# Staff Profile

My research lies at the intersection between observational Cosmology, Astrophysics, and Statistics. I study the formation of structures in the Universe and the nature of Dark Energy using data from ongoing and future large-area cosmological surveys like the Hyper Suprime Cam survey and Rubin. The overarching goal of my research is to quantify the equation of state of Dark Energy and advance modern Data Science methodology in fundamental sciences.

My research lies at the intersection between observational Cosmology, Astrophysics, and Statistics. I study the formation of structures in the Universe and the nature of Dark Energy using data from ongoing and future largearea cosmological surveys like the Hyper Suprime Cam survey and Rubin. These experiments image the Universe to unprecedented accuracy and depth, advancing the field into a golden age of discovery. The massive amounts of data gathered by these programs pose fascinating challenges not only for Cosmology and Astrophysics, but also for Statistics. I'm particularly interested in developing scalable inference techniques to tackle the Big Data challenges in these fields, which often relate to spatial statistics and statistical inverse problems. The massive amounts of data gathered in modern Astronomy and Cosmology make the development of novel computational approaches to facilitate the analysis of image data from hundreds of millions of galaxies a prerequisite for discovery. As such, the Universe is the final frontier not only for physics but also for statistics and data science.

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Publication List on ORCID https://orcid.org/0000-0003-3709-1324

I teach Time Series and Design and Analysis of Experiments.