Join Our Team!

AI-Powered Software Engineering

Our lab focuses on advancing cutting-edge AI technologies and software development techniques to enable innovative problem-solving and real-time collaboration. We specialize in the development of Retrieval-Augmented Generation Small Large Language Models (RAG-sLLM) and Retrieval-Augmented Generation Large Multimodal Models (RAG-LMM), enhancing their effectiveness and adaptability across diverse applications. Additionally, we conduct research in the following areas:

  • Fusion of Intelligent LLM Agents and Community-Based Knowledge: Researching advanced technologies that combine the reasoning capabilities of large language models (LLMs) with community-driven knowledge bases to enable innovative solutions and real-time collaboration in AI and software development.
  • Automated Software Artifact Generation Using Open-Source sLLMs: Leveraging the natural language understanding and code generation capabilities of open-source small language models (sLLMs) to automate the creation of software artifacts, including requirement definitions, design documents, code, and test cases, throughout the software development lifecycle.
  • Automatic Bug Patch Generation with Open-Source sLLMs: Utilizing the reasoning and generation capabilities of open-source sLLMs to automatically detect bugs in source code, analyze context, and generate appropriate patches. This research focuses on enhancing software maintenance efficiency through the automation of static analysis and code review processes.
  • Issue Template Automation and Collaborative Tool Integration with Open-Source sLLMs: Developing intelligent solutions that integrate open-source sLLMs with project management platforms (such as OpenProject, Mattermost, and GitLab) to automate issue template generation and optimize development workflows.
  • Code Security Issue Detection and Reporting System Using Open-Source sLLMs and DevSecOps: Combining the language understanding capabilities of open-source sLLMs with DevSecOps principles to develop systems that detect and report security vulnerabilities and compliance issues in real time.
  • Kubernetes Cluster Setup and Resource Monitoring with Open-Source sLLMs and MLOps: Designing and implementing systems that integrate open-source sLLMs with MLOps pipelines to automate Kubernetes cluster setup and efficiently monitor cluster resources and application performance.

Graduate Student Support

  • State-of-the-Art Resources: All students have access to a shared, high-performance Kubernetes-based Ray cluster, optimized for scalable and efficient model training and deployment. The cluster features cutting-edge hardware specifications, including 14th Gen Intel i9 CPUs with a total of 192 cores and 256 threads, 1TB of RAM, and dual H100 GPUs.
  • Personalized Research Space: All students are provided with a personalized research space optimized for productivity, including a high-performance server (Intel i9-14th Gen CPU, 128GB RAM, RTX 4090) and dual 27-inch LG monitors, creating a productive and immersive work environment.
  • Financial Support: Comprehensive funding is provided to cover tuition, living expenses, and annual productivity incentives.
  • Conference and Travel Opportunities: Full funding is provided for participation in leading domestic and international conferences and technical seminars.
  • Knowledge and Career Development: Students are given unrestricted access to IT literature, textbooks, coding assessments, portfolio-building tools, and personalized career guidance — all aimed at preparing them for positions at top-tier tech companies.
  • Industry Interaction: Students have regular opportunities to engage with industry professionals for knowledge sharing, mentorship, and networking.

Get in Touch

Lab. website Adviser website

Who Should Apply

  • We are looking for passionate, driven individuals who are eager to collaborate in a cutting-edge research environment and aspire to become leaders in the field of software engineering and development.

Application Details

  • Interested applicants should contact Prof. Geunseok Yang at gsyang@hknu.ac.kr (located in Engineering Building 1, Room 311).

No. of Recruitments

  • We are currently accepting applications for 4 positions: 2 Post-Doctorals and 2 Graduate Students. (July 2025)