Explainable, Adaptive and Ethical AI Framework for Domain-Agnostic Personalization

AI-powered skin analysis prototype with Power BI dashboard highlighting model performance, bias, and generalisation challenges in melanin-rich datasets.

Machine learning project analyzing bias and fairness in loan approval predictions using metrics like disparate impact and error disparity.

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.

Mitigating algorithmic bias in facial detection systems using Debiasing Variational Autoencoders (DB-VAE). An implementation focusing on AI Fairness and latent space re-sampling.

This repository explores Explainable and Responsible AI concepts with projects on bias detection & mitigation, model interpretability, and machine unlearning. It demonstrates techniques to make AI systems fairer, transparent, and accountable.

A generative defense mechanism using High-Res CTGANs to expose and break adversarial attacks on XAI models (LIME & SHAP).

A comprehensive fairness-aware music recommendation system that detects and mitigates bias in collaborative filtering algorithms. Features interactive Streamlit demo, bias detection metrics, and multiple fairness-aware re-ranking approaches including MMR and constrained optimization.

An intelligent auditing platform designed to detect and mitigate hidden biases in automated recruitment systems.

A flexible framework for Multi-Objective Neural Architecture Search (NAS) in PyTorch. It implements and compares Quantum-Inspired (MO-QNAS) and classic Evolutionary Algorithms (GA, NSGA-II, NSGA-III) to optimize CNNs for multiple objectives like accuracy, model size, and inference time. Includes a module for post-hoc fairness evaluation.

Fairness-aware predictive modeling using Random Forest, Equalized Odds constraints, and fairness–performance tradeoff analysis on the UCI Adult Income dataset.

A research toolkit for systematically analyzing gender bias in Large Language Model (LLM) responses to job description generation tasks.

🎵 Build a fairness-aware music recommender that balances accuracy and bias, enhancing diversity and equity in recommendations from the Last.fm dataset.