[ICCV'25 Highlight] Derm1M: A Million‑Scale Vision‑Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology

[MICCAI‘25 Early Accept] MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment

Vision-language foundation model for zero-shot dermatology

Superfast, privacy centric RAG VLM dermatologist.

Skin disease classification using deep learning and ANN-based medical image analysis

Derma MedGemma — Dermatology Vision-Language Fine-Tuning on Indian Diseases

AI Voice Assistant for dermatology clinic that can manage callings, bookings. Tech Stack: TypeSript, React.js , N8N Automation, Tailwind CSS, Eleven Labs

Open research workspace for federated multimodal alopecia prognosis with latent diffusion, rigorous evaluation, and governance-by-design.

Fairness Auditing in Dermoscopic AI: Quantified a 55% FNR disparity based on Anatomical Localization (Spurious Bias Audit). Focus on Disentangled Representation learning for Equitable AI.

[MICCAI '26 Early Accept] Quality-Guided Semi-Supervised Learning for Medical Image Segmentation

An ML pipeline to classify skin lesions as malignat or benign with a data dashboard and a API interface tested on the HAM10000

A project to understand and build basic knowledge on dermatologic classification/segmentation