Wanlu Lei

Wanlu Lei has extensive experience in the field of electrical and communication engineering, with a focus on high-speed data transmission and machine learning applications. From October 2017 to June 2022, Wanlu Lei worked at Ericsson as an Industrial PhD, developing power-efficient parallel reinforcement learning methods for mmWave beam tracking and implementing deep reinforcement learning algorithms for spectrum allocation in Integrated Access and Backhaul (IAB) networks. Prior experience includes a master's thesis project on common-mode signals for interconnect products and work as an Interconnect Design Engineer, where responsibilities included developing high-speed products and testing designs for a major project with SoftBank. An early role as a data science intern at Techrise Electronics involved work on a single-phase intelligent meter. Educational qualifications include a PhD in Information Science Engineering and a master's degree from KTH Royal Institute of Technology, complemented by a bachelor's degree from the University of Electronic Science and Technology.