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PRODID:IEEE vTools.Events//EN
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TZID:Europe/Stockholm
BEGIN:DAYLIGHT
DTSTART:20230326T030000
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TZOFFSETTO:+0200
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DTSTART:20231029T020000
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BEGIN:VEVENT
DTSTAMP:20231012T081743Z
UID:E186B030-58D6-4105-A657-AEBFD6DB3D05
DTSTART;TZID=Europe/Stockholm:20231005T120000
DTEND;TZID=Europe/Stockholm:20231005T130200
DESCRIPTION:- 12:00-12:10 Welcome\, Introduction & Photo session\n- 12:10-1
 2:35 Talk 1 Mr. Jiawei Xiong (Guest PhD student\; LTU\, Sweden\; Best Pape
 r Award Winner of 2022 IEEE Global Reliability & PHM conference): Generati
 ng Controlled Physics-Informed Time-to-failure Trajectories for Prognostic
 s in Unseen Operational Conditions\n- 12:35-13:00 Talk 2 Dr. Haidong Shao 
 (Asso. Prof.\; Hunan University\, China\; 2020-2022 World's Top 2% Scienti
 sts): Towards data-poor and knowledge-rich machinery fault diagnosis\n- Mo
 re questions after 13:00\n\nVirtual: https://events.vtools.ieee.org/m/3769
 14
LOCATION:Virtual: https://events.vtools.ieee.org/m/376914
ORGANIZER:janet.lin@ltu.se
SEQUENCE:11
SUMMARY:Webinar 2023_03
URL;VALUE=URI:https://events.vtools.ieee.org/m/376914
X-ALT-DESC:Description: <br /><ul>\n<li>12:00-12:10 Welcome\, Introduction 
 &amp\; Photo session</li>\n<li>12:10-12:35 Talk 1 <strong>Mr. Jiawei Xiong
  (Guest PhD student</strong><strong>\; LTU\, Sweden\; </strong><strong>Bes
 t Paper Award Winner of </strong><strong>2022 IEEE Global </strong><strong
 >Reliability</strong><strong> &amp\; PHM </strong><strong>conference</stro
 ng><strong>): </strong>Generating Controlled Physics-Informed Time-to-fail
 ure Trajectories for Prognostics in Unseen Operational Conditions</li>\n<l
 i>12:35-13:00 Talk 2 <strong>Dr.</strong><strong> </strong><strong>Haidong
 </strong><strong> Shao (</strong><strong>Asso</strong><strong>. Prof.\; Hu
 nan University\, China\; 2020-2022 World's Top 2% Scientists)</strong>: To
 wards data-poor and knowledge-rich machinery fault diagnosis</li>\n<li>Mor
 e questions after 13:00</li>\n</ul>
END:VEVENT
END:VCALENDAR