Research software developed in my work on cybersecurity, data quality and power systems. Each entry states its availability, so that readers can find and reuse what is public.
DataAiPrep
Machine learning data-quality assessment platform
DataAiPrep provides tools for inspecting and improving datasets used in machine learning. According to its public repository, it covers missing-value analysis, outlier and data-drift detection, fairness and bias analysis, data-leakage detection, feature selection, SHAP-based explainability, and interactive quality reports.
| Language | Python (3.8+) |
|---|---|
| Source code | Public GitHub repository |
| Documentation | README with user guide, API reference, CLI reference and examples |
| