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Research at a Glance
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.
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
Research Experience
Graduate Research (University of Missouri) : 08/2018-05/2023
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
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
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
Publication List
Journal Papers:
Journal Papers:
O. Hassan, T. Paul, N. Amin, T. Titirsha, D. Parvin, A. S. M. Mosa and S. K. Islam, “An Optimized Hardware Inference of SABiNN: Shift-Accumulate Binarized Neural Network for Sleep Apnea Detection”, IEEE Transactions on Instrumentation and Measurements, IEEE, 2023, April.
O. Hassan, T. Paul, M. M. Hossain Shuvo, D. Parvin, R. Thakker, M. Chen, A. S. M. Mosa and S. K. Islam, “Energy Efficient Deep Learning Inference Embedded on FPGA for Sleep Apnea Detection”, Journal of Signal Processing Systems, Springer, 2022.
D. Parvin, O. Hassan, T. Oh, S. K. Islam, “Design of a Smart Maximum Power Point Tracker (MPPT) for RF Energy Harvester”, International Journal of High-Speed electronics and systems. doi:10.1142/S0129156420400066
T. Oh, D. Parvin, O. Hassan, S. Shamsir, S. K. Islam, “MPPT Integrated DC-DC Boost Converter for RF Energy Harvester”, in IET Circuits, Devices and Systems. (doi: 10.1049/iet-cds.2019.0509 )
M. M. S. Hassan and O. Hassan, “Higher Education and Creation of Jobs in Bangladesh”, European Journal of Teaching and Education.
M. M. S. Hassan and O. Hassan, “The Importance of Changing the Traditional Mode of Higher Education in Bangladesh: Creating huge Job Opportunities for Home and Abroad”, 21st Int. Conf. On Employment, Education and Entrepreneurship (ICEEE), June 2019.
Book Chapter
Book Chapter
S. Shamsir, M. S. Hasan, O. Hassan, P. S. Paul, M. R. Hossain, M. R. Islam, “Semiconductor Device Modeling and Simulation for Electronic Circuit Design”, In Modeling and Simulation in Engineering, IntechOpen, April 29 2020.
Conference Papers:
Conference Papers:
O. Hassan, R. Thakker, T. Paul, D. Parvin, and S. K. Islam, “SABiNN: FPGA Implementation of Shift Accumulate Binary Neural Network Model for Real -Time Automatic Detection of Sleep Apnea”, 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).
O. Hassan, T. Paul, R. Thakker, D. Parvin, M. M. H. Shuvo, A. S. M. Mosa, S. K. Islam, “A Multi-Sensor Based Automatic Sleep Apnea Detection System for Adults Using Neural Network Inference on FPGA “, The 17th Edition IEEE Medical Measurements and Application Conference 2022
D. Parvin, O. Hassan, T. Titirsha and S. K. Islam, “FPGA Implementation of an Energy Efficient Neural Network Model for Maximum Power Point Tracking”, National Radio Science Meeting (USNC-URSI) 2022.
T. Paul, O. Hassan, S. K. Islam and A. S. M. Mosa, “ECG and SpO2 Signal-Based Real-Time Sleep Apnea Detection Using Feed-Forward Artificial Neural Network”, American Medical Informatics Association (AMIA) Symposium, 2022.
M. M. Hossain Shuvo, O. Hassan, D. Parvin, M. Chen and S. K. Islam, "An Optimized Hardware Implementation of Deep Learning Inference for Diabetes Prediction," 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2021, pp. 1-6.
D. Parvin, O. Hassan, T. Oh and S. K. Islam, "RF Energy Harvester Integrated Self-Powered Wearable Respiratory Monitoring System," 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2021, pp. 1-6,
O. Hassan, D. Parvin and S. K. Islam, “Machine Learning Model Based Digital Hardware System Design for Detection of Sleep Apnea Among Neonatal Infants”, The 63rd Edition of IEEE International Midwest Symposium on Circuits and Systems 2020.
O. Hassan, S. Shamsir and S. K. Islam, “Machine Learning Based Hardware Model for a Biomedical System for Prediction of Respiratory Failure”, The 15th Edition of IEEE International Symposium on Medical Measurements and Applications 2020.
S. Shamsir, O. Hassan and S. K. Islam, “Smart Infant-Monitoring System with Machine Learning Model to Detect Physiological Activities and Ambient Conditions”, IEEE International Instrumentation & Measurement Technology Conference 2020.
Oh. T, O. Hassan, S. Shamsir and S. K. Islam, “DC-DC Boost Converter Design with Maximum Power Point Tracker (MPPT) used in RF- Energy Harvester”, IEEE International Symposium on Medical Measurements and Applications, June 2019.
Oh. T, O. Hassan, S. Shamsir and S. K. Islam, “Low-Power RF Energy Harvester Circuit Design for Wearable Medical Applications” , National Radio Science Meeting (USNC-URSI), Jan 2019
Projects
Projects
INFANT MONITORING SYSTEM
INFANT MONITORING SYSTEM
WINNER OF IEEE INERTIAL STUDENT DESIGN COMPETITION 2019: 1st Place
My GitHub Page
My GitHub Page
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