Areas & Directions

Research Areas
1. AI-Native Networking and AI-RAN

We study how future mobile networks can be redesigned as AI-native platforms. This includes AI-RAN architectures, RAN intelligence, AI-assisted radio/network optimization, and the interaction between AI workloads and communication systems.

Keywords: AI-RAN, 5G-Advanced, 6G, RAN intelligence, O-RAN, network-aware AI, AI-aware networking

2. Autonomous Network Systems

We investigate autonomous network operation using data-driven observability, closed-loop automation, and AI agents. Our research explores how networks can monitor themselves, understand intent, detect anomalies, and perform adaptive optimization with minimal human intervention.

Keywords: autonomous networks, closed-loop automation, observability, AI agents, intent-based networking, xApps/rApps, near-/non-RT RIC

3. Edge Intelligence and Real-World AI Services

We develop edge/cloud collaborative AI systems that support low-latency, high-reliability, and context-aware AI services. Application domains include robotics, smart campus services, intelligent mobility, and multimodal AI services over advanced network infrastructure.

Keywords: edge AI, distributed inference, low-latency AI services, campus networks, robotics, multimodal AI

4. Next-Generation Communication Infrastructure

We work on programmable, cloud-native, and scalable communication infrastructure for future AI-driven services. This includes telco cloud, virtualization, Kubernetes-based network platforms, programmable transport, and large-scale testbeds for validating future network architectures.

Keywords: telco cloud, cloud-native networks, Kubernetes, programmable infrastructure, network virtualization, large-scale testbeds

Selected Research Directions

• AI-native architecture for future mobile networks

• AI-RAN and intelligent RAN control

• Autonomous network operation using AI agents

• Near-real-time RIC (RAN Intelligent Controller), non-real-time RIC, xApps, and rApps

• Edge/cloud collaborative AI inference

• Network infrastructure for robotics and real-world AI services

• Observability and closed-loop automation for telecom networks

• Scalable testbeds for 5G-Advanced and 6G systems

Research Philosophy

Our research is driven by three principles:

• System-oriented research
  We value end-to-end system design, implementation, and validation, beyond isolated algorithms or conceptual models.

• Real-world impact
  We aim to solve practical problems in communication infrastructure, AI services, and autonomous operation through close collaboration with industry and public-sector partners.

• Bridging networks and AI
  We believe future innovation will emerge at the intersection of networking and artificial intelligence — where networks support AI services, and AI transforms the way networks are designed and operated.