Shen demonstrated a way to compress machine learning models held and exchanged through a wireless communications network.
Communication and networking by machine learning, for machine learning
LICAN focuses on advancing future communication and networking systems that are designed by, and support for, edge intelligence and machine learning. We believe that beyond 5G has created new challenges for communication theorists and practitioners to rethink the system designs, and we envision new tools from machine learning that can benefit this task. On the other hand, edge learning and, more broadly, machine intelligence represents a new “Quality of Service” for communication and networking, which poses new requirements and design challenges.
Cong Shen clears the path toward more intelligent wireless communications with partners at Penn State and the University of Miami.
Cong Shen joins a DoD-funded research effort to develop a 5G-enabled smart warehouse. In collaboration with the Virginia Tech Applied...
Cong Shen Earns Grant to Autonomously Configure 5G and Beyond Wireless Networks Using Machine Learning
Machine-learning solution combines pure data-driven reinforcement learning algorithms with domain knowledge.
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Laboratory for Intelligent Communications and Networking (LICAN)
Department of Electrical and Computer Engineering
University of Virginia
Email: email@example.comContact Information
Fully-funded Ph.D. student positions are available in our lab. Candidates with strong analytical or engineering backgrounds are welcome to apply. In particular, we are looking for students who are interested in machine learning and/or wireless networks. Please contact Prof. Shen with your CV and transcripts if you are interested.More Information