Company Filing History:
Years Active: 2025
Title: The Innovative Mind of Serveh Shalmashi
Introduction
Serveh Shalmashi is a notable inventor based in Enebyberg, Sweden. He has made significant contributions to the field of telecommunications, particularly in the area of radio access networks. His innovative approach combines machine learning with network management, showcasing his expertise and forward-thinking mindset.
Latest Patents
Serveh Shalmashi holds a patent for a method titled "Radio access network slice feasibility check based on machine learning." This patent describes a method for conducting a feasibility check of a new RAN slice performed by a network node. The process involves computing a first estimate of occupied resources for each resource within the network node and its cell, utilizing historical data on resource utilization. Additionally, a trained supervised machine learning model is applied to provide a second estimate of resource demand for each resource for the new RAN slice. The method includes comparing the sum of the first and second estimates to a defined threshold value, allowing for the admission of the new RAN slice when the sum does not exceed this threshold per resource. This innovative approach enhances the efficiency and effectiveness of network management.
Career Highlights
Serveh Shalmashi is currently employed at Telefonaktiebolaget LM Ericsson (publ), a leading company in telecommunications. His work at Ericsson has allowed him to apply his inventive ideas in a practical setting, contributing to advancements in network technology.
Collaborations
One of his notable collaborators is Paul Stjernholm, with whom he has worked on various projects within the telecommunications sector. Their partnership exemplifies the collaborative spirit that drives innovation in the industry.
Conclusion
Serveh Shalmashi's contributions to the field of telecommunications through his innovative patent demonstrate his commitment to advancing technology. His work not only reflects his expertise but also highlights the importance of integrating machine learning into network management.