Ongoing Project

Funded by: Research and Publication Cell, University of Chittagong, Bangladesh

Period:  27-10-2025~26-07-2026

Role: leader

Project Summary: 

EEG signals are collected over multiple trials to construct a subject-specific template. During authentication, incoming EEG signals are compared against stored templates using similarity measures to verify identity.

Funded by: Ministry of Science & Technology (MOST), Bangladesh 

Period:  01-07-2025~30-06-2026 

Role: leader

Project Summary: 

Despite advances in educational technology, there remains a gap in understanding how different video presentation formats influence cognitive load. This study addresses that gap by investigating the cognitive load induced by watching a standard two-dimensional (2D) video on a laptop versus an immersive 360-degree VR video, using electroencephalography (EEG) to measure brain activity.


Completed project 


·   Cognitive load and mental fatigue computation.

·   Different statistical and ML techniques can be investigated for the best outcome.



·   Envisioned speech recognition of speech impaired people by using EEG signals captured by EEG sensors.

·   Different ML techniques can be investigated for the best outcome.


Fulfilling the capacity and energy demands simultaneously is a challenging problem to be solved for IoT networks towards 5G and beyond (5G-B). Among the various challenging requirements of 5G-B, spectral efficiency and energy efficiency are the two key requirements. Therefore, it is time demand to design new protocols which are both energy and spectral efficient. By considering this issue, a novel protocol is proposed for wireless powered IoT networks by exploiting NOMA and interference-aided simultaneous wireless information and power transfer (SWIPT) which is expected to be both spectral and energy efficient.