From aspiring AI researcher to IEEE acceptance with AUC 0.983
Aarnav developed a machine learning approach for discovering biomarkers in lung cancer, analyzing genomic data to identify signatures associated with the disease. His model achieved an AUC of 0.983, near-perfect discrimination, pointing toward earlier detection when treatment is most effective. The paper was accepted at IEEE ICITSIF 2026.
AI & Biomedical
Accepted at IEEE ICITSIF 2026
IEEE ICITSIF 2026, 2026
Aarnav Bhat, YRI Fellow
A high school student passionate about AI and medicine who wanted to apply machine learning to cancer detection but did not know where to start.
IEEE conference accepted with a lung cancer biomarker model achieving an AUC of 0.983.
“The YRI Fellowship gave me PhD mentorship, publication opportunities, ISEF coaching, and lasting support beyond the program.”
Accepted at the IEEE International Conference on IT, Security, and Innovation Future 2026
Achieved an AUC of 0.983 for lung cancer biomarker identification
Applied machine learning to genomic data for biomarker discovery
Sai Pasuparthi, Accepted at IEEE RCSM 2025