Professor Geoffrey Ye Li stands as a preeminent figure in wireless communications engineering with transformative contributions spanning both academia and industry. He currently holds the position of Chair Professor in the Department of Electrical and Electronics Engineering at Imperial College London, where he directs the Intelligent Transmission and Processing (ITP) Lab. Prior to his appointment at Imperial in 2020, he served for two decades as a Full Professor at the Georgia Institute of Technology, establishing himself as a cornerstone of electrical engineering education and research. His professional foundation was laid during five years as a Principal Technical Staff Member with AT&T Labs-Research, the renowned successor to Bell Labs, where he began pioneering innovations that would shape modern wireless technologies.
Professor Li made history in 2016 by becoming the first researcher to introduce deep learning methodologies to communications systems, catalyzing an entirely new research direction that has since gained widespread adoption across the field. His fundamental contributions to orthogonal frequency division multiplexing (OFDM) for wireless communications have been instrumental in advancing global communication standards, earning him the prestigious 2024 IEEE Eric E. Sumner Technical-Field Award. His exceptional impact is further evidenced by multiple IEEE honors including the 2019 IEEE ComSoc Edwin Howard Armstrong Achievement Award, the 2017 IEEE Communications Society Award for Advances in Communication, and the IEEE Donald G. Fink Overview Paper Award. These seminal contributions have fundamentally reshaped how wireless systems are conceptualized, designed, and optimized in the modern era.
As a dual Fellow of the Royal Academy of Engineering and IEEE, Professor Li continues to lead the evolution of intelligent wireless communications through both theoretical innovation and practical implementation. His current research focuses on harnessing large language models to revolutionize wireless systems, exploring three key directions: adapting pretrained LLMs for core communication tasks, developing wireless-specific foundation models, and enabling autonomous reasoning capabilities for network optimization. Through his leadership at Imperial College London and extensive international collaborations, he mentors emerging researchers while driving the integration of artificial intelligence with physical communication layers. His ongoing work promises to bridge critical gaps between AI capabilities and wireless infrastructure, potentially transforming how future networks dynamically adapt to meet evolving communication demands.
