Stephan Rabanser
PhD candidate @utoronto.ca and @vectorinstitute.ai | Soon: Postdoc @princetoncitp.bsky.social | Reliable, safe, trustworthy machine learning.
- 🏅 Very excited to share that my recent Google internship project on model cascading has received the 𝗕𝗲𝘀𝘁 𝗣𝗼𝘀𝘁𝗲𝗿 𝗔𝘄𝗮𝗿𝗱 at the 𝘛𝘛𝘖𝘋𝘓𝘦𝘳-𝘍𝘔 𝘞𝘰𝘳𝘬𝘴𝘩𝘰𝘱 @ 𝘐𝘊𝘔𝘓! Thanks a lot to the organizers for setting up this amazing workshop!
- 📣 I will be at #ICML2025 in Vancouver next week to present two main conference papers (including one oral paper ✨) and two workshop papers! Say hi if you are around and want to chat about ML uncertainty & reliability! 😊 🧵 Papers in order of presentation below:
- 📢 New ICML 2025 paper! Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention 🤔 Think model uncertainty can be trusted? We show that it can be misused—and how to stop it! Meet Mirage (our attack💥) & Confidential Guardian (our defense🛡️). 🧵1/10
- 🔍 Background—Cautious Predictions: ML models are often designed abstain from predicting when uncertain to avoid costly mistakes (finance, healthcare, justice, autonomous driving). But what if that safety valve becomes a backdoor for discrimination? 🚪⚠️ 🧵2/10
- Starting off this account with a banger: In September 2025, I will be joining @princetoncitp.bsky.social at Princeton University as a Postdoc working with @randomwalker.bsky.social & @msalganik.bsky.social! I am very excited about this opportunity to continue my work on trustworthy/reliable ML! 🥳
