The program chairs for #SaTML2027 will be Fabio Pierazzi (@fbpierazzi.bsky.social) and Florian Tramèr! We're in for a great conference under their leadership.
Posts by Conference on Secure and Trustworthy Machine Learning
SaTML is looking for a host for #SaTML2027! If you're interested in bringing SaTML to a city near you, please fill out this form by April 15! 🏘️🏙️🏡🌆
docs.google.com/forms/d/e/1F...
Still no plans for March 2026? How about a pretzel and a beer in Munich 🥨🍺 Registration for SaTML is now open:
satml.org/attend/
We have a packed program with papers on secure, private, and fair machine learning. Accepted papers here:
satml.org/accepted-pap...
The accepted papers for SaTML 2026 are now online: satml.org/accepted-pap...
Congratulations to all authors 🎉 and many thanks to everyone who submitted their work!
This year, we received 233 submissions, of which 55 papers were accepted. A few revisions are still in the pipeline, so stay tuned.
Got some hot research cooking? 🔥
The @satml.org paper deadline is just 9 days away. We are looking forward to your work on security, privacy, and fairness in machine learning.
👉 satml.org/call-for-pap...
⏰ Sep 24
IEEE Conference on Secure and Trustworthy Machine Learning Technical University of Munich, Germany March 23–25, 2026
Three weeks to go until the SaTML 2026 deadline! ⏰ We look forward to your work on security, privacy, and fairness in AI.
🗓️ Deadline: Sept 24, 2025
We have also updated our Call for Papers with a statement on LLM usage, check it out:
👉 satml.org/call-for-pap...
@satml.org
📣 Researchers in AI security, privacy & fairness: It's time to share your latest work!
The SaTML 2026 submission site is live 👉 hotcrp.satml.org
🗓️ Deadline: Sept 24, 2025
@satml.org
🚨 Got a great idea for an AI + Security competition?
@satml.org is now accepting proposals for its Competition Track! Showcase your challenge and engage the community.
👉 satml.org/call-for-com...
🗓️ Deadline: Aug 6
Call for Competitions Competition proposal deadline: August 6, 2025 Decision notification: August 27, 2025
We’re happy to announce the Call for Competitions for
@satml.org
The competition track has been a highlight of SaTML, featuring exciting topics and strong participation. If you’d like to host one for SaTML 2026, visit:
👉 satml.org/call-for-com...
⏰ Deadline: Aug 6
IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), March 23-25, 2025, Munich Submission deadline: September 24, 2025
We're excited to announce the Call for Papers for SaTML 2026, the premier conference on secure and trustworthy machine learning @satml.org
We seek papers on secure, private, and fair learning algorithms and systems.
👉 satml.org/call-for-pap...
⏰ Deadline: Sept 24
🌍 Help shape the future of SaTML!
We are on the hunt for a 2026 host city - and you could lead the way. Submit a bid to become General Chair of the conference:
forms.gle/vozsaXjCoPzc...
🚨 SaTML is searching for its 2026 home!
Interested in becoming General Chair and hosting the conference in your city or institution? We’d love to hear from you. Place a bid here:
👉 forms.gle/kbxtwZddpcLD...
🎤 That’s a wrap on #SaTML25! Huge thanks to the speakers, organizers, reviewers, and everyone who joined the conversation. See you next time!
🔍 How private was that release? @a-h-koskela.bsky.social presents a method for auditing DP guarantees using density estimation. #SaTML25
🧮 Getting the math right. @matt19234.bsky.social walks through common traps in privacy accounting and how to avoid them. #SaTML25
🧠 Marginals leak. Steven Golob shows how synthetic data built on marginals can still compromise privacy. Paper: arxiv.org/abs/2410.05506 #SaTML25
📃🔐 Privacy and fairness? Khang Tran introduces FairDP, enabling fairness certification alongside differential privacy. Paper: arxiv.org/abs/2305.16474 #SaTML25
📏 Wrapping up the talks with deep dives into differential privacy—Session 14 gets technical, from fairness to auditing.
🖼️📡 Hide and seek. Luke Bauer presents a method for covert messaging with provable security via image diffusion. Paper: arxiv.org/abs/2503.10063 #SaTML25
💣 Still work to do. Yigitcan Kaya makes the case that ML-based behavioral malware detection is fragile and far from solved. Paper: arxiv.org/abs/2405.06124 #SaTML25
🕵️♂️ From detection to covert messaging—Session 13 explores the gray areas of ML security. #SaTML25
💻 What can you learn privately when compute is tight? Zachary Charles tackles user-level privacy under realistic constraints. #SaTML25
📊 Not all public datasets are equal. Xin Gu proposes a new metric—gradient subspace distance—to guide private learning choices. Paper: arxiv.org/abs/2303.01256 #SaTML25
📚🔒 Choose wisely. Kristian Schwethelm presents a method to balance data utility and privacy in active learning. Paper: arxiv.org/abs/2410.00542 #SaTML25
⚖️ Privacy isn’t always fair. Kai Yao breaks down the mechanisms that can introduce unfairness into private learning. Paper: arxiv.org/abs/2501.14414 #SaTML25
🔐 Starting the final afternoon at #SaTML25 with Session 12—private learning from all angles: fairness, dataset selection, active learning, and budget-aware privacy.
🌲💀 Even decision trees aren’t safe. Lorenzo Cazzaro shows how to poison tree-based models. Paper: arxiv.org/abs/2410.00862 #SaTML25
🚗🔦 How robust are LiDAR detectors?Alexandra Arzberger presents Hi-ALPS, benchmarking six systems used in autonomous vehicles. Paper: arxiv.org/abs/2503.17168 #SaTML25
🎯 Robustness meets domain adaptation. Natalia Ponomareva introduces DART, a principled method for adapting without labels—and withstanding attacks. #SaTML25
🛡️🌍 Session 11 at #SaTML25 is all about making models that hold up—across domains, sensors, and even sneaky tree poison.