BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//TECoSA - ECPv6.18.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:TECoSA
X-ORIGINAL-URL:https://www.tecosa.center.kth.se
X-WR-CALDESC:Events for TECoSA
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20270328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20271031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20261105T150000
DTEND;TZID=Europe/Paris:20261105T160000
DTSTAMP:20261026T140835Z
CREATED:20261026T140835Z
LAST-MODIFIED:20261026T140835Z
UID:8358-1793890800-1793894400@www.tecosa.center.kth.se
SUMMARY:TECoSA Seminar - Runtime Assurance in AI-Based Autonomy: Between Learning and Monitoring 
DESCRIPTION:Presenter: Hazem Torfah \nAbstract: The deployment of autonomous systems in complex environments has increased significantly in recent years\, with many relying on machine learning (ML) components for critical decision-making tasks. However\, ML models are inherently brittle and prone to failures that can compromise system safety. This highlights the need for a systematic methodology to identify the conditions under which autonomy pipeline components may fail and how to detect such failures at runtime. \nThis talk introduces a safety assurance approach for autonomous systems based on runtime verification. Runtime verification involves extracting information from a system at runtime and evaluating it to determine whether an execution satisfies or violates a given safety property. We will present recent methods for learning and monitoring the conditions under which autonomous systems operate correctly. Specifically\, we will discuss approaches for learning runtime monitors that can detect deviations from safe and expected system behavior\, while remaining robust to uncertainties in both the environment and AI-based components. \nZoom-link to the seminar : https://kth-se.zoom.us/j/66857695267
URL:https://www.tecosa.center.kth.se/event/tecosa-seminar-runtime-assurance-in-ai-based-autonomy-between-learning-and-monitoring/
CATEGORIES:Seminar
END:VEVENT
END:VCALENDAR