Projects
A curated portfolio of research projects in medical imaging, information retrieval, and generative deep learning, emphasizing reproducibility, generalization, and real-world evaluation.
work
Skin Lesion Classification with Deep Learning Ensembles
A generalizable ensemble deep learning framework for automated skin lesion classification, integrating CNNs and ViTs with internal + external validation.
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: Horse ↔ Zebra (Unpaired 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.
Skin Cancer Classification (CNN Baselines)
CNN-based framework for skin lesion and melanoma classification using dermoscopic image datasets, serving as a strong baseline for medical imaging research.