Dan Schrider

In this discussion, Dan Schrider, an assistant professor at UNC Chapel Hill, reveals how machine learning is revolutionizing population genetics. He highlights the effectiveness of convolutional neural networks in outperforming traditional statistical methods. Dan shares insights on the integration of bioinformatics and discusses the importance of reference genomes in understanding genetic variation. Furthermore, he explores the challenges of estimating human population dynamics and the need for innovative approaches to bridge machine learning with genetic research.