BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Venue Radar//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:SaTML 2027 Calendar BEGIN:VEVENT UID:satml-2027-deadline-abstract@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART:20260923T115900Z DTEND:20260923T125900Z SUMMARY:[Robustness & Safety][Privacy-preserving ML] SaTML 2027 - Mandatory abstract registration deadline DESCRIPTION:Conference title: IEEE Conference on Secure and Trustworthy Mac hine Learning\nWebsite: https://satml.org/\nSource URL: https://satml.org /call-for-papers/\nLocation: Reykjavik\, Iceland\nTopics: Robustness & Sa fety\, Privacy-preserving ML\, Fairness & Responsible AI\, Explainability & Interpretability\nSize: M\nSubmission type: Paper-based / systematizat ion of knowledge / position papers\nConfidence: confirmed\nLast checked d ate: 2026-10-07\nNotes: Fifth annual edition. Main meeting May 4-6\; work shops May 3. The mandatory registration and new-paper deadlines have pass ed. Revisions are restricted to existing submissions and do not reopen ne w-paper opportunities. Camera-ready is only announced as mid-February\, e xact date TBC\, so no exact camera-ready event is invented. Size M is an editorial estimate.\nScope: Security\, safety\, and trustworthiness of ma chine learning. Characteristic work studies attacks and defenses\, privac y\, verification\, ML-system security\, fairness\, interpretability\, and trustworthy data curation. Theoretical\, empirical\, and applied papers must engage substantively with a safety or trustworthiness question\; mer ely using an ML model is insufficient.\nAdditional topics: Machine Learni ng\, ML Systems & Infrastructure\nScope sources (2027): https://satml.org /call-for-papers/\nScope last checked: 2026-10-07 URL:https://satml.org/call-for-papers/ END:VEVENT BEGIN:VEVENT UID:satml-2027-deadline-full-paper@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART:20260930T115900Z DTEND:20260930T125900Z SUMMARY:[Robustness & Safety][Privacy-preserving ML] SaTML 2027 - Research\ , SoK\, and position paper deadline DESCRIPTION:Conference title: IEEE Conference on Secure and Trustworthy Mac hine Learning\nWebsite: https://satml.org/\nSource URL: https://satml.org /call-for-papers/\nLocation: Reykjavik\, Iceland\nTopics: Robustness & Sa fety\, Privacy-preserving ML\, Fairness & Responsible AI\, Explainability & Interpretability\nSize: M\nSubmission type: Paper-based / systematizat ion of knowledge / position papers\nConfidence: confirmed\nLast checked d ate: 2026-10-07\nNotes: Fifth annual edition. Main meeting May 4-6\; work shops May 3. The mandatory registration and new-paper deadlines have pass ed. Revisions are restricted to existing submissions and do not reopen ne w-paper opportunities. Camera-ready is only announced as mid-February\, e xact date TBC\, so no exact camera-ready event is invented. Size M is an editorial estimate.\nScope: Security\, safety\, and trustworthiness of ma chine learning. Characteristic work studies attacks and defenses\, privac y\, verification\, ML-system security\, fairness\, interpretability\, and trustworthy data curation. Theoretical\, empirical\, and applied papers must engage substantively with a safety or trustworthiness question\; mer ely using an ML model is insufficient.\nAdditional topics: Machine Learni ng\, ML Systems & Infrastructure\nScope sources (2027): https://satml.org /call-for-papers/\nScope last checked: 2026-10-07 URL:https://satml.org/call-for-papers/ END:VEVENT BEGIN:VEVENT UID:satml-2027-deadline-notification@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART:20261217T115900Z DTEND:20261217T125900Z SUMMARY:[Robustness & Safety][Privacy-preserving ML] SaTML 2027 - Decision notification DESCRIPTION:Conference title: IEEE Conference on Secure and Trustworthy Mac hine Learning\nWebsite: https://satml.org/\nSource URL: https://satml.org /call-for-papers/\nLocation: Reykjavik\, Iceland\nTopics: Robustness & Sa fety\, Privacy-preserving ML\, Fairness & Responsible AI\, Explainability & Interpretability\nSize: M\nSubmission type: Paper-based / systematizat ion of knowledge / position papers\nConfidence: confirmed\nLast checked d ate: 2026-10-07\nNotes: Fifth annual edition. Main meeting May 4-6\; work shops May 3. The mandatory registration and new-paper deadlines have pass ed. Revisions are restricted to existing submissions and do not reopen ne w-paper opportunities. Camera-ready is only announced as mid-February\, e xact date TBC\, so no exact camera-ready event is invented. Size M is an editorial estimate.