🔬 Research Work 🔬

PhD Research Focus

My PhD focuses on building intelligent agent systems powered by Large Language Models (LLMs) for personalized genomic interpretation. By fusing multi-omics data, retrieval-augmented generation, and explainable AI, I aim to make variant interpretation scalable, interpretable, and clinically actionable. This work sets a new standard for privacy-preserving, human-in-the-loop genomic reasoning.

Multi-Omics & AI Integration

I develop pipelines that connect genomics, transcriptomics, and phenotypic data, ensuring robust prediction models. By leveraging ontologies and domain-specific embeddings, my frameworks enable holistic views of complex diseases, supporting early diagnosis and precision interventions.

Trustworthy AI & Explainability

One of my key goals is to design AI models clinicians trust. Using XAI techniques, causal reasoning, and transparent agent workflows, my research ensures that every insight is traceable and understandable. This bridges the gap between black-box AI and critical clinical decision-making.

Future Vision

I am committed to democratizing access to advanced genomic tools and making personalized health insights available to all. By open-sourcing critical components and advocating for ethical, fair AI practices, my work will pave the way for a collaborative, impactful future in precision medicine.

Published Papers