Alexandre Gouy, PhD
Evolutionary Geneticist • Computational Biologist
I study how populations adapt to their environment: the genetic architectures that enable it, the selective pressures that shape it, and the computational methods needed to detect it. From archaic introgression in humans to rapid radiation in rodents, my work sits at the intersection of evolutionary theory, population genomics, and machine learning.
Research Themes
Adaptation & Natural Selection
Polygenic selection, adaptive introgression, and the interplay between drift and selection — from archaic humans to conservation genomics of tigers.
Population Genomics & Genetic Architecture
Demographic inference, epistasis, and the polygenic basis of complex traits. Statistical methods and software (fastsimcoal2, STRAF) used worldwide. Why most heritability remains missing.
Computational Methods
Machine learning for genomics, simulation-based inference, and AI-assisted research workflows applied to evolutionary and biomedical questions.
Epistemology & Honest Science
Replication crisis, incentive structures in academia, and the role of methodology in producing reliable knowledge. How computational tools can enforce transparency and reproducibility.