Industrial AI
ML engineered for real-world industries (manufacturing, environment, food, health, and more) for prediction, monitoring, and decision support on operational data.

Don’t compare yourself to anyone else because we all have our own unique journey and story that we should be proud of.
I'm currently a tenure-track faculty member at Kookmin University in Seoul, where I've worked since 2026. Before that, I worked at Sejong University in Seoul, from 2022 to 2026. I also spent three years (2019-2022) as a full-time faculty member and five years (2014-2019) as a fully-funded graduate researcher/research assistant at Dongguk University.
My research is in industrial AI, data science, and big data. I like building systems that hold up on messy, real-world data. I also teach programming, machine learning, and database courses, and enjoy helping students find their own path into the field. If you'd like to talk research or collaboration, feel free to reach out.
Applying AI and data science across industries (not just manufacturing, but environment, food, health, and beyond), wherever messy real-world data needs to become reliable decisions.
ML engineered for real-world industries (manufacturing, environment, food, health, and more) for prediction, monitoring, and decision support on operational data.
Turning heterogeneous, high-velocity data into trustworthy insight through representation learning and knowledge extraction.
Predictive and prescriptive analytics across sectors: forecasting, anomaly detection, and optimization that turn data into measurable value.
The systems layer of smart, connected industries: IoT (Internet of Things), digital twins, and edge-cloud pipelines linking sensors to intelligence.
(*) Publications and citations from Google Scholar. (**) Total peer review outlets from ORCID.