Looking for a friendly, accessible way to learn about differential privacy? 🧐 Prefer simple explanations to ugly equations? 😇. Introducing my ✨ newly revamped ✨ blog post series about differential privacy, now with an intro page & table of contents 🌈.

Hahahaha I'm hearing that posts that mention other social networks by name are de-prioritized in "for you" timelines. What a loser move 🤣. Anyway I'm over there ⤵️

I now have a presence on Bluesky: 🦋. If your main presence is on Bluesky, it'd be fantastic if you could follow so your posts are also mirrored on Mastodon, and I can follow you from there 💖.

Super excited about this ✨ new blog post ✨, where I try to offer a super simple & intuitive explanation of the exponential mechanism, a fundamental building block in differential privacy 🧱. Feedback welcome! 💝.

Updated my list of real-world deployments of differential privacy! 🚀. Changelog:.- Added the @Wikimedia pageview release 🌐.- Added two releases by @uscensusbureau 🇺🇸.- Added details on a COVID-19 release from Google 💉.- Various maintenance fixes 🛠️.

Thanks a ton to @thegautamkamath, @ccanonne_, and @shortstein for their feedback and their help publishing this!.

New, by me: what do we know about differential privacy composition theorems? What's missing, and would be useful to folks who are building practical DP software? 🔧. This blog post surveys existing results and raises a bunch of overlooked open problems. Feedback welcome! 💖.

New blog post co-written by yours truly! In which we look at data clean rooms, what they do, what they often don't do, and why that can be a Problem™ 😬. Feedback super welcome as always! 🌈.

RT @TWlTTERDOTEDU: first arxiv preprint ever🫣 “Publishing Wikipedia usage data with strong privacy guarantees,” which i’ll be presenting at….

RT @usenix: Hear it at 2023 USENIX Conference on Privacy Engineering Practice and Respect: *Privacy-Preserving Analytics on the Ground* pre….

RT @PET_Symposium: The 2023 Caspar Bowden PET Award winner is: "The 2020 Census Disclosure Avoidance System TopDown Algorithm" #pets23.

@PET_Symposium @TumultLabs More info in the paper → 🎓. And check out the full @PET_Symposium program; there it a ton of fantastic work in there: ✨.

If you're at @PET_Symposium next week, don't miss Marika Swanberg's talk about her research at @TumultLabs last summer: a novel DP mechanism for partition selection which, in contrast to prior work, scales horizontally 📈. In collaboration with Sam Haney & yours truly 😊.

RT @KatharinaKoern1: "When we want to protect individuals whose data is distributed across multiple rows, protecting individual rows is not….

Many thanks to @thegautamkamath, @thejonullman and @shortstein for the helpful comments and the help with editing & publication ❤️.

And now for something different: during a customer engagement, we stumbled upon a natural, but surprisingly tricky open problem in differential privacy. We couldn't figure it out, so we posted a simplified version of it as an open problem on 👀.

Woo-hoo, this is a huge step for Tumult Analytics! 🤩. Privacy IDs are a super important feature, and making it work with all our other advanced features was no small feat 😊. Check out the blog post we wrote to explain what problem it solves, and how it works in practice ✨.

I'll give a talk there! About floating-point vulnerabilities in differential privacy software. Mark the ticket sales on your calendar, from what I hear, tickets run out fast!.

RT @TWlTTERDOTEDU: excuse me while I earnest-post about my work for a sec!! along with @TumultLabs I helped @Wikimedia release ~250 million….

It was such a privilege to work with @Wikimedia folks on this data release 💙. They care a *ton* about the privacy of Wikipedia users, and also wanted to uphold the nonprofit's commitment to transparency and open data 🔓. A perfect job for differential privacy! ✨.

RT @Wikimedia: Did you know that we release data about pageviews of every Wikimedia project hourly?. But we were asked to go further. In p….