Projects
Researcher
Title: A MACHINE LEARNING BASED ANALYSIS OF SLEEP PATTERNS IN AGING USING PHYSIOLOGICAL SIGNALS
Description: This ongoing PhD research focuses on leveraging machine learning techniques to investigate age-related variations in sleep dynamics using physiological signals such as EEG, ECG, and PPG. The study aims to identify discriminative features and biomarkers that can assist in understanding sleep degradation with aging, enabling early detection and intervention for sleep-related disorders in elderly populations.
Fund: Cotutelle program studentship
Funding Organisation: Centre for Computational Science and Mathematical Modelling (CSM) - Modelling
Collaboration Organisation: Coventry University (UK), Deakin University (Austrlia)
Period: Jan. 1, 2023 - Present
Research Assistant (Casual)
Title: Sensor-based indoor air temperature prediction using deep ensemble machine learning for Australian urban environment
Description: Contributed as a Research Assistant to a MAAP linkage project funded by the Australian Research Council. This project involved collaboration with Monash University and AETMOS, focusing on predicting indoor air temperature and air quality using meteorological data. The work explored deep learning architectures to evaluate health impacts of environmental conditions, and proposed predictive models for smart urban sustainability.
Fund: ARC MAAP linkage project fund
Funding Organisation: Australian Research Council (ARC)
Collaboration Organisation: Deakin University (Austrlia), Monash University (Australia), AETMOS (Australia)
Period: Mar 1, 2022 - Feb. 28, 2023
Research Assistant (Casual)
Title: Channel minimisation and epileptic seizure detection using single channels using Deep Learning from continuous iEEG
Description: This voluntary research focused on minimizing the number of EEG channels required for accurate epileptic seizure detection. Leveraging deep learning on continuous iEEG signals, the study aimed to optimize detection performance while reducing computational and clinical complexity, contributing to more accessible and efficient seizure monitoring systems.
Fund: No funding. This is a voluntary collaboration research work.
Funding Organisation: (N/A)
Collaboration Organisation: Deakin University (Austrlia), Monash University (Australia), Alfred Health (Australia)
Period: Apr 1, 2020 - Mar 31, 2022
Project Research Associate
Title: DESIGNING A 3-LAYER NETWORK SECURITY TECHNIQUE IN SERVERS FOR PREVENTION OF DDOS ATTACK.
Description: This project proposed a novel three-layered security framework to mitigate DDoS attacks targeting server infrastructures. The system design integrated preventive, detection, and response mechanisms to enhance cybersecurity resilience and ensure uninterrupted service availability. The project was funded by HSTU through the IRT Annual Research Grant.
Fund: IRT Annual Research Fund
Funding Organisation: Institute of Research and Training (IRT), Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur-5200, Bangladesh.
Collaboration Organisation: (N/A)
Period: Jul 1, 2018 - Jun 30, 2019
Project Research Associate
Title: ANALYSIS AND DESIGN OF A NON-INVASIVE WAY OF MEASURING AND MONITORING BLOOD-SODIUM CONCENTRATION LEVEL USING NEAR-INFRARED SPECTROSCOPY.
Description: This project explored the feasibility of developing a non-invasive technique to monitor blood sodium concentration using near-infrared spectroscopy. The research involved signal processing, optical modeling, and preliminary prototype design to assess potential applications in real-time clinical diagnostics. It was supported by HSTU’s IRT Annual Research Fund.
Fund: IRT Annual Research Fund
Funding Organisation: Institute of Research and Training (IRT), Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur-5200, Bangladesh.
Collaboration Organisation: (N/A)
Period: Jul 1, 2018 - Jun 30, 2019
