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Revision as of 23:30, 2 May 2026


SRLab
Software Reliability Laboratory

Research on Trustworthy Software for Aerospace and Autonomous Systems

Digital Twin Β· Runtime Assurance Β· Airborne Software Β· LLM Engineering

About the Lab

SRLab, the Systems Research Laboratory'system software for trustworthy and intelligent computing', particularly in domains where failure is not an option β€” aircraft, UAVs, and autonomous systems. Our mission is to make system software intelligent, reliable, and efficient across these high-stakes environments.

Our research integrates the following themes:

  • AI-Driven System Software β€” bringing Artificial Intelligence, Vision-Language Models (VLM), and Agentic AI into the system software stack
  • Physical AI β€” designing and verifying AI systems that interact with the physical world
  • Digital Twin β€” modeling and operationalizing digital twins for aircraft, UAVs, and autonomous platforms
  • Runtime Assurance (RTA) β€” ensuring runtime safety and fail-safe behavior in real-time environments
  • Edge Computing & Computation Offloading β€” optimizing distributed computing under resource constraints
  • LLM for Software Engineering β€” automating software engineering processes with Large Language Models

These threads converge on a single question: how do we design, implement, and verify trustworthy system software?

  • Affiliation: Aerospace Software Engineering Program, Gyeongsang National University
  • Principal Investigator: Prof. Seongjin Lee
  • Location: Jinju, Gyeongsangnam-do, Republic of Korea
  • Email: insight@gnu.ac.kr

β†’ Meet our researchers Β· β†’ Learn more about us

Research Areas

πŸ›°οΈ Digital Twin (DT)

Building digital twin models for aircraft and UAVs, combined with edge/cloud computation offloading techniques, to enable real-time monitoring and predictive diagnostics.

β†’ View DT researchers Β· 0 publications

πŸ›‘οΈ Runtime Assurance (RTA)

Designing runtime monitoring and fail-safe mechanisms that guarantee safety of aerospace and autonomous systems during operation. We also explore verification methodologies aligned with avionics standards such as DO-178C.

✈️ UAV & Airborne Software

Designing and verifying embedded software for unmanned aerial vehicles β€” from flight control to mission management β€” including work on open platforms such as PX4 and ROS2.

πŸ€– LLM for Software Engineering

Leveraging Large Language Models to transform software engineering workflows β€” from requirements analysis and code generation to automated documentation of safety-critical software.

πŸ—οΈ Structural Health Monitoring (SHM)

Sensor-driven techniques for diagnosing and predicting structural conditions, with applications in aircraft structural health monitoring systems.

πŸ”— Multi-Agent Systems (MAS)

Algorithms for coordination and cooperation among multiple autonomous agents, along with verification methods for distributed systems.

β†’ Explore our research in depth

News & Highlights

Recent Publications

On-the-fly repair of multi-variable atomicity violations in airborne software
Changhui Bae; Euteum Choi; Ok-Kyoon Ha; Yong-Kee Jun; Seongjin Lee
Journal of Systems and Software, vol. 239, pp. 1128892026
DOI: 10.1016/j.jss.2026.112889
Digital twin platform for real-time data communication in UAV environment
Changhui Bae; Euteum Choi; Sungjoo Kang; Sungsoo Ahn; Seongjin Lee
Future Generation Computer Systems, vol. 175, pp. 1080782026
DOI: 10.1016/j.future.2025.108078
Software Execution Error Diagnosis for UAS Health Management
Jinseok Park; Keon-Pyo Lee; Euteum Choi; Yong-Kee Jun; Seongjin Lee
Journal of the Korean Society for Aeronautical & Space Sciences, vol. 53, no. 4, pp. 433-4442025
DOI: 10.5139/JKSAS.2025.53.4.433
... further results

β†’ All Publications

Recent Patents

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... further results

β†’ All Patents and Software Copyrights

Join Us

We are looking for motivated researchers

SRLab welcomes students passionate about software for aerospace and autonomous systems. You may be a great fit if you are interested in:

  • Safety-critical systems β€” aircraft, autonomous vehicles, medical devices, and beyond
  • Digital twins, simulation, and model-based development
  • Embedded software, with experience or willingness to learn C/C++, Python, ROS
  • Applying LLMs to automate software engineering tasks

Open Positions

Level Requirements Preferred Background
PhD Student M.S. degree (or equivalent) in a relevant field, or expected completion Publication record, prior research project experience
M.S. Student Bachelor's degree (or expected completion) Programming background; experience in aerospace SW or AI projects
Undergraduate Intern 3rd or 4th year undergraduate students Self-motivated learning attitude, team project experience

What We Offer

  • Funding: Tuition and stipend support for graduate students through government and industry-funded projects (BK21, NRF, etc.)
  • Research Environment: Dedicated workspace, high-performance workstations, GPU servers, and UAV experimental equipment
  • Growth Opportunities: Support for domestic and international conference presentations, industry collaborations, and overseas internship programs
  • Career: Our alumni have joined leading institutions and companies in aerospace, software, and AI (β†’ See Alumni)

International Students

We actively welcome international students. Our lab currently has researchers from multiple countries, and English is widely used in research discussions. Information about Korean Government Scholarships (KGSP) and other funding options for international students is available upon request.

How to Apply

If you are interested, please send the following documents by email:

  1. CV / Resume
  2. Academic transcripts
  3. A short statement (1 page) describing your research interests and motivation
  4. (Optional) GitHub profile, portfolio, or representative publications

πŸ“§ Contact: lab@gnu.ac.kr (Principal Investigator)

After an initial email exchange, we will arrange a meeting in person or via video call.

Quick Links

πŸ‘₯ Members
PhD Β· M.S. Β· Undergrad Β· Alumni

πŸ”’ Patents
36 filed

πŸ”¬ Projects
Ongoing & completed

Contact

  • Address: Gyeongsang National University, Jinju, Gyeongsangnam-do, Republic of Korea
  • Email: insight@gnu.ac.kr
  • Phone: +82-55-772-1378
  • GitHub: github.com/System-SW

Β© SRLab, Gyeongsang National University Β· Last updated: 2026-05-02

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