I'm a Ph.D. Candidate in Explainable AI for Medical Imaging. My research work focuses on developing inherently interpretable deep learning models for disease diagnosis in medical imaging.
Topics of interest: Explainable AI, Vision-Language Models, Concept-based Explanations, Medical Image Analysis, Skin Image Analysis.
- NEW! ViConEx-Med: Visual Concept Explainability via Multi-Concept Token Transformer for Medical Image Analysis (Preprint, 2025) [Code][PDF]
 - NEW! SynSkin: A Synthetic Skin Lesion-Like Dataset for Benchmarking Dermoscopic Color Concepts (RECPAD, 2025) [Code][PDF]
 - NEW! Unsupervised contrastive analysis for anomaly detection in brain MRIs via conditional diffusion models (Preprint, 2025) [Code][PDF]
 - NEW! CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification (CIBM, 2025) [Code][PDF]
 - A Two-Step Concept-Based Approach for Enhanced Interpretability and Trust in Skin Lesion Diagnosis (CSBJ, 2025) [Code][PDF]
 - Towards Concept-based Interpretability of Skin Lesion Diagnosis using Vision-Language Models (IEEE ISBI, 2024) [Code][PDF]
 - Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis (IEEE CVPRW, 2023) [Code][PDF]
 - Explainable Deep Learning Methods in Medical Image Classification: A Survey (ACM CSUR, 2023) [Code][PDF]
 - Zero-Shot Face Recognition: Improving the Discriminability of Visual Face Features Using a Semantic-Guided Attention Model (ESWA, 2023) [Code][PDF]
 - ZSpeedL - Evaluating the Performance of Zero-Shot Learning Methods using Low-Power Devices (AVSS, 2021) [Code][PDF]
 


