Suryanarayana Duggirala

Title: The Innovations of Suryanarayana Duggirala: A Pioneer in Machine Learning and IC Design

Introduction: Suryanarayana Duggirala, based in San Jose, CA, is a distinguished inventor with a remarkable portfolio of 12 patents to his name. His innovations primarily focus on enhancing the quality and efficiency of integrated circuit (IC) designs, showcasing his expertise in the field of machine learning and design-for-test (DFT) methodologies.

Latest Patents: Among his notable contributions, two of Suryanarayana's latest patents stand out. The first patent describes a machine-learning-based design-for-test recommendation system aimed at improving automatic test pattern generation (ATPG) quality of results (QOR). This system utilizes training data gathered from various test-case configurations across different IC designs, allowing the trained machine learning model to predict ranked test-case configurations based on extracted features. The second patent introduces a dynamically reconfigurable shared scan-in test architecture. This innovative architecture reduces test data volume and application time by enabling the reconfiguration of scan inputs during operations on a per-shift basis, thus offering enhanced flexibility in the testing process.

Career Highlights: Suryanarayana Duggirala's career has been significantly intertwined with Synopsys, Inc., where he has made substantial contributions to the field of technology. His deep understanding of IC design and testing processes has established him as a valuable resource within the organization, and his inventions continue to impact the industry positively.

Collaborations: Throughout his career, Suryanarayana has collaborated with esteemed colleagues such as Rohit Kapur and Thomas W. Williams. These partnerships have been instrumental in driving innovative projects forward and enhancing the scope of their collective work within Synopsys.

Conclusion: Suryanarayana Duggirala exemplifies the spirit of innovation in the technology sector. His commitment to improving IC design through machine learning techniques sets a benchmark for future inventors and organizations. As his work continues to evolve, it undoubtedly shapes the advancement of integrated circuit technology in meaningful ways.