Telecommunications Network Group

The Telecommunications Network Group (TNG) is a premier research unit at the intersection of physical systems and computational intelligence. Comprised of 14 distinguished faculty members from both the Department of Electronics and the Department of Computer Science, the group leverages a unique multidisciplinary synergy to solve complex interconnectivity challenges.
Core Research Areas
The group’s activities are organized into four strategic pillars, encompassing the most critical advancements in modern telecommunications:

1. AI-Driven Intelligent Network Automation & Analytics
The group focuses extensively on the integration of Machine Learning (ML) and Deep Learning for communication networks, moving toward self-optimizing infrastructures. This includes the application of Big Data and ML for traffic analysis and monitoring, providing deep insights into network behavior. A key frontier of their research is Agentic AI for cybersecurity, where autonomous agents detect, respond to, and mitigate threats in real-time without human intervention.

2. Next-Generation Infrastructure & Virtualization
The transition toward programmable hardware is a central theme. The group investigates:
- Software Defined Networking (SDN) and programmable data planes, allowing for granular control over network traffic.
- Cloud Computing and Network Function Virtualization (NFV) to decouple hardware from service logic.
- Optical switching architectures and networks, pushing the boundaries of high-capacity data transport.
- Traffic control in data centers, optimizing resource allocation for high-density computing environments,
- Job scheduling policies in LLM inference system.

3. Security, Privacy & Social Dynamics
Beyond technical performance, the group prioritizes the human and safety dimensions of technology. Research in Cybersecurity and Online Privacy ensures the integrity of data across public and private domains. Uniquely, the group also explores Social Media Networks and related dynamics, applying mathematical modeling to understand how information and influence propagate through digital societies.

4. Sustainability & Specialized Applications
Recognizing the environmental impact of ICT, the group is dedicated to developing energy-efficient and green networks to reduce the carbon footprint of global connectivity and to improve network resilience. In this area the group investigates:
- Networks powered by renewable energy sources
- Integration of aerial nodes into the terrestrial infrastructure
- Network and infrastructure sharing
- Edge AI to distribute intelligence at the edge of the networks
Furthermore, the group pushes the limits of low-latency synchronization through research in Networked music performance, enabling real-time collaborative arts over long distances, a rigorous testbed for ultra-reliable communication.

Impact and Methodology
The group’s structure provides a rare "full-stack" research environment, thanks to the mixed expertise of the members from two departments. This collaborative framework allows the group to transition seamlessly from theoretical modeling to the deployment of functional prototypes. Their work serves as a vital bridge between academic innovation and industrial application, contributing to international standards and providing a high-level training ground for the next generation of engineers and researchers working on computer and telecommunication networks.