Healthy Algorithms

There are lovely libraries near my house.

A hands-on guide to catching simulations bugs with automated tests TL;DR What you’ll learn: Write rigorous tests for randomized algorithms without arbitrary thresholds.

The Journal of Privacy and Confidentiality has managed to get one more edition published this year: https://journalprivacyconfidentiality.org/index.php/jpc/issue/view/123 Happy new year to the editors!

I’m back on social media — https://bsky.app/profile/healthyalgo.bsky.social It is fun to get a social feed again, but I’ve got some curating to do — I’ve got a lot of interesting people to follow, but not a lot of science peers to interact with.

Coding and testing when you know what you want the computer to do Reminder of Intro and Debugging 1 & 2: AI is BS, but not useless; You can prompt it with an error message and get suggestions, you can give it an example of code that is not doing what you…

Debugging 2: When the code does not fail, but still is wrong Reminder of Intro and Debugging 1: AI is BS, but not useless; Prompt with error, get suggestions, keep asking, if necessary.

Following up on the general guidance I offered Epi 554 last week, this week I tried to get specific about how to use AI assistance in debugging.

I offered students in Introduction To Epidemic Modeling For Infectious Diseases some general guidance on using AI this week, and I thought I’d share it more broadly.

For the last year, I have been a faculty advisor for the START Center at UW, which gives students an opportunity to do consulting projects, mostly in global health, mostly for the Gates Foundation.

When I was preparing to teach my Fall course, I was concerned about AI cheaters, and whether my lazy approach to getting students to do the reading would be totally outdated.