RESEARCHER

Summary: The Wireless Communication programme focuses on the physical and lower layers of wireless communication. The programme features both theoretical and practical learning, as well as plenty of group assignments and presentations. During the final semester, I was involved in active research under the supervision of Associate Prof. Hidekazu MURATA for my Masters thesis work on sum rate analysis of multi-user multi-input multi-output (Μ-MIMO) in centralized and distributed antenna systems under the effects of spatial correlation.

Summary: My doctoral research focused on the dynamic clustering (over transmit and receive antennas, carriers, power) problem in large-scale MU-MIMO distributed antenna systems. To solve the dynamic clustering optimization problem and reduce the precoding complexity in the considered systems, I proposed a simple and efficient clustering scheme based on multiple orthogonal carriers with maximizing the system sum rate. For the clustering problem in the systems, I have considered several design objectives and proposed other efficient and low-complexity clustering techniques. My doctoral research focused also on the user collaboration using the WLAN or milli-meter waves for future wireless communication systems.

Summary: Worked on wireless communication systems including cellular and IoT networks, artificial intelligence, and big data analysis. Responsibilities include: providing technical solutions to the clients; expert level fault handling; participate in projects and take charge from operation side; devising new solution and implement them to adapt new requirements; implementing access control and security process as part of network infrastructure.

Summary: Worked on wireless communication systems, resilient IoT networks, AI, and big data-driven modeling in academic projects. Responsibilities include: proposing research themes and technical strategies; leading development of radio propagation prediction using transfer learning and geographical knowledge, achieving high-accuracy RSSI estimation and IEEE publication; proposing federated transfer learning with data security considerations, leading to grants and patents; driving DX projects from problem formulation to system design, field trials, and implementation for applications such as mobility tracking and disaster-resilient sensing; contributing to 3D point cloud and Gaussian Splatting-based digital infrastructure and simulation; publishing research and promoting industry-academia collaboration.

Summary: Worked on wireless communication systems, machine learning (ML)-driven optimization, semantic communication, and 3D Gaussian Splatting (3DGS)-based modeling in practical environments. Responsibilities include: delivering client-focused solutions using ML-based radio propagation prediction and data-driven optimization; developing ML-based semantic communication techniques to improve transmission efficiency and context-aware performance; handling complex network faults with expert analysis; supporting project deployment and continuous system improvement; designing solutions integrating ML, semantic communication, and 3D spatial modeling; and ensuring network security and access control.