Projects
Research projects in medical image analysis, AI governance, information retrieval, natural language processing and generative deep learning, with an emphasis on reproducibility and rigorous evaluation.
Generalizable Skin-Lesion Classification with Deep Learning
A reproducible study of seven deep learning architectures and a probability-level ensemble for dermoscopic skin-lesion classification, with internal evaluation on HAM10000 and external evaluation on ISIC 2019.
Bangladesh AI Policy & Innovation Lab (BAPIL)
An independent research initiative designing a trustworthy AI policy-intelligence capability for Bangladesh, from the White Paper to a Technical Blueprint with a tested reference implementation.
Patent Retrieval & Re-ranking (Dense + Cross-Encoders)
Research-oriented patent retrieval pipeline combining dense retrieval with transformer cross-encoder re-ranking, evaluated using standard IR metrics.
CycleGAN: Unpaired Horse-to-Zebra Image Translation
PyTorch implementation of CycleGAN for unpaired image-to-image translation, with qualitative results and quantitative evaluation using SSIM and PSNR.
Emotion Recognition from Text (ML + Transformers)
Comprehensive emotion recognition pipeline combining classical machine learning baselines with transformer-based models, evaluated on a standard emotion dataset.
Simplified DRAW Model for Generative Image Modeling
Implementation of a simplified DRAW-style recurrent variational autoencoder for iterative image reconstruction and generation on Fashion-MNIST.