Yangkang Chen Migration biology & data science
Research
I use data science, statistical ecology, and genomics to study movement and biodiversity patterns that are difficult to observe directly.
I develop statistical and machine-learning approaches for turning uneven biodiversity observations into movement estimates and spatiotemporal ecological predictions. BirdFlow and stemflow are two examples of this broader modeling direction: using imperfect, large-scale data to infer ecological processes that are difficult to observe directly.
I study bird migration as a continental system shaped by climate, geography, species interactions, and extreme weather. My interests in this direction center on how movement, community structure, environmental context, and evolutionary history interact across broad spatial and temporal scales.
My genomics work asks how evolutionary history, demographic change, and sampling design shape biological inference. These projects span target capture sequencing, molecular dating, RNA sampling from field carcasses, and genomic evidence for lineage history and recovery in rare species.
