3D/4D Vision & Spatial Intelligence
Learning spatial and spatiotemporal representations for 3D reconstruction, dynamic-scene understanding, novel-view synthesis, and neural rendering.
HELLO, I'M
I am an undergraduate researcher at KAIST working on 3D computer vision, neural rendering, reinforcement learning, and multi-agent systems.
I am interested in systems that understand, reconstruct, and act in the physical world. My work connects research ideas to reproducible experiments—clear assumptions, controlled evaluation, failure analysis, and working code.
I am currently involved in research at KAIST CVLab. Previously, I explored AI for Science at DSAIL and led applied AI, education, and consulting projects.
Learning spatial and spatiotemporal representations for 3D reconstruction, dynamic-scene understanding, novel-view synthesis, and neural rendering.
Connecting visual perception, language reasoning, and embodied action to build agents that understand and interact with the physical world.
Designing human-centered AI experiences and coordinated agent systems that support communication, collaboration, and real-world decision-making.
KAIST CVLab collaborative research · Contributor (non-first author)
Contributed literature review, experimental-condition design, quantitative evaluation tables, baseline comparisons, and paper figures for dynamic-scene reconstruction research.
Manuscript under reviewKAIST CVLab collaborative research · Contributor
Contributing prior-art and baseline analysis, problem formulation, pipeline design, and weekly research materials for large-scale urban 3D reconstruction.
Work in progressAdditional project pages, paper links, and code will be added as they become publicly available.
Developed an AI assistant-powered communication service designed to help adolescents with developmental disabilities express themselves and engage in supportive conversations.
Measured the relationship between sky obstruction and satellite-internet performance by synchronizing terminal, GPS, network, and sky-mask data.
Developed a combat-simulation training workflow using PPO, SAC, curriculum learning, self-play, checkpoint recovery, and sequence replay.
Built a proxy-agent negotiation system that replans work when schedule changes create bottlenecks in software teams.
Selected moments from consulting, education, and applied AI work beyond the lab.
Led and contributed to strategy projects for Frip, Nota AI, and Coupang Play, turning market research into concrete service and go-to-market proposals.
Designed and delivered an English-language AI development curriculum with KAIST volunteers and students at the National University of Timor-Leste.
Won 3rd Prize in the AI sector by proposing a structured data pipeline and model-selection framework for an insurance AI solution, then presented the work at the final stage.
29th Cohort · Graduated early before entering KAIST.
Vice President · Led consulting projects for Nota AI and Frip, translating market questions into executable strategies.
AI Education Lead · Designed and delivered an English-language AI development curriculum.
Undergraduate Researcher · Reviewed AI for Science research and studied graph learning and scientific reasoning pipelines.
3rd Prize, AI Sector · Recognized for an AI project in Hanwha Life's future-talent competition before joining CVLab.
Undergraduate Researcher · Joined CVLab after the Hanwha Life contest, following the earlier research experience at DSAIL. Currently conducting research on 4D novel-view synthesis, city-scale mesh reconstruction, action latent representations, and vision-language-action models.
Craftsman Information Processing
Korean National Technical Qualification
APEX AI Certification
TOEIC 835
English proficiency
Research: 3D Vision, Neural Rendering, RL, Multi-Agent Systems
Languages: Python, C, Java, Scala, TypeScript
Systems: PyTorch, Node.js, SQL, MongoDB, Git
I am always open to discussing research, projects, and new ideas.