Arko Barman

Application of Machine Learning Tools for Waterbird Colony Monitoring Provides Gains in Precision and Temporal Efficiency

The paper compares four waterbird monitoring methods using drone imagery, finding that fully automated detection reduces annotation time by 98% while maintaining 87% accuracy.

Integrating Explainable Machine Learning and Transcriptomics Data Reveals Cell-Type Specific Immune Signatures Underlying Macular Degeneration

The paper uses explainable machine learning on transcriptomics data to identify immune-related genes associated with AMD, highlighting glial cell differences and a novel regulatory variant.