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Professor Kadota’s research encompasses the development of theoretical models to capture the fundamental limits and trade-offs of next-generation communication networks, along with the design and implementation of networks that enable emerging applications such as the Internet-of-Things and Smart Cities. His work includes rigorous theoretical frameworks, such as designing network control algorithms that provide performance guarantees employing tools from Lyapunov optimization and multi-armed bandits. Furthermore, he focuses on system implementations, including FPGA-based real-time algorithms that can adaptively configure integrated circuits for full-duplex wireless communication. Kadota also integrates machine learning applications into his research, exemplified by the development of convolutional neural network-based pipelines that leverage data from millimeter-wave radar to sense atmospheric phenomena. His contributions to the field aim to bridge the gap between theoretical advancements and practical network functionality.
Standard PhD requirements for TGS departments including Chemistry, Physics, and Sociology.