I am an academically trained philosopher of science and data scientist. I do work in machine learning interpretability research, statistical modeling, and data science.
Some of my highlight projects include:
- Using statistical methods to compare the concepts used by deep learning algorithms with each other and limitations of those methods.
- Fitting data sets to probability distributions and then running statistical tests to evaluate hypotheses.
- Performing supervised learning using linear classifiers and artificial neural networks to make predictions about hospital readmissions.
I also have a published paper on the No Free Lunch Theorems and ongoing work on the history and philosophy of probability theory with the work of Frank Ramsey.