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Julia Palacios

Associate Professor of Statistics
Associate Professor of Biomedical Data Science
Associate Professor, by courtesy, of Biology
Joint Appointment or Affiliation:
Data Science
Institute of Computational and Mathematical Engineering
Julia Palacios

In her research, Professor Palacios seeks to provide statistically rigorous answers to concrete, data-driven questions in population genetics, epidemiology, and comparative genomics, often involving probabilistic modeling of evolutionary forces and the development of computationally tractable methods that are applicable to big data problems. Past and current research relies heavily on the theory of stochastic processes and recent developments in machine learning and statistical theory for big data; future research plans are aimed at incorporating the effects of selection and population structure in Bayesian inference of evolutionary parameters such as effective population size and recombination rates, and development of more realistic and computationally efficient methods for phylodynamic methods of infectious diseases.

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