DATE Save the Date 17 to 19 April 2023

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Graduate School Intelligent Methods for Test and Reliability

Project Acronym
GS-IMTR
Project Type
Graduate School at the University of Stuttgart funded by Advantest
Project Dates
-
Project Website
https://www.gs-imtr.uni-stuttgart.de
Contact Person
Prof. Dirk Pflueger (coordinator), Prof. Hussam Amrouch

Project Partners

  • Advantest Europe, Boeblingen
  • Institute of Computer Architecture and Computer Engineering, University of Stuttgart
  • Institute of Information Security, University of Stuttgart
  • Institute for Parallel and Distributed Systems, University of Stuttgart
  • Institute of Robust Power Semiconductor Systems, University of Stuttgart
  • Institute of Signal Processing and System Theory, University of Stuttgart
  • Institute of Smart Sensors, University of Stuttgart
  • Institute of Software Technology, University of Stuttgart
  • Institute for Visualization and Interactive Systems, University of Stuttgart
  • Visualization Research Center (VISUS), University of Stuttgart

Description

Test methods are a main pillar of the semiconductor technology and are an essential prerequisite for obtaining high-quality products at reasonable cost. To give a major impetus on applied semiconductor test and reliability research, Advantest, a major automatic test equipment (ATE) vendor, and the University of Stuttgart jointly established a Graduate School on “Intelligent Methods for Semiconductor Test and Reliability” (GS-IMTR).

1. What makes the project concept unique?

For the first time, a company funds a multi-partner Graduate School within a University, thus supporting ten PhD candidates and one Assistant Professor with projects selected using a competitive peer-review-based process. This brings together focused interdisciplinary expertise in fields as diverse as machine learning; visualization; security; radio-frequency circuit design; emerging technologies and architectures.

2. What project outcomes can be of use to the DATE 2022 community?

The overarching question of GS-IMTR is how to leverage data generated across the whole semiconductor value chain: during post-silicon validation, test and in-field operation. Notable expected contributions are in deep learning and visual analytics for test data; system-level test; software test suite optimization; secure testing; millimeter-wave radio frequency design; and testing of emerging technologies.

3. What inputs (solutions) are expected from the DATE 2022 community?

GS-IMTR is interested in both: new problems to which its methodologies are applicable, and specific use cases for the solutions established. GS-IMTR includes funds to facilitate international collaboration that can be used for pursuing specific scientific ideas.

4. What new research topics and trends the project introduces?

GS-IMTR follows a radically interdisciplinary approach to semiconductor testing that goes beyond its current state of the art. For example, topics such as visualization of test data or privacy-preserving test applications have not received attention so far.