\nScope: Security\, safety\, and trustworthiness of ma chine learning. Characteristic work studies attacks and defenses\, privac y\, verification\, ML-system security\, fairness\, interpretability\, and trustworthy data curation. Theoretical\, empirical\, and applied papers must engage substantively with a safety or trustworthiness question\; mer ely using an ML model is insufficient.\nAdditional topics: Machine Learni ng\, ML Systems & Infrastructure\nScope sources (2027): https://satml.org /call-for-papers/\nScope last checked: 2026-10-07 URL:https://satml.org/call-for-papers/ END:VEVENT BEGIN:VEVENT UID:satml-2027-deadline-revision@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART:20270122T115900Z DTEND:20270122T125900Z SUMMARY:[Robustness & Safety][Privacy-preserving ML] SaTML 2027 - Invited p aper revision deadline DESCRIPTION:Conference title: IEEE Conference on Secure and Trustworthy Mac hine Learning\nWebsite: https://satml.org/\nSource URL: https://satml.org /call-for-papers/\nLocation: Reykjavik\, Iceland\nTopics: Robustness & Sa fety\, Privacy-preserving ML\, Fairness & Responsible AI\, Explainability & Interpretability\nSize: M\nSubmission type: Paper-based / systematizat ion of knowledge / position papers\nConfidence: confirmed\nLast checked d ate: 2026-10-07\nNotes: Fifth annual edition. Main meeting May 4-6\; work shops May 3. The mandatory registration and new-paper deadlines have pass ed. Revisions are restricted to existing submissions and do not reopen ne w-paper opportunities. Camera-ready is only announced as mid-February\, e xact date TBC\, so no exact camera-ready event is invented. Size M is an editorial estimate.\nScope: Security\, safety\, and trustworthiness of ma chine learning. Characteristic work studies attacks and defenses\, privac y\, verification\, ML-system security\, fairness\, interpretability\, and trustworthy data curation. Theoretical\, empirical\, and applied papers must engage substantively with a safety or trustworthiness question\; mer ely using an ML model is insufficient.\nAdditional topics: Machine Learni ng\, ML Systems & Infrastructure\nScope sources (2027): https://satml.org /call-for-papers/\nScope last checked: 2026-10-07 URL:https://satml.org/call-for-papers/ END:VEVENT BEGIN:VEVENT UID:satml-2027-conference@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART;VALUE=DATE:20270504 DTEND;VALUE=DATE:20270507 SUMMARY:[Robustness & Safety][Privacy-preserving ML] SaTML 2027 - Conferenc e DESCRIPTION:Conference title: IEEE Conference on Secure and Trustworthy Mac hine Learning\nWebsite: https://satml.org/\nSource URL: https://satml.org /\nLocation: Reykjavik\, Iceland\nTopics: Robustness & Safety\, Privacy-p reserving ML\, Fairness & Responsible AI\, Explainability & Interpretabil ity\nSize: M\nSubmission type: Paper-based / systematization of knowledge / position papers\nConfidence: confirmed\nLast checked date: 2026-10-07\ nNotes: Fifth annual edition. Main meeting May 4-6\; workshops May 3. The mandatory registration and new-paper deadlines have passed. Revisions ar e restricted to existing submissions and do not reopen new-paper opportun ities. Camera-ready is only announced as mid-February\, exact date TBC\, so no exact camera-ready event is invented. Size M is an editorial estima te.\nScope: Security\, safety\, and trustworthiness of machine learning. Characteristic work studies attacks and defenses\, privacy\, verification \, ML-system security\, fairness\, interpretability\, and trustworthy dat a curation. Theoretical\, empirical\, and applied papers must engage subs tantively with a safety or trustworthiness question\; merely using an ML model is insufficient.\nAdditional topics: Machine Learning\, ML Systems & Infrastructure\nScope sources (2027): https://satml.org/call-for-papers /\nScope last checked: 2026-10-07 URL:https://satml.org/ LOCATION:Reykjavik\, Iceland END:VEVENT END:VCALENDAR