Knowledge Discovery in Test Applications - Promises and Challenges
IEEE members who do not have GLOBALFOUNDRIES or IBM badges to provide access to the GLOBALFOUNDRIES site must contact Judy McCullen (hurstj@us.ibm.com) no later than 8AM on Friday 8/19 so that she can arrange for badges. You must show valid ID (driver's license) at the entrance gates to the site and again at security when you sign in at the 969 visitor lobby.
The seminar starts at noon -- you must be at the lobby by 11:40 to allow for badging and walking to the 969 presentation center where the seminar will be held. David Schuler will meet you in the visitor lobby to escort you to the event.
Abstract
Test has become a major application area for data mining in recent years. In this talk, we take the view that data mining is an iterative knowledge discovery process. In this process, there are three major components: the domain knowledge to prepare a dataset, the tool to analyze the dataset, and the evaluation to determine meaningfulness of the result. Based on this view, we discuss our experience of applying data mining in several test applications, including customer return prevention, yield optimization, and burn-in elimination. Experiment results based on automotive product lines are presented to demonstrate the promises in practice and explain the challenges of making a production tool. Current research to overcome the challenges will be discussed.
About the presenter:
Li-C. Wang is professor of ECE department and Director of Computer Engineering Program at UC-Santa Barbara. He was a senior CAD software technical staff member at PowerPC Design Center, Motorola from 1996 to 2000, where he led various projects for PowerPC microprocessor test and verification. Dr. Wang received best paper awards from DATE-1998, IEEE VTS-1999, DATE-2003, VLSI DAT 2008, 2011 and ITC 2014. He received the Technical Excellence Award from Semiconductor Research Cooperation (SRC) in 2010 for contribution on developing data mining technologies in the areas of test and validation. He is currently serving or had served as technical PC member for various workshops and conferences including ITC, VTS, ICCAD, DATE, DAC, ISQED, HLDVT, ITSW, DATA, ATS, ICCD, VLSI-DAT, etc and is currently serving as the Program Chair for ITC 2016. He is an associate editor of IEEE Trans. on CAD . From 2005, his research group has published more than 80 papers on the topics related to data mining and machine learning in test, verification and validation. In the last two years, he had given six tutorials on data mining and had been invited to lecture on data mining in DAC, ICCAD, ASP-DAC and ISPD.
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Date and Time
Location
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Registration
- Date: 22 Aug 2016
- Time: 11:40 AM to 01:00 PM
- All times are (GMT-05:00) US/Eastern
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- GLOBALFOUNDRIES
- 1000 River Street
- Essex Junction, Vermont
- United States 05452
- Building: Building 969
- Room Number: 969 Presentation Center
- Contact Event Host
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To arrange badge - Send email to hurstj@us.ibm.com by 8 AM on Friday 8/19
- Co-sponsored by GLOBALFOUNDRIES & IBM Technical Vitality Council
- Starts 16 August 2016 01:00 PM
- Ends 16 August 2016 01:03 PM
- All times are (GMT-05:00) US/Eastern
- No Admission Charge
Speakers
Professor Li-C Wang of UC-Santa Barbara
Knowledge Discovery in Test Applications - Promises and Challenges
Abstract
Test has become a major application area for data mining in recent years. In this talk, we take the view that data mining is an iterative knowledge discovery process. In this process, there are three major components: the domain knowledge to prepare a dataset, the tool to analyze the dataset, and the evaluation to determine meaningfulness of the result. Based on this view, we discuss our experience of applying data mining in several test applications, including customer return prevention, yield optimization, and burn-in elimination. Experiment results based on automotive product lines are presented to demonstrate the promises in practice and explain the challenges of making a production tool. Current research to overcome the challenges will be discussed.
Biography:
About the presenter:
Li-C. Wang is professor of ECE department and Director of Computer Engineering Program at UC-Santa Barbara. He was a senior CAD software technical staff member at PowerPC Design Center, Motorola from 1996 to 2000, where he led various projects for PowerPC microprocessor test and verification. Dr. Wang received best paper awards from DATE-1998, IEEE VTS-1999, DATE-2003, VLSI DAT 2008, 2011 and ITC 2014. He received the Technical Excellence Award from Semiconductor Research Cooperation (SRC) in 2010 for contribution on developing data mining technologies in the areas of test and validation. He is currently serving or had served as technical PC member for various workshops and conferences including ITC, VTS, ICCAD, DATE, DAC, ISQED, HLDVT, ITSW, DATA, ATS, ICCD, VLSI-DAT, etc and is currently serving as the Program Chair for ITC 2016. He is an associate editor of IEEE Trans. on CAD . From 2005, his research group has published more than 80 papers on the topics related to data mining and machine learning in test, verification and validation. In the last two years, he had given six tutorials on data mining and had been invited to lecture on data mining in DAC, ICCAD, ASP-DAC and ISPD.
Address:UC- Santa Barbara, , Santa Barbara, California, United States
Professor Li-C Wang of UC-Santa Barbara
Knowledge Discovery in Test Applications - Promises and Challenges
Biography:
Address:Santa Barbara, California, United States
Agenda
Seminar by Professor Li-C Wang
ECE Department and Director of Computer Engineering Program, UC-Santa Barbara
Co-sponsored by GLOBALFOUNDRIES and IBM Technical Vitality Council