I am currently a Research Assistant Professor with the Department of Electronic and Computer Engineering (ECE), The Hong Kong University of Science and Technology (HKUST). Before joining HKUST, I was a Postdoctoral Fellow with the State Key Laboratory of Internet of Things for Smart City, University of Macau. I received the B.Eng. degree in Optoelectronic Information Engineering from Nanjing University of Science and Technology in 2016, the M.S. degree in Biomedical Engineering from the University of Science and Technology of China in 2019, and the Ph.D. degree in Information and Communication Engineering from Southeast University in 2023.

My research centers on AI-native wireless communications. I have built a long-standing research foundation in channel intelligence for advanced MIMO, spanning CSI acquisition, feedback, estimation, prediction, extrapolation, beamforming-oriented learning, and deployment. My current research focuses on two complementary directions: efficient, adaptive and trustworthy wireless AI, and wireless foundation models and environment intelligence. Across these directions, I connect wireless-domain modeling, artificial intelligence, practical deployment, and 3GPP standardization.

I have authored or co-authored more than 90 research papers, including more than 20 first-author journal papers. My research has received more than 3,300 citations with an h-index of 27 according to Google Scholar. I have also served as the contact person for more than 20 3GPP contributions submitted to 3GPP RAN, RAN1, and RAN4.

My research achievements have been recognized by several awards and honors, including the First Prize of the Natural Science Award of the Chinese Institute of Electronics, the Best Ph.D. Thesis Award of the Chinese Institute of Electronics, the Best Ph.D. Thesis Award of Jiangsu Province, and the selection of our research on AI Theory and Technology for Air Interface as one of the 2022 Annual Top Ten Technological Advancements in Information and Communication in China.

Should you have any inquiries or be interested in research collaboration, please feel free to contact me at eejiajiaguo@ust.hk.

Main Research Interests

Channel Intelligence for Advanced MIMO
CSI acquisition and feedback, channel estimation and prediction, channel extrapolation, beamforming-oriented learning, RIS/cell-free MIMO, and signaling-efficient channel knowledge.
Efficient, Adaptive and Trustworthy Wireless AI
Lightweight AI, knowledge distillation, online and federated adaptation, Learngene/Learnware, large-small model collaboration, performance monitoring, and deployment-efficient wireless AI.
Wireless Foundation Models and Environment Intelligence
Environment knowledge, semantic digital twins, multimodal side information, large AI models and wireless foundation models, large-small model collaboration, reusable wireless knowledge across tasks and scenarios, wireless radiance fields, and 3D Gaussian Splatting for wireless communications.
3GPP Standardization & Technology Translation
3GPP RAN1/RAN4, AI/ML for the air interface, CSI acquisition and compression, data collection and monitoring, model pairing and lifecycle management, testing and interoperability, superimposed pilots, and 6G-related standardization.

Tutorial

Spatial Intelligence for Wireless Communications and Sensing: Methods to Applications

with Jun Zhang, Yumeng Zhang, and Chenghong Bian (3 hours). in IEEE/CIC ICCC, Wuhan, China, Aug. 2026 and IEEE GLOBECOM, Macau, Dec. 2026..

Research Paper Collections

Large AI Models for Wireless Physical Layer

A curated collection of papers on Large AI Models (LAMs) for wireless physical-layer applications, extended from our overview paper:

Paper: Large AI Models for Wireless Physical Layer
Paper collection: AI4Wireless/LAM4PHY_6G

3D Gaussian Splatting for Wireless Communications

A curated collection of papers on 3D Gaussian Splatting (3DGS) for wireless communications, covering wireless radiance fields, radio environment reconstruction, channel representation, environment-aware communications, and related optical-RF spatial intelligence.