of Bacteria Proliferation  in Food Samples

Modeling Various Statistical Analysis related to the Education Sector in Bangladesh using mathematical models

Publication List

Journal Papers:

Book Chapter

Conference Papers:

Projects

DeepSAC for Sleep Apnea Device

IEEE SSCS PICO Design Contest: Top 10

INFANT MONITORING SYSTEM

WINNER OF IEEE INERTIAL STUDENT DESIGN COMPETITION 2019: 1st Place

My GitHub Page