This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignees: King Abdullah University of Science and Technology, Unist-Academy Industry Research Corporation, University of California. Active years: 2023.
Company Filing History:
1 out of 730 
1 out of 30 
1 out of 15,988 
Years Active: 2023
Title: Jong Eun Lee: Innovator in ReRAM-Based Deep Learning Accelerators
Introduction
Jong Eun Lee is a prominent inventor based in Ulsan, South Korea. He has made significant contributions to the field of deep learning technology, particularly through his innovative patent related to resistive random access memory (ReRAM).
Latest Patents
Jong Eun Lee holds a patent titled "Stuck-at fault mitigation method for ReRAM-based deep learning accelerators." This patent describes a method for confirming a distorted output value (Y0) caused by a stuck-at fault (SAF) using a correction data set in a pre-trained deep learning network. The method involves updating the average (μ) and standard deviation (σ) of a batch normalization (BN) layer using the distorted output value (Y0). Furthermore, it details the process of folding the BN layer into a convolution layer or a fully-connected layer and deriving a normal output value (Y1) using the updated deep learning network.
Career Highlights
Throughout his career, Jong Eun Lee has worked with notable organizations, including the Unist-Academy Industry Research Corporation and the University of California. His work has focused on enhancing the performance and reliability of deep learning accelerators.
Collaborations
Jong Eun Lee has collaborated with talented individuals such as Gi Ju Jung and Su Gil Lee. Their combined expertise has contributed to advancements in the field of deep learning technologies.
Conclusion
Jong Eun Lee's innovative work in the realm of ReRAM-based deep learning accelerators showcases his commitment to advancing technology. His contributions are paving the way for more reliable and efficient deep learning systems.