DAIS Research Group

The DAIS Research Group is a research group within the Energy AI & Computational Science Lab. at the Korea Institute of Energy Research (KIER). We develop AI methods for the heterogeneous data that arises in energy research — aiming for tools and pipelines that can be reused across projects rather than tied to a single domain or dataset.

Data → Analysis → Intelligence → System

D — Data. Collecting and organizing the diverse research data that arises in the field — unstructured documents (PDFs, reports, papers), experimental and process measurements, and more.
A — Analysis. Structure analysis and information extraction from documents; preprocessing of experimental and process data into shapes downstream models can use.
I — Intelligence. Classification, summarization, search, and recommendation over large document and data collections; prediction and fitting models for experimental and process data; robust learning methods combined with domain knowledge.
S — System. Turning models and analyses into things other people can actually use; automating repetitive work and keeping analysis code reproducible.

We collaborate with other groups within KIER and with external partners, organizing our work as reusable code and workflows rather than one-off solutions tied to a single project.

Publications

Domestic Conference Papers

Hyoeun Choi

First author

, Woonjae Ruh, Yun Sik Kang, Byeongseon An, Woonghee Lee

Corresponding author

(2026). Comparing SHAP and CRAFT Across Architectures for PEMFC SEM Images. ASK 2026 · 🏆 Bronze Award (Undergraduate Track).

Software Copyrights

Woonghee Lee (2026). AI-Based Technology-Trend News Collection, Analysis, and Report Generation System. SW Copyright C-2026-019657.