AI Researcher @ Samsung AI Center
Industrial AI | Agent | Multimodal RAG | Robustness
I'm a Staff Researcher at Samsung AI Center (formerly SAIT AI Research Center), developing robust and efficient machine learning models tailored for industrial applications. My work has focused on AI-driven automation in manufacturing, spanning diverse modalities including vision, language, structured data (e.g., graph, tabular), and time-series domains.
I received my Ph.D. (through an integrated M.S./Ph.D. program) in Electrical and Computer Engineering from Seoul National University in 2022, under the supervision of Prof. Jin Young Choi. I received my B.S. in Electrical and Computer Engineering from Seoul National University in 2016.
AI Center, Samsung Electronics
Samsung Advanced Institute of Technology (SAIT)
Seoul National University
Advisor: Jin Young Choi
Seoul National University
Developing generalizable and transferable AI models for industrial applications
Building domain-specific AI agents that reason, plan, and interact with tools and environments
Enhancing AI agents with external multimodal knowledge retrieval for accurate and grounded responses
Improving model robustness under data imbalance, distribution shifts, and noisy labels
My research focuses on developing generalizable and transferable ML models for real-world applications. Recently, I have worked on improving model robustness under data imbalance (e.g., IB, PRIME), distribution shifts (e.g., BiasAdv), and noisy labels (e.g., SLC), but I am open to exploring a broader range of topics. First-author papers are highlighted.
Method and Device with Image-Difference Reduction Preprocessing [Google Patent]
Method and Electronic Device with Adversarial Data Augmentation [Google Patent]
Method and Device with Defect Detection [Google Patent]