Xin Huang is a postdoctoral researcher based in Vienna with 11 years of experience at the intersection of population genetics and computational biology. He develops and applies statistical and computational methods to infer introgression and the distribution of fitness effects from population genomic data, bridging theory and large-scale empirical analyses. His background includes industry-facing genomics pipeline development for GWAS and a PhD in Computational Biology, giving him fluency in both production workflows and academic method development. Known for translating complex evolutionary questions into tractable inference problems, he often combines rigorous modeling with practical pipeline implementation.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computional Biology, Doctor of Philosophy - PhD, Computional Biology at University of Chinese Academy of Sciences
Bachelor of Science - BSc, Biochemistry and Molecular Biology, Bachelor of Science - BSc, Biochemistry and Molecular Biology at South China Agricultural University
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