Sorin Tibuleac
Director, system architecture
@
Adtran
Sorin Tibuleac is a Director of System Architecture known for his contributions to optical communications, including significant publications in 2022 and participation in a telco journal roundtable at OFC 2024.
Sorin Tibuleac's Title
Sorin Tibuleac serves as the Director of System Architecture. In this role, he oversees the design and implementation of complex telecommunications systems. His expertise in system architecture ensures that the infrastructure is both robust and scalable, meeting the evolving needs of the telecommunications industry. His leadership in this area is crucial for driving innovation and maintaining the reliability of network systems.
Sorin Tibuleac's Participation in OFC 2024
Sorin Tibuleac participated in a telco journal roundtable at the Optical Fiber Communication Conference (OFC) in 2024. OFC is one of the premier global events for the latest advancements in optical communications and networking. His involvement in this roundtable highlights his active engagement with industry thought leaders and his commitment to staying at the forefront of technological developments. The insights shared during such events often influence future research directions and industry standards.
Sorin Tibuleac's Published Research in JOCN
In June 2022, Sorin Tibuleac co-authored a significant paper titled 'Benefits of Quasi-Continuous Symbol Rate Tunability in Links Constrained by ROADM Filtering,' published in the Journal of Optical Communications and Networking (JOCN). This research explores the advantages of adjustable symbol rates in optical communication links that are limited by Reconfigurable Optical Add-Drop Multiplexer (ROADM) filtering. The findings contribute to improving the efficiency and flexibility of optical networks, making them more adaptable to varying data traffic demands.
Sorin Tibuleac's Research on OSNR Using Machine Learning
Sorin Tibuleac co-authored another influential paper, 'Constellation-based identification of linear and nonlinear OSNR using machine learning: a study of link-agnostic performance,' published in Optics Express in January 2022. This study employs machine learning techniques to identify Optical Signal-to-Noise Ratio (OSNR) and distinguish between linear and nonlinear impairments in optical links. The research demonstrates a novel approach to enhancing the performance and reliability of optical communication systems by leveraging advanced data analytics.