news

Dec 06, 2025 Our paper, PEARL: Peer-Enhanced Adaptive Radio via On-Device LLM, has been presented at the NeurIPS’25.
Oct 13, 2025 Our work has been selected as an oral presentation at the NeurIPS’25 (AI4NextG).
Aug 25, 2025 Invited to serve on the Program Committee for the AI4NextG Workshop at NeurIPS’25.
Jul 18, 2025 Invited to join the ML4Wireless panel discussion at the ICML’25 as an industry speaker.
Jul 17, 2025 Our paper, On-Device LLM for Context-Aware Wi-Fi Roaming, has been presented at the ICML’25.
Jul 16, 2025 Our paper, AutoBS: Autonomous Base Station Deployment with Reinforcement Learning and Digital Network Twins, has been presented at the ICML’25.
Apr 04, 2025 Our paper, “Generative vs. Predictive Models in Massive MIMO Channel Prediction” has been presented and published at the Asilomar’24.
Feb 02, 2025 Invited to serve on the Technical Committee for the IEEE Globecom’25 MLCN (Machine Learning for Communications and Networking) track.
Sep 17, 2024 Our paper, “A Scalable and Generalizable Pathloss Map Prediction” has been accepted and published in the IEEE TWC.
Sep 09, 2024 Our paper, “Integrating Pre-Trained Language Model with Physical Layer Communications” has been accepted and published in the IEEE TWC.
Aug 26, 2024 Joined Nokia in Sunnyvale, CA, USA as a Principal Researcher specializing in AI/ML.
Apr 19, 2024 Invited to serve on the Technical Committee for the IEEE ICASSP’24 RMA (Radio Maps and Their Applications Workshop).
Feb 29, 2024 Invited to serve on the Technical Committee for the IEEE Globecom’24 MLC (Machine Learning for Communications) track.
Jan 23, 2024 Collaborated on-site with the SMI team at Samsung Research America (Dallas, TX) on low-complexity generative model-based channel prediction for mMIMO systems.
Dec 23, 2023 Our paper, “Handover Protocol Learning for LEO Satellite Networks” has been accepted and published in the IEEE TWC.
Dec 08, 2023 Our two papers, “Robust Pathloss Map Prediction via Supervised Learning” and “Simple and Effective Augmentation Methods for CSI-Based Indoor Localization,” were presented at the IEEE GLOBECOM’23.
Jun 10, 2023 Our designed PMNet framework achieved the 1st (Top)-Rank at the IEEE ICASSP’23 ML competition (Radio Map Prediction Challenge), thanks to its outstanding accuracy.
Dec 19, 2022 Our proposal, titled “End-to-End Semantic Communication Systems with Pre-Trained Model” was choosen as Selected Abstract in 2023 Qualcomm Innovation Fellowship.