Hello, I just recently finished a Msc in Statistics at The University of Toronto,
where I worked with
Before that I was Graduate student in the Atmospheric Physics group under the supervision of
I am widely interested in statistics and machine learning.
Some current things i'm thinking about include:
● principled priors for bayesian neural networks ● limits of mean field variational inference ● hypernetworks and their bayesian variants ● bayesian optimization for the large scale exploration of chemical space ● generative models of graphs for automatic chemical design ● Bayesian approaches to fair machine learning If you're interested in any of these and want to work together please send me an email at email@example.com. You can also check out my resume if you want to.