Juseong Park

Senior Engineer @ Qualcomm Wireless R&D | Ph.D. in ECE, UT Austin

I am a wireless communications researcher at Qualcomm. I received my Ph.D. in Electrical and Computer Engineering from The University of Texas at Austin in 2026, where I was advised by Prof. Jeffrey G. Andrews and was a member of the Wireless Networking and Communications Group (WNCG) and the 6G@UT Research Center. I received my B.E. and M.E. degrees from Korea University, where I was advised by Prof. Inkyu Lee. During my Ph.D. studies, I completed research internships at Nokia Bell Labs, Nokia Standards, and Qualcomm.

My research interests lie at the intersection of wireless communications, signal processing, and machine learning, with a particular focus on multi-user MIMO, CSI acquisition and feedback, channel modeling, and generative learning for wireless systems.

Research Interests

Wireless Communications: Multi-User MIMO, CSI Acquisition and Feedback, Channel Modeling
Machine Learning for Wireless: Generative Models, Deep Learning, Representation Learning
Signal Processing: Optimization, Compressive Sensing

Education

The University of Texas at Austin
Ph.D. in ECE (2022–2026)
Dissertation: Deep Learning-Enabled Multi-User MIMO Systems: Efficient Pilot and Feedback Strategies
Korea University
M.E. in ECE (2019 - 2021)
Korea University
B.E. in Electrical Engineering (2013 - 2019)

Publications

Journal Articles

Self-Nomination: Deep Learning for Decentralized CSI Feedback Reduction in MU-MIMO Systems
J. Park, F. Sohrabi, J. Du, and J. G. Andrews
IEEE Transactions on Wireless Communications, vol. 25, pp. 10321-10336, 2026.
Generating High Dimensional User-Specific Wireless Channels Using Diffusion Models
T. Lee, J. Park, H. Kim, and J. G. Andrews
IEEE Transactions on Wireless Communications, vol. 25, pp. 2907-2921, 2026.
End-to-End Deep Learning for TDD MIMO Systems in the 6G Upper Midbands
J. Park, F. Sohrabi, A. Ghosh, and J. G. Andrews
IEEE Transactions on Wireless Communications, vol. 24, no. 3, pp. 2110-2125, March 2025.
Deep Recurrent Q-Network Methods For Mmwave Beam Tracking Systems
J. Park, H. Lee, S. Hwang, and I. Lee
IEEE Transactions on Vehicular Technology, vol. 71, no.12, pp.13429-13434, December 2022.
Decentralized Computation Offloading With Cooperative UAVs: Multi-Agent Deep Reinforcement Learning Perspective
S. Hwang, H. Lee, J. Park, and I. Lee
IEEE Wireless Communications, vol.29, no.4, pp.24-31, August 2022.
Grid-Based Bayesian Beam Tracking With Multiple Observations for Millimeter Wave Channels
J. Park, S. Baek, J. Moon, and I. Lee
IEEE Transactions on Vehicular Technology, vol.70, no.12, pp.13413-13417, December 2021.

Conference Proceedings

Learning Ray-Tracing for Radio Propagation via Cross-Attention-Based Diffusion Models
J. Park, T. Lee, Y. Xing, J. Chen, A. Ghosh, and J. G. Andrews
Asilomar Conference on Signals, Systems, and Computers, pp. 1210-1214, Nov 2025.
Self-Nomination Based Feedback Reduction for MU-MIMO
J. Park, F. Sohrabi, J. Du, and J. G. Andrews
Asilomar Conference on Signals, Systems, and Computers, Nov 2024.
High Dimensional User-Specific Channel Generation for CSI Compression Using Diffusion Models
T. Lee, J. Park, H. Kim, and J. G. Andrews
Asilomar Conference on Signals, Systems, and Computers, Nov 2024.
Deep Reinforcement Learning Approach for UAV-Assisted Mobile Edge Computing Networks
S. Hwang, J. Park, H. Lee, M. Kim and I. Lee
IEEE Global Communications Conference (Globecom), Dec 2022.

Juseong Park

Research Interests

Education

Publications

Journal Articles

Conference Proceedings

Recent Posts

Self-Nomination for Decentralized CSI Feedback Reduction in MU-MIMO

End-to-End Deep Learning for TDD MIMO Systems in the 6G Upper Midbands