Here you’ll find posts about my research, thoughts on science, and things I’ve written elsewhere.
I probably overuse the normal-inverse-gamma posterior. Every time I build a bandit system, every time I need uncertainty quantification for sequential decisions, I end up back at conjugate linear regression.
For a new project at work, we didn’t want to do passwords. The two candidates were magic links and WebAuthn, and we ended up going with magic links—but I got curious about WebAuthn anyway, so I built a demo app to understand it.
Suppose you’re choosing a continuous value x and observing a noisy reward y. The reward depends on x through some unknown function f(x), and you’re making decisions repeatedly—learning as you go. This post explores how to build scalable Bayesian models for this problem using principled approximations.
In my previous post, I covered running portable services—version-controlled config, atomic updates, zero-downtime restarts, all without a container runtime. This is only half of the container story, though. You also need to build the service images.
I run bowl.science, an online Science Bowl tournament platform. It’s a side project, but it’s real production: the DOE Office of Science uses it for their Science Bowl competitions. When a tournament is happening, the app needs to work. There’s no “we’ll fix it in the next sprint.”
My friend Alexa is a graphic designer. Last week I asked her what percentage of her time she spends on meta-design. She asked me what that meant.
Rarely do I ever get asked to make churn estimates for someone who needs to bring the full power of a proportional hazards model to bear. Besides, the person asking for churn estimates doesn’t actually want to know “what is the probability someone churns eventually?” (Spoiler: it’s 1.)
We were studying how microglia affect neuronal networks using a standard imaging experiment: 3 mice, 3 coverslips per condition, about 20 neurons measured per coverslip. Our question: Does LPS activation significantly increase PNA signal?
A while back, I wrote a short piece about planning scientific projects for New Science. The article explores systematic approaches to identifying impactful research questions and structuring PhD projects for maximum scientific contribution.