• Developed the Alignment Quality Index (AQI), a contrastive, layer-attentive metric leveraging CKA-driven introspection to detect alignment-relevant representations beyond over-smoothed final embeddings. • Mitigated final-layer over-smoothing by optimizing layerwise weights to maximize inter-class separation in latent space between safe and unsafe completions - Work submitted to EMNLP’25
• Worked under the supervision of Dr. Sriparna Saha at the AI-NLP-ML Research Lab IIT Patna. • Developed a multilingual benchmark evaluating trustworthiness of language models in healthcare across 15 languages, 18 tasks, and 5 core dimensions—truthfulness, fairness, safety, robustness, and privacy. • Designed evaluation protocols covering critical medical domains including diagnostics, treatments, surgeries, and medications, spanning linguistic and demographic diversity from all major continents. • Under review at NeurIPS 2025.