I graduated in Computer Science and Engineering from North South University, Bangladesh, and currently work as an Advanced Artificial Intelligence Trainer at Invisible Technologies Inc. In my role, I work on teaching Large Language Models (LLM) to focus on the minute details and nuances present in video and audio. This not only advances the proficiency of foundation models but also plays a crucial role in shaping the trajectory of visual media for the future.
My research interest lies at the intersection of AI and healthcare, where I aim to explore innovative solutions to improve patient outcomes and advance medical technologies. I previously worked under Dr. Shahnewaz Siddique with a goal to develop and refine deep learning systems for medical imaging applications. Our research also focused on ensuring secure transfer of clinical data.
I am currently working on 2D image-based drug discovery methods for Dengue treatment. The project aims to accelerate the drug discovery process by utilizing visual representations of molecular structures to predict their effectiveness. This research is supervised by Dr. Tanzilur Rahman, and it holds promise for contributing to the global effort to combat Dengue.
I am actively exploring PhD opportunities for Fall 2025 admission. If you know of any relevant openings, I would be grateful for your insights. Thank you!
Experience
Invisible Technologies Inc., USA
Advanced Artificial Intelligence Trainer —Feb 2025 - Present
Intermediate Artificial Intelligence Trainer —Apr 2024 - Jan 2025
North South University, Bangladesh
Research Assistant —Dec 2023 - Sept 2024
Education
North South University, Bangladesh
Department of Electrical and Computer Engineering
BS, Computer Science and Engineering
2019 - 2023
Publications
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M. Y. Hossain, M. M. H. Rakib, S. Rajit, I. R. Nijhum, R. M. Rahman, Adaptive and automatic aerial image restoration pipeline leveraging pre-trained image restorer with lightweight Fully Convolutional Network, Expert Systems with Applications, 2025 [Paper]
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S. Rajit, Z. F. Ananna, M. M. Ehsan, N. N. Punom and S. Siddique, Multi-Class Brain Tumor Classification of MRI Image Using Federated Learning with Blockchain, IEEE Region 10 Symposium (TENSYMP), 2024 [Paper]
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S. Rajit, M. A. A. Sayed, Federated Learning Based Histopathological Image Classification for Oral Squamous Cell Carcinoma, 8th IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2024 [Presented; Proceedings Pending]