ValleyML Technology Foundation Announces the Winner of the ValleyML Distinguished Technical Achievement Award
Dr. Kiran Gunnam, Distinguished Engineer - Machine Learning & Computer Vision, Western Digital, receives the ValleyML Distinguished Technical Achievement Award for long-lasting contributions to architectures and algorithms of real-time signal processing, communication, and machine learning systems that enabled ubiquitous computing.
SANTA CLARA, Calif., Dec. 15, 2021 /PRNewswire/ -- ValleyML Technology Foundation has announced that Dr. Kiran Gunnam has been named the recipient of the ValleyML Distinguished Technical Achievement Award.
The ValleyML Distinguished Technical Achievement Award honors innovators who have made lasting significant contributions to advanced computing and artificial intelligence technology for the broader benefit of humanity.
Dr. Gunnam invented the most advanced Low-Density Parity-Check (LDPC) code decoder technology at Texas A&M University (TAMU) that enabled remarkable storage densities and high-speed wireless communications. His patented work has been already incorporated in more than 3 billion data storage, WiFi, and 5G chips as of 2020 and is set to continue to be incorporated in more than 500 million chips per year. TAMU LDPC is the most advanced Low-Density Parity-Check (LDPC) code technology, originally developed and patented by Texas A&M University (TAMU) and is now currently used in high-volume storage and communication industry products. He is the primary inventor of TAMU LDPC. Industry implementations and the IEEE standards group studies have shown that TAMU LDPC has up to 75% savings in area and power over other LDPC designs and two orders of improvements over algebraic-coded implementations.
Dr. Gunnam has 86 issued US patents on algorithms, architectures, and real-time low-cost implementations for computing, storage-class memory, storage, computer vision, and AI. He is the primary or sole inventor for 90% of these innovations. His significant contributions include precise localization and navigation technology for autonomous aerial refueling and space docking applications; low-complexity simultaneous localization and mapping (SLAM) for autonomous driving and robotic systems; storage-class memory (SCM) based storage systems; in-situ processing; and efficient domain-specific accelerator architectures for machine learning and computer vision with the co-optimization of algorithms, software, and hardware with the novel ways of fully exploiting sparsity and redundancy.
Dr. Gunnam will formally receive the ValleyML Distinguished Technical Achievement Award at ValleyML AI Expo.
About ValleyML Technology Foundation
ValleyML Technology Foundation is a California non-profit corporation whose mission is to use technology as the equalizer and strengthen humanity's shared voice through excellence awards.
SOURCE ValleyML Technology Foundation
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