Date/Time
Date(s) - 10/23/2024
12:00 PM - 1:00 PM
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Speaker
Dr. Li-C Wang is a professor at ECE department at the University of CA, Santa Barbara.
Abstract
The emergence of Large Language Models (LLMs) has transformed how we apply Machine Learning (ML) in the field of semiconductor test. Recent advancements in LLMs showcase their impressive ability to engage in meaningful dialogue across a wide range of topics, answer complex questions, and even generate code. In this webinar, we will share our experience in harnessing the power of LLMs to develop an AI agent specifically for semiconductor test data analytics. Our approach centers on the integration of a Knowledge Graph (KG), advocating for an end-to-end methodology that positions the KG as a critical component. We introduce a novel paradigm, Decision-Support ML (DSML), and explain its implementation in common test data analytics workflows. Using wafermap analytics as a case study, we demonstrate how we built IEA-Plot, an LLM-assisted AI solution, by leveraging typical LLM functionalities. We will show the real-world application of IEA-Plot on test data collected from a recent production line.
Biography
Li-C. Wang is a professor at ECE department at the University of CA, Santa Barbara. He received PhD in 1996 from the University of Texas, Austin, and was previously with Motorola PowerPC Design Center. Starting from 2003, his research has focused on investigating how machine learning could be utilized in design and test flows, where he had published more than 100 papers and supervised 22 PhD theses on related subjects. Before that, his research spanned across multiple topics in EDA and test, including microprocessor test and verification, statistical timing analysis, defect-oriented testing, and SAT solvers. He received 10 Best Paper Awards and 2 Honorable Mentioned Paper Awards from major conferences, including recent best paper awards from ITC 2022, ITC 2020, VTS 2016, and VLSI-DAT 2019. He is the recipient of the 2010 Technical Excellence Award from Semiconductor Research Corporation (SRC) for his research contributions in data mining for test and validation. He is the recipient of the 2017 IEEE-TTTC Bob Madge Innovation Award. He is an IEEE fellow and served as the General Chair of the International Test Conference (ITC) in 2017, 2018, and 2023.