Naveen Sivadasan

This paper develops an AI-guided framework for personalized cancer immunotherapy dosing, achieving high remission rates with lower median doses compared to fixed regimens.

This paper develops a deep learning model for mitotic figure detection that generalizes across diverse histological regions and tumor types, achieving an F1-score of 0.7769.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

MAGE accurately identifies microbial strains and quantifies their abundances using read mapping information without relying on strain-specific markers.

This paper introduces V-ALIGN, a new sequence alignment algorithm for directed graphs that avoids DAGification steps, improving efficiency for aligning sequences on genomic variation graphs.

GPhase is a fast and accurate haplotype inference tool that outperforms existing methods on real and simulated datasets.