# About me

I am an assistant professor in the Statistics group at Universitat Pompeu Fabra, Department of Economics. Previously, I was a postdoctoral scholar in the Department of Statistics at Stanford University, mentored by Prof. Julia A. Palacios. I earned my Ph.D in Statistics in 2018 from the Department of Decision Sciences at the Bocconi University, under the supervision of Prof. Stephen G. Walker and Prof. Sonia Petrone.

# Research interests

I seek to provide computationally tractable methods and scalable algorithms that are tailored to big data problems. My research is motivated by concrete questions arising in applications - in particular, population genetics and applied mathematics - and I address these questions via statistical methods. My research spans theory and applications of statistical inference

**Scalable coalescent-based inference**, working on alternative to Kingman coalescent to make inference feasible for large data sets**Change-point detection**, In particular, I am studying how to quantify the uncertainty in various change-point detection settings.**Recursive algorithms in Bayesian statistics**, studying and developing recursive algorithms to approximate predictive distributions in Bayesian nonparametrics model**Phylodynamics and Applications in infectious diseases and ancient DNA**, using coalescent methods to infer evolutionary parameters such as effective population size in order to monitor the ongoing SARS-CoV-2 pandemic and to study question in anthropology**Statistical approaches to inverse problems**, by framing some questions in combinatorics and applied mathematics as a statistical problem and solving those with tools from the statistical literature