We work on the theory and practice of trustworthy intelligent systems, with a particular focus on safety, verification, and real-world deployment.
We aim to develop methods that provide formal guarantees for systems that directly affect human lives, combining rigorous formal methods with data-driven learning and practical engineering.
Key facts about the AiX Lab since its foundation.
Lab founded at Gyeongsang National University.
Master’s students graduated.
Master’s students currently enrolled.
Collaborations with UPenn, KAIST, Aalborg University, INRIA/RISA, and more.
I am an associate professor in the Department of AI Information Engineering at Gyeongsang National University. I completed my postdoctoral research under the supervision of Professor Insup Lee at the PRECISE Lab, University of Pennsylvania.
My research interests include software verification and validation, especially for cyber-physical systems (CPS), and the safety and trustworthiness of AI in domains such as medical AI and autonomous driving. I recently developed Ophtimus (Ophthalmological Small Language Models), a family of domain-specialized ophthalmology LLMs designed to support reliable clinical decision-making.
I have collaborated with groups at the PRECISE Lab of the University of Pennsylvania, KAIST, Aalborg University, and INRIA/RISA, and previously worked with advisors including Kim G. Larsen, Axel Legay, and Sungwon Kang.
This page summarizes the academic outcomes of the AiX Lab, including publications, patents, software artifacts, and awards.
Journal and conference papers covering AI safety, formal verification of CPS, medical AI, and autonomous driving.
You can find a detailed list of publications on the Publication page.
Patents related to formal methods, medical AI pipelines, and autonomous driving (including F1TENTH-based RoboRacer platforms).
Open-source and research software developed in the lab, including trusted AI toolchains, medical AI models, and autonomous driving stacks.
Awards and recognitions from academic conferences, competitions, and industry collaborations related to AI safety and CPS.