Kulikov Nikita

Investigación

My research focuses on developing machine learning methods for phylogenomic-scale analysis, with a particular emphasis on phylogenetic tree reconstruction. Phylogenetic inference is essential for many evolutionary analyses and beyond. While current methods are very precise, they become extremely computationally demanding with large genomic data sets. To address this challenge, I work on designing novel machine learning approaches that balance accuracy and computational efficiency.