{"id":84,"date":"2025-09-03T15:32:04","date_gmt":"2025-09-03T13:32:04","guid":{"rendered":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/?page_id=84"},"modified":"2025-09-29T12:07:29","modified_gmt":"2025-09-29T10:07:29","slug":"program","status":"publish","type":"page","link":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/?page_id=84","title":{"rendered":"Program"},"content":{"rendered":"\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>09:00 &#8211; 10:00<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><strong>Welcome &amp; Keynote<\/strong><\/p>\n\n\n\n<p><a href=\"https:\/\/rvmeetsmdb2025.digital-hub.sh\/wp-content\/uploads\/2025\/09\/Ingo_Pill_Keynote_MBDmRV_25.pdf\">Model-based Diagnosis meets Verification &#8211; The Principles, Potential, and Application of MBD<\/a><br><em>Ingo Pill<\/em><\/p>\n\n\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>Abstract &amp; Bio<\/summary>\n<p>Starting with its connections to verification, I will outline the basics of model-based diagnosis (MBD). We will delve into the underlying concept of reasoning from first principles, will discuss computational concepts, and we will look into how we can diagnose formal models and requirements in Amir Pnueli\u2019s temporal logic of programs (LTL) for infinite and finite computations. I will conclude with a brief characterization of MBD and a short outline of some open challenges in MBD research.<\/p>\n\n\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>Biography<\/summary>\n<p>Since 2020, <a href=\"http:\/\/www.ist.tugraz.at\/pill\/index.html\">DI Dr. techn Ingo Pill<\/a> has been an external lecturer with the Institute of Software Engineering and AI (SAI, former Institute for Software Technology) at Graz University of Technology. From 2020 to 2024 he was a staff scientist with the Silicon Austria<br>Labs (SAL) in Graz. Before joining SAL in 2020, he was a senior scientist with the Software Engineering &amp; Artificial Intelligence group at SAI where he completed his PhD in Formal Verification in 2008. His research interests lie in symbolic AI and formal methods, with a special focus on diagnosis and its integration with verification, control, and sub-symbolic AI techniques in order to facilitate resilient systems. Ingo is a recognized expert in model-based diagnosis and reasoning, is a member of AAAI, ACM and ASAI\/\u00d6GAI, reviews for top journals and conferences, and has been a regular (senior) program committee member of leading AI venues like AAAI, IJCAI or ECAI for which he received several outstanding program committee member awards for his efforts. He has been active in organizing workshops and conferences, e.g., as co-chair of the International Conference on Principles of Diagnosis and resilient systems (DX) (2014, 2017, 2023, 2024, 2025) for which he also chairs the Steering Committee since 2023, as co-chair of the Dagstuhl Seminar 24031 \u201cFusing Causality, Reasoning and Learning for Fault Management and Diagnosis) in 2024, and in several capacitites for further conferences and workshops in the area of AI. He received several awards, including the Best Paper Award at the DX conference in 2025. He co-supervised several master and PhD students and has been chair or member of MSc\/PhD examination boards (e.g, TU Graz, ANU, Ben Gurion University of the<br>Negev, or the University of Trento). At SAL, Ingo was one of three members of the SAL doctoral college core team who governed the SAL-DC and who lead as well as authored the multi-million MSCA-Cofund program CRYSTALLINE with 18 PhD students (funding of 2.4M\u20ac) that started in 2024.<\/p>\n<\/details>\n<\/details>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>10:00 &#8211; 10:30<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><strong>Coffee break<\/strong><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>10:30 &#8211; 10:55<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p>Monitoring for Risk Reduction in Autonomous Driving<br><em>Franz Wotawa<\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>10:55 &#8211; 11:20<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p>Runtime Verification of Risk<br><em>Michael Hofbaur<\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>11:20 &#8211; 11:45<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><a href=\"https:\/\/rvmeetsmdb2025.digital-hub.sh\/wp-content\/uploads\/2025\/09\/presentation_rvmeetsmbd2025_rodler_FINAL_protected.pptx\">Choosing Abstraction Levels for Model-based Software Debugging: A Theoretical and Empirical Analysis for Spreadsheet Programs (and its Relation to Runtime Veri\ufb01cation)<\/a><br><em>Patrick Rodler, Birgit Hofer, Dietmar Jannach, Iulia Nica, and Franz Wotawa<\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>11:45 &#8211; 12:10<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p>Execution Monitoring for Behavior Trees<br><em>Leo F\u00fcrba\u00df and Gerald Steinbauer-Wagner&nbsp;<\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>12:10 &#8211; 13:30<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><strong>Lunch break<\/strong><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>13:30 &#8211; 13:55<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p>Assumption-based Runtime Verification: From RV to Diagnosis<br><em>Alessandro Cimatti<\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>13:55 &#8211; 14:20<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><a href=\"https:\/\/rvmeetsmdb2025.digital-hub.sh\/wp-content\/uploads\/2025\/09\/raik-hipler_main.pdf\">Stream-based Diagnosis with LOLA<\/a><br><em>Raik Hipler<\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>14:20 &#8211; 14:45<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p>A Multi-Modal Emergency Recognition System Using Smartphone Sensors: Lightweight Deep Learning for Activity and Sound Analysis with Model-Based Diagnosis<br><em>Hyoung-Gook Kim, J\u00f6rn Fischer, and Jin-Young Kim <\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p>14:45 &#8211; 15:15<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><strong>Coffee break<\/strong><\/p>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n","protected":false},"excerpt":{"rendered":"<p>09:00 &#8211; 10:00 Welcome &amp; Keynote Model-based Diagnosis meets Verification &#8211; The Principles, Potential, and Application of MBDIngo Pill 10:00 &#8211; 10:30 Coffee break 10:30 &#8211; 10:55 Monitoring for Risk Reduction in Autonomous DrivingFranz Wotawa 10:55 &#8211; 11:20 Runtime Verification of RiskMichael Hofbaur 11:20 &#8211; 11:45 Choosing Abstraction Levels for Model-based Software Debugging: A Theoretical [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":2,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-84","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=\/wp\/v2\/pages\/84","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=84"}],"version-history":[{"count":18,"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=\/wp\/v2\/pages\/84\/revisions"}],"predecessor-version":[{"id":117,"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=\/wp\/v2\/pages\/84\/revisions\/117"}],"up":[{"embeddable":true,"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=\/wp\/v2\/pages\/2"}],"wp:attachment":[{"href":"https:\/\/rvmeetsmdb2025.digital-hub.sh\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=84"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}