Computer Science Graduate
Computer Science graduate (B.Sc. CSE, CGPA 3.69/4.00) currently pursuing an M.Sc. in Computer Science & Engineering. Experienced in designing and implementing machine learning and deep learning pipelines, Android and web applications, and IoT prototypes. Author of peer-reviewed and under-review research spanning medical imaging, graph-based learning and physiological strain modelling, with work presented or accepted at venues in Australia, Italy and the United Kingdom.
Interdisciplinary research team (neuroscience, physiology, MedTech, AI)
Jan 2025 — Present· 1 yr 9 mos
Contributing to the Network Strain framework, which examines how interacting neural, cardiovascular, autonomic and affective systems shape individual vulnerability to cumulative physiological strain under environmental stress. Co-author of SIREN (Signal-Integrated Resilience Early-warning Neurodiagnostic), a proposed closed-loop smart textile system combining multimodal neurocardiovascular sensing and AI-enabled modelling with an adaptive cooling response, aiming to move beyond passive wearable monitoring toward personalised prevention of heat-related physiological breakdown. Part of the stakeholder group in exploratory climate-health research that led to the SIREN spin-out opportunity.
2026 – Present
M.Sc. · Computer Science & Engineering
2020 – 2025
B.Sc. · Computer Science & Engineering · 3.69 / 4.00
HSC · Science · 5.00 / 5.00
SSC · Science · 4.86 / 5.00
Project
Designed and implemented a hybrid architecture combining ViT-based feature extraction with GraphSAGE classification to leverage both image-level representations and graph-structured relationships. Conducted experiments on preprocessed MRI datasets, applie
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Project
Implemented a GAN pipeline to synthesize MRI slices for data augmentation: dataset curation, generator/discriminator implementation, training experiments and reproducible notebooks.
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Developed CNN classification pipelines and a Streamlit demo for inference; repository includes training notebooks and deployment scripts.
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Implemented CNNs, GNNs, GANs and LSTMs for classification and generative tasks.
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Data cleaning, visualization, feature engineering and preprocessing pipelines.
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Built an Android app for medication management with reminders, history tracking and prescription images, focused on usability and data organization.
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2023
University of Dhaka • EDGE Project, Bangladesh Computer Council
Expired 2024