Group Members

Graduating from EEE, BUET, Fattah's research focuses on the applications of Deep Learning in medical imaging, UAVs, and robotics, with a thesis on motion artifact correction of MRI. His emergency fire rescue assistant drone project won multiple awards in BUET Robotics Society and EEE Day competitions. Beyond academics, he is a passionate musician, serving as the lead guitarist and vocalist of a BUET-based rock band. 

Ramim graduated from the Department of EEE at BUET, majoring in Communication and Signal Processing. His research focuses on deep learning-based motion artifact removal in MRI. He has worked on classification and 3D CNN models, as well as projects in robotics and automation. Beyond academics, he is passionate about AI and data science. 

Sadad conducted his undergraduate thesis, titled “Reassessing the Potential of Quantitative Susceptibility Mapping (QSM) based Biomarkers in the Investigation of Neurodegeneration.” His maiden research publication is a paper titled “Development of a Multilingual Voice-Controlled Smart Wheelchair with Advanced Features,” which was presented at ECCE-2025 held at CUET. His research interests include but are not limited to signal processing, biomedical image processing, embedded systems, robotics, and control systems. 

Tasmin Khan is a graduate student of the Department of EEE at BUET. Majoring in Electronics, she has a passion for VLSI, while also exploring the application of Deep Learning in medical imaging. Her thesis on MRI Quantitative Susceptibility Mapping (QSM) secured the RISE Student Research Grant in 2024. This research explored a deep learning-based approach for improving the accuracy of Quantitative Susceptibility Mapping (QSM) in Magnetic Resonance Imaging (MRI), which is crucial for diagnosing neurological disorders like Alzheimer's, Parkinson's, and Multiple Sclerosis. Outside of the academic pursuits, she enjoys drawing as a form of escape. 

Prantik Paul is an Electrical & Electronic Engineering graduate from Bangladesh University of Engineering & Technology (BUET), with a major in Communication and Signal Processing. His thesis explores biomarkers for neurodegenerative diseases based on an MRI technique called Quantitative Susceptibility Mapping (QSM). His interest in medical imaging is complemented by research interests in computational imaging, machine learning, AI accelerators, and embedded systems. Outside of his academic pursuits, he is an enthusiastic gamer. 

Sk Shahriar Iqbal is a recent Electrical & Electronic Engineering graduate from Bangladesh University of Engineering & Technology, with a major in Communication and Signal Processing. He’s passionate about research in MR Imaging, Computer Vision, Deep Learning, AI and Robotics & Automation. His background includes hands-on experience with UAV automation and the development of solutions for various robotic tasks, including perception, navigation, and control. With solid experience in team management, public speaking, and presentations, He’s now actively seeking research opportunities in my fields of interest.