Trustworthy Structuring at Scale
Building on this foundation, I joined the Human-Inspired AI Research Group at Korea University, where I was co-advised by Prof. Jaehyung Seo and Prof. Heuiseok Lim as I broadened my scope from sentence-level parsing to document-level structure understanding. Over the past three years, the core of my work has been expanding the scope of Trustworthy Structuring — from text and table QA[3][4] to industrial-document-level structure recovery[5], hierarchical multimodal retrieval[6], and retrieval-augmented generation[7].
Today I focus on unifying heterogeneous unstructured inputs — text, tables, images — into Structured Evidence that enables reliable long-context reasoning[8]. Beyond short-term metric gains, I am establishing fundamental mechanisms that allow AI to audit its own reasoning process, proving the explainability of multimodal document AI.
To tackle real-world challenges beyond what a single researcher could address, I founded KUDoc — the Document AI research group at Korea University — on my own initiative. I now lead and advise KUDoc, and together we have published 12 top-tier papers (including 4 as first author at ACL, CVPR, and EMNLP) and successfully completed 4 major industry–academia projects[9] with 3 technology transfers, ensuring that academic results translate directly into practical value. This leadership earned me a promotion to Senior Researcher.