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PRODID:IEEE vTools.Events//EN
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TZID:America/Los_Angeles
BEGIN:DAYLIGHT
DTSTART:20260308T030000
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DTSTART:20261101T010000
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BEGIN:VEVENT
DTSTAMP:20260901T014219Z
UID:83C4EA85-1C5A-4CF7-B60B-562C2FC15782
DTSTART;TZID=America/Los_Angeles:20261023T090000
DTEND;TZID=America/Los_Angeles:20261023T133000
DESCRIPTION:Four guided training talks with small-group interaction:\n9:00:
  Advanced Packaging for AI – Challenges and Roadmaps in Fault Isolation 
 and Failure Analysis\n9:30: Metal TIM and Low-Temp Solder Paste for HPC &amp; 
 AI Industry Challenges\n10:30: Failure Analysis of Electronic Components f
 or AI and Data Center Infrastructure\n11:00: Scanning Acoustic Microscopy 
 (SAM) and Photo-induced Force Microscopy (PiFM) for Defect Identification 
 and Characterization in AI Hardware\n\n11:30: lunch\, social/networking\, 
 and optional lab tours\n\nCo-sponsored by: Paul Wesling\n\nSpeaker(s): Yan
  Li\, David Hu\, Audrey Chamoire \, Austin Barnes\n\nCovalent Corp.\, 925 
 Thompson Place\, Sunnyvale\, California\, United States\, 94085\, Virtual:
  https://events.vtools.ieee.org/m/575155
LOCATION:Covalent Corp.\, 925 Thompson Place\, Sunnyvale\, California\, Uni
 ted States\, 94085\, Virtual: https://events.vtools.ieee.org/m/575155
ORGANIZER:p.wesling@ieee.org
SEQUENCE:31
SUMMARY:Workshop: Decoding AI Hardware - Materials\, Metrology\, and Failur
 e Analysis in Advanced Packaging
URL;VALUE=URI:https://events.vtools.ieee.org/m/575155
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;Four guided training talks with small-grou
 p interaction:&lt;br&gt;9:00: &lt;strong&gt;Advanced Packaging for AI&lt;/strong&gt; &amp;ndash\
 ; Challenges and Roadmaps in Fault Isolation and Failure Analysis&lt;br&gt;9:30:
  &lt;strong&gt;Metal TIM and Low-Temp Solder Paste&lt;/strong&gt; for HPC &amp;amp\; AI In
 dustry Challenges&lt;br&gt;10:30:&lt;strong&gt; Failure Analysis of Electronic Compone
 nts&lt;/strong&gt; for AI and Data Center Infrastructure&lt;br&gt;11:00: &lt;strong&gt;Scann
 ing Acoustic Microscopy (SAM)&lt;/strong&gt; and Photo-induced Force Microscopy 
 (PiFM) for Defect Identification and Characterization in AI Hardware&lt;/p&gt;\n
 &lt;p&gt;11:30: lunch\, social/networking\, and optional lab tours&lt;/p&gt;\n&lt;p&gt;&amp;nbsp
 \;&lt;/p&gt;
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