This inventor holds 4 USPTO granted patents and 1 published patent application. Top assignee: Ansys, Inc.. Active years: 2022-2025.
Company Filing History:
Years Active: 2022-2025
Title: En-Cih Yang: Innovator in Integrated Circuit Thermal Management
Introduction
En-Cih Yang is a prominent inventor based in Taipei, Taiwan. He has made significant contributions to the field of integrated circuit (IC) thermal management, holding a total of 4 patents. His work focuses on enhancing the resolution of thermal profiles in ICs through innovative machine learning techniques.
Latest Patents
Yang's latest patents include groundbreaking systems and methods for machine learning-based fast static thermal solvers. These inventions describe machine-assisted systems that enhance the resolution of an IC thermal profile from a system analysis. The methods utilize a neural network-based predictor trained to determine temperature rises across an entire IC. The training process involves generating representations of multiple templates that identify different portions of the IC, performing thermal simulations for each template, and training a neural network to predict temperature changes. Another notable patent involves predicting on-chip transient thermal responses in multi-chip systems using a recurrent neural network (RNN)-based predictor. This method also includes generating representations of templates, performing thermal simulations, and training a neural network with collected data.
Career Highlights
En-Cih Yang is currently employed at Ansys, Inc., where he continues to develop innovative solutions for thermal management in integrated circuits. His expertise in machine learning and thermal simulations has positioned him as a leader in this specialized field.
Collaborations
Yang has collaborated with notable colleagues, including Akhilesh Kumar and Ying-Shiun Li, to advance research and development in thermal management technologies.
Conclusion
En-Cih Yang's contributions to integrated circuit thermal management through his innovative patents and collaborative efforts highlight his significant role in the field. His work continues to influence advancements in machine learning applications for thermal analysis.