• Building a Video AI Evaluation Platform
  • Benchmarking: Build an evaluation pipeline for video understanding and benchmark frontier models (e.g., Gemini, GPT)
  • Monitoring: Design a scenario-based evaluation system for daily health checks and regression detection after model updates
  • Visualization: Develop an interactive web dashboard to review and share research results and demonstrate outcomes to external partners (e.g., Samsung Electronics)
  • Infrastructure: Architect a Ray-based distributed video indexing pipeline to process ~300 videos in parallel and build a Feast-based feature store serving as the single source of truth (SSOT) for video-derived features
• Research on Video Understanding
  • Video Scene Segmentation: Study methods for segmenting videos into meaningful narrative units (scenes) while preserving contextual information
  • Video RAG: Explore retrieval-augmented generation approaches that leverage visual and audio signals for efficient storage and retrieval of video knowledge

• Conducted research spanning video anomaly detection and medical image segmentation, with 4 first-author publications.
  • Anomaly Detection: Developed AnyAnomaly, a zero-shot VAD framework using LVLMs (WACV 2026); developed VideoPatchCore extending PatchCore to the video domain (ACCV 2024); proposed MAMA, an SSL-based framework to amplify anomaly signals via frame destruction (IEEE Access)
  • Segmentation: Developed DS-UNETR, a dual-stream fusion U-Net Transformer for 3D medical image segmentation (IEEE BigComp 2024)
• Graduation thesis: VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection · Research Portfolio
• Advisor: Prof. Sanghyun Park (sanghyun@yonsei.ac.kr)

Poster presentation

Accepted at NVIDIA GTC 2026, San Jose, CA

• Enhanced video retrieval performance through scene-based video indexing
• Conducted Video QA experiments comparing uniform segmentation and scene-based segmentation on long-video benchmark

Team project

Grand Prize in Capstone Design Contest (Top project)

• Led the Fridge team; designed and implemented an end-to-end AI system
• Developed a vision-based AI chatbot for automatic food expiration-date recognition and management
• Conducted industry interviews with E-mart (Shinsegae Group) to validate real-world adoption scenarios