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About

I am a Schmidt AI in Science postdoctoral fellow at the University of Chicago. My research focuses on developing model-agnostic searches for new physics (though I am partial to searches in particle collision data) using machine learning tools.

As a data physicist, I am excited to be a proponent of interdisciplinary research and create a welcoming community for other data physicists!

A(n almost) complete list of my papers can be found at my Inspire HEP. The code from all my papers can be found at my GitHub.

You can contact me at rmastand at uchicago dot edu