We are pleased to announce that Dr. M. A. A. Abdelgawad, along with co-inventors H. Yan, C. C. R. Cheung, and Q. Zheng, has successfully received patent approval from the United States Patent Office for their groundbreaking work titled “System and method for fast processing singular value decomposition (SVD) of extremely large-scale low-rank matrices” (Patent No. US 2025/0139198 A1).
This significant achievement represents a substantial contribution to the field of computational mathematics and large-scale data processing. The patented methodology addresses critical challenges in singular value decomposition optimization, which has extensive applications across machine learning, data analytics, and scientific computing domains. The innovation in handling extremely large-scale low-rank matrices will enable enhanced computational efficiency and processing capabilities for complex data analysis tasks.
We extend our congratulations to the entire research team for this notable accomplishment and their continued excellence in advancing computational methodologies.