This inventor holds 2 USPTO granted patents. Top assignee: Qualcomm Incorporated. Active years: 2024-2026.
Company Filing History:
Years Active: 2024-2026
Title: Innovations by Aziz Gholmich in Wireless Communications
Introduction
Aziz Gholmich is an accomplished inventor based in Del Mar, CA. He has made significant contributions to the field of wireless communications, particularly in enhancing machine learning model training and inference. His innovative work has the potential to improve the efficiency and effectiveness of wireless networks.
Latest Patents
Gholmich holds a patent titled "Network measurements for enhanced machine learning model training and inference." This patent describes methods, systems, and devices for wireless communications. In this invention, user equipment (UE) can communicate with a network entity within a wireless communications network. The UE may transmit a request for information to the network entity and, in response, receive the requested information. This process allows the UE to request data from various data repositories associated with the network entity. The information request may relate to measurements associated with network operations. Additionally, the UE can utilize a machine learning model to perform training or inference based on the information received.
Career Highlights
Aziz Gholmich is currently employed at Qualcomm Incorporated, a leading company in the telecommunications industry. His work at Qualcomm focuses on advancing technologies that enhance wireless communication systems. Gholmich's expertise in machine learning and network measurements positions him as a valuable asset in the field.
Collaborations
Gholmich has collaborated with notable colleagues, including Shankar Krishnan and Xipeng Zhu. These collaborations have contributed to the development of innovative solutions in wireless communications.
Conclusion
Aziz Gholmich's contributions to wireless communications through his patent and work at Qualcomm demonstrate his commitment to innovation in the field. His efforts in enhancing machine learning applications in network operations are paving the way for more efficient wireless communication systems.