Beau Coker
this is me
Hello there! I’m a PhD student in biostatistics at Harvard, advised by Finale Doshi-Velez and Brent Coull. I’m part of the Data to Actionable Knowledge Lab (DtAK). Previously I worked with Cynthia Rudin while completing a master’s in statistics at Duke.
I’m interested in probabilistic machine learning, particularly Bayesian neural networks (BNNs) and Gaussian processes (GPs). I think about questions like:
- How do we design priors that encode meaningful functional properties?
- What are the theoretical connections between BNNs and GPs, especially under approximate inference?
- And (maybe one day), how can we guide learning towards a causal understanding to help with generalization?
Here’s a recent talk I gave at AISTATS about mean-field variational BNNs.
Contact: beaucoker [AT] g [DOT] harvard [DOT] edu