Environmental researcher working on exposure assessment, risk analysis, and environmental data analysis.
Current interests include environmental exposure, quantitative risk assessment, microplastics, data integration, ontologies, and knowledge graphs.
Computational tool for reproducing dietary microplastics exposure calculations from published data.
- React dashboard and Streamlit interface
- Exposure and particle-mass calculations
- Automated calculation tests
Early-stage project for structuring links between microplastic occurrence, exposure, and toxicological evidence.
- RDF/OWL data modeling
- Exposure–toxicity evidence mapping
- SPARQL queries
- Study-level provenance
Python workflow for evaluating synthetic VOC proficiency-testing data and measurement variability.
- TVOC and toluene proficiency metrics
- Z-score and relative-error analysis
- Chamber and sampling-volume variability
- QA/QC visualizations
Text analysis of synthetic survey data on carbon black demand and applications in the context of turquoise hydrogen production.
- TF-IDF analysis
- NMF topic extraction
- Rule-based demand categories
- Survey-result visualization
I am interested in using structured data and computational methods to support environmental exposure and risk assessment, particularly where information is distributed across different datasets and evidence sources.
Current areas of interest include exposure data harmonization, ontology-based data integration, knowledge graphs, and quantitative risk analysis.
- M.S. in Environmental Science and Ecological Engineering, Korea University
- Environmental testing and R&D experience at Korea Conformity Laboratories
- Research experience in microplastics, exposure assessment, VOC measurement, and environmental QA/QC