Research Areas
Process Mining
Discovering process models from event logs and optimizing real-world workflows with data-driven insights.
Text Mining
Extracting meaningful knowledge from unstructured text using NLP and machine learning methods.
Data-Driven AI
Applying AI and machine learning to real-world processes and intelligent systems across diverse application domains.
Recent News
- ▪ (2026.08)The paper entitled "Integrating Text-Derived ESG Signals into Bayesian Portfolio Optimization: Evidence from South Korea" has been accepted for publication in Computational Economics.
- ▪ (2026.06)The paper entitled "Information Processing and Review Helpfulness in Online Platforms: A Dual-Process Perspective" has been accepted for publication in IEEE Access.
- ▪ (2026.04)The paper entitled "Structure Learning-Based Interaction Feature Construction for Bank Failure Prediction" has been accepted for publication in IEEE Access.
- ▪ (2026.03)Our lab has been awarded the Outstanding Young Scientist Grants entitled "A Layered AI-Augmented Process Science Framework: Model Intelligence, Behavioral Reasoning, and Operational Adaptation" funded by MSIT and NRF.
- ▪ (2026.01)The paper entitled "Extracting declarative constraints for process modeling from natural language descriptions with large language models" has been accepted for publication in Decision Support Systems.
- ▪ (2025.10)Our lab has been awarded the German–Korean Academia-Industry International Collaboration Grants entitled "AI-BioDynamics: Artificial Intelligence for Biodiversity Mapping and Conservation Decision-Making" funded by MSIT and NRF.
Join Us
We are looking for highly motivated students who are passionate about data analytics, machine learning, and AI research.
- Ph.D. and M.S. positions available
- Undergraduate research internships
- Strong background in CS, statistics, or related fields
- Experience with Python and ML frameworks preferred