Julia A. Palacios

Julia A. Palacios is an Associate Professor of Statistics and Biomedical Data Science at Stanford University, with a courtesy appointment in Biology. She leads the Palacios Lab, focusing on developing statistical methods for evolutionary genomics, infectious diseases, and stochastic processes impacting public health. Her work integrates Bayesian nonparametric techniques, probabilistic AI, and computational statistics to address challenges in genetics, health, and cancer research.

Her educational background includes a PhD in Statistics and postdoctoral research in computational biology. Current lab members include postdocs Bingjing Tang and Isaac Goldstein, PhD students Yi-Ting Tsai, Ivan Specht, Julie Zhang, and Leda Liang, and undergraduate researcher Shinnosuke Yagi. Former postdocs like Airam Blancas and Jaehee Kim have moved to faculty positions at ITAM and Cornell, respectively.

Research funding includes NIH, NSF, Sloan Foundation grants, and the Terman Fellowship. Key contributions span phylodynamic modeling, coalescent theory, and real-time pathogen surveillance. Her lab's software tools include phylodyn (R package for phylodynamic inference) and adaPop (Bayesian population dynamics inference).

Awards include the Sloan Research Fellowship and Gabilan Fellowship. Teaching roles include courses like Stats 376 and Stats 305A. Her lab actively recruits students and postdocs for research in evolutionary stochastic processes and biomedical data science.

Labs/Teams: Palacios Lab at Stanford's Department of Statistics, collaborating with institutions globally on pandemic tracking and genomic studies. Current projects focus on multifurcating trees in infectious diseases, Bayesian nonparametric coalescent models, and computational tools for public health.