My academic philosophy is anchored in the belief that the next frontier of Artificial Intelligence lies not just in scaling parameters, but in scaling the accessibility and utility for the under-served. My research lab at IIT Kharagpur focuses on the area of Computer Vision and Intelligence for Translational Applications with a focus on AI in Healthcare. We aim to build AI systems that are theoretically rigorous yet robust enough to function in the resource-constrained reality of India’s healthcare infrastructure. We aim to produce deployable solutions that are trusted, affordable, and accessible. Some of the initial research directions that I am working on as following:
Label-Efficient Learning: Semi- and self-supervised techniques that pull relevant features out of noisy, sparsely labelled data. Efforts include leveraging novel techniques, investigating generative AI, and also frontier world-model approaches.
Automated Disease Detection: Investigating novel techniques for automated disease detection in medical imaging. Emphasis is placed on developing robust and accurate models for Cancer/ other relevant disease diagnosis for indian population.
Lightweight architectures for offline and edge deployment — low latency, low energy, privacy-preserving — so real-time diagnostics can run on point-of-care devices in rural clinics.
Explainable AI: I am exploring how to design domain-specific saliency methods and standardized metrics to understand how well the explanations align with domain-knowledge relevance and real decisions.
Trustworthy AI: Anchoring generative AI to reality, validating diagnostic systems so they stay safe, calibrated, and ethically sound.
- Co-Principal Investigator
Ph. D. Students
Aman Kumar
Area of Research: Computer Vision, AI in Healthcare, Self-Supervised Learning
