Taejoon Kim

Taejoon Kim is an Associate Professor at the School of Electrical, Computer and Energy Engineering, Arizona State University, with research focusing on Wireless Communications, Statistical Signal Processing, and Networked Systems. His work bridges Information Theory, Machine Learning, and Optimization for applications in 5G/6G Security, mmWave/THz Communication, and Distributed Fusion.

• Education: PhD in Electrical and Computer Engineering from Purdue University, MS from KAIST (South Korea), BS from Sogang University (South Korea).

Research interests span Machine Learning for Physical Layer design, Feature Learning, Distributed Interference Management, and Algorithms on Manifolds. Recent projects examine learnability in AI/ML-based physical layer techniques, fast beam alignment in mmWave systems, and optimization of network resource allocation.

His article portfolio reveals trends in 5G/6G Security, Federated Learning, and Channel Estimation. Notable awards include the Kansas Board of Regents Faculty of the Year (2024), Miller Professional Award (2023), and IEEE Transactions on Communications Best Paper Award (2016).

• Scientific Honors
  • Kansas Board of Regents Faculty of the Year (2024)
  • Miller Professional Award for Research (2023)
  • Harry Talley Excellence in Teaching (2022)
  • IEEE Stephen O. Rice Prize (2016)
  • CityU Hong Kong President's Award (2017)

Active grants include NSF Convergence Accelerator Track G, ONR projects, and NASA collaborations. His research group has produced 29 US patents and supervised numerous PhD students, including Hadi Ghauch (now Assistant Professor at Telecom Paris) and Wei Zhang (now at Harbin Institute of Technology Shenzhen).