Undersampled - Felix Xiao

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Welcome to my blog. My name is Felix, and this is where I typically write about my projects and research in statistical modeling and machine learning.

I graduated from Princeton University in 2016 with a bachelor’s in Operations Research and Financial Engineering, where I wrote a thesis on approximate graph partitioning algorithms for the brain parcellation problem. Nowadays I’m a Data Scientist at Goldman Sachs in NYC and I occasionally do research on weekends.

I’m broadly interested in many parts of stats/ML but my background lies mostly on the frequentist side. As such most of the papers I read are on frequentist inference algorithms for less-tractable probability models with no closed-form maximum likelihood estimators, things like stochastic processes and ranking models.

I also enjoy doing other things like playing violin, cooking, hiking, and singing bass.

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