Department Department of Electronic and Computer Engineering/National Taiwan University of Science and Technology

RT Lab

Wang, Jui-Tang (RT)
https://sites.google.com/view/rt-lab

Research Field

Telecommunication Engineering
Introduction

He received his Master's degree from the Department of Computer Science and Information Engineering at National Cheng-Kung University in 2000 and his PhD degree from the Department of Computer Science and Information Engineering at National Chiao-Tung University, Taiwan, in 2008. In February 2019, he joined the Department of Electronic and Computer Engineering at the National Taiwan University of Science and Technology as an Assistant Professor. His research focuses on wireless communication and security protocol. 

  1. 5G/6G Communication Protocols and Management Platform
  2. Blockchain Network and Application
  3. Cloud Computing
  4. Networking System Performance Modelling and Analysis
  5. Innovation Patent Portfolio

Research Topics
  • 5G/6G Communication Protocols and Management Platform
  • Blockchain Network and Application
  • Networking System Performance Modelling and Analysis
  • Innovation Patent portfolio
Honor

None

Educational Background

He received his Master's degree from the Department of Computer Science and Information Engineering at National Cheng-Kung University in 2000 and his PhD degree from the Department of Computer Science and Information Engineering at National Chiao-Tung University, Taiwan, in 2008. In February 2019, he joined the Department of Electronic and Computer Engineering at the National Taiwan University of Science and Technology as an Assistant Professor. His research focuses on wireless communication and security protocol. 

Job Description

Standards study & technical digest

  • Read and summarize key 3GPP 5GC specs (service-based architecture, NFs, procedures, interfaces) and O-RAN architecture/specs (RIC, SMO, interfaces).
  • Produce weekly technical notes: “what the spec says” → “what we implement” → “what we measure”.

Open-source testbed implementation

  • Deploy and integrate 5GC/RAN components using open source (e.g., free5GC / Open5GS / OpenAirInterface / srsRAN / O-RAN SC, depending on project needs).
  • Containerized deployment with Docker/Kubernetes/Helm, basic CI scripting, and reproducible experiment setup.

Algorithm design & prototyping

  • Design algorithms for network intelligence/optimization (e.g., RIC xApp/rApp control, admission control, handover tuning, slicing/resource allocation, anomaly detection, NWDAF-driven analytics).
  • Implement prototypes in Python/C/C++/Go (as appropriate) and integrate with the testbed.

Experimentation & evaluation

  • Define KPIs and run experiments (latency, throughput, stability, signaling overhead, reliability).
  • Use tools like Wireshark/tcpdump, and monitoring stacks (Prometheus/Grafana) to collect evidence.

Technical writing & publication

  • Contribute to figures/tables, reproducibility notes, and paper drafting for IEEE/ACM venues.
  • Maintain clean documentation and version control on Git.

Preferred Intern Educational Level

  • Master’s student (preferred) in Computer Science, Electrical/Electronic Engineering, Telecommunications, Network Engineering, or a closely related field.
  • Strong senior undergraduates with relevant experience are also welcome.

Skill sets or Qualities

Must-have

  • Solid fundamentals in computer networking (TCP/IP, routing, HTTP, Linux networking basics).
  • Comfortable working in Linux environments and using Git.
  • Ability to read and extract key points from technical specifications and research papers.
  • One programming language proficiency: Python / C/C++ / Go.

Nice-to-have

  • Knowledge of 5G Core (3GPP SBA) concepts: AMF/SMF/UPF, N1/N2/N3, NAS, PFCP, SBI/HTTP-based service calls.
  • Familiarity with O-RAN: SMO, near-RT RIC, E2/A1/O1 interfaces, xApps/rApps (concept-level is fine).
  • Experience with containers: Docker, Kubernetes, Helm; basic cloud/VM operations.
  • Experimentation mindset: KPI design, trace analysis, log parsing, and performance profiling.
  • Interest/experience in ML/optimization applied to networks.

Personal qualities

  • Strong ownership and execution: can turn ambiguous requirements into a working plan.
  • Detail-oriented and evidence-driven (logs, traces, reproducibility).
  • Clear communication in English (reading/writing); teamwork and steady progress reporting.