I am a PhD-trained Art Historian specializing in post-Byzantine iconography, currently developing computational workflows to transform complex cultural heritage materials into machine-readable datasets. My work operates at the intersection of classical visual analysis, semantic data modeling, and computer vision processing.
My core research specialization is Sacred Temporality - specifically operationalizing the theological concepts of time (Kairos vs. Chronos) into measurable visual structures utilizing Python and OpenCV.
- Domain Expertise: Post-Byzantine Christian Art, Theological Visual Architectures, and Iconography.
- Computational Stack: Digital asset parsing with Python, database engineering using SQL, exploratory data analysis via Pandas, and structural image transformation utilizing OpenCV pipelines (CLAHE, histogram optimization).
- Open Science Frameworks: Structuring metadata compliant with CIDOC CRM schemas and archiving reproducible workflows in line with European FAIR data standards.
- [Technical Report] Preliminary Image Enhancement Framework for Post-Byzantine Iconography Using Contrast Limited Adaptive Histogram Equalization (CLAHE). [Forthcoming / In Progress]
- [Theoretical Working Paper] Visual Chronotypes of Christian Art: Operationalizing Sacred Temporality. [https://doi.org/10.5281/zenodo.21297721]
- [Theoretical Working Paper] The Problem of Time in Painting. [https://doi.org/10.5281/zenodo.21325537]
- [Theoretical Working Paper] Temporality as a Hidden Structural Axis of Visual Art. [https://doi.org/10.5281/zenodo.21350320]
- [Theoretical Working Paper] Between Eternity and Time: Christian Art, Sacred Presence, and Visual Form. [https://doi.org/10.5281/zenodo.21411969]
- [Theoretical Working Paper] Architecture as Theology: Time in Orthodox and Catholic Christianity: A Case Study of Nineteenth-Century Iconostases in the Kyustendil Region, Bulgaria [https://doi.org/10.5281/zenodo.21440939]
- The Core: An open-access pipeline mapping the regional visual language of the Samokov Iconographic School.
- The Tech: Deploys OpenCV architectures (
cv2.createCLAHE) to enhance structural boundaries on visually degraded icons, alongside statistical attribute distribution modeling via Pandas and Matplotlib.
- The Core: A comparative visualization infrastructure analyzing spatial and temporal transitions across foundational modern art movements.
- The Tech: Built utilizing Python pipelines, structured relational datasets, and dynamic visualization arrays to map geographical distribution variances.
- The Core: A relational database system mapping visitor behavioral profiles across pre-, peri-, and post-pandemic epochs at major cultural heritage institutions.
- The Tech: Comprehensive relational layout featuring custom normalization schemas, entity-relationship tracking (ERDs), and execution-ready SQL analytical scripts.