This inventor holds 1 USPTO granted patent. Top assignees: California Institute of Technology, University of California. Active years: 2026.
Company Filing History:
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1 out of 15,977 
Years Active: 2026
Title: Innovations by Sean Chen in Neural Network Optimization
Introduction
Sean Chen is an accomplished inventor based in Los Angeles, CA. He has made significant contributions to the field of neural networks, particularly in optimizing decoding techniques for linear block codes. His innovative approach aims to improve frame error rate (FER) performance, showcasing his expertise in the intersection of artificial intelligence and telecommunications.
Latest Patents
Sean Chen holds a patent titled "Neural-network-optimized degree-specific weights for LDPC minsum decoding." This invention introduces Neural Normalized MinSum (N-NMS) decoding, which enhances the performance of linear block codes over traditional normalized MinSum (NMS) methods. The patent describes a method where dynamic multiplicative weights are assigned to each check-to-variable message during iterations. This approach efficiently provides training parameters for N-NMS, allowing it to support longer block lengths. Additionally, the invention includes embodiments for neural two-dimensional normalized MinSum (N-2D-NMS) decoders, which require fewer training parameters. The N-2D-NMS techniques utilize the same weight for edges with identical check and/or variable node degrees. Simulation results demonstrate that this LDPC decoding method performs comparably to previous techniques while significantly reducing the training required.
Career Highlights
Throughout his career, Sean Chen has worked with prestigious institutions such as the University of California and the California Institute of Technology. His experience in these organizations has allowed him to collaborate with leading experts in the field and contribute to groundbreaking research.
Collaborations
Sean has collaborated with Linfang Wang, further enhancing the impact of his work in neural network optimization.
Conclusion
Sean Chen's innovative contributions to neural network optimization and decoding techniques have the potential to significantly advance the field of telecommunications. His work exemplifies the importance of research and development in improving technology for practical applications.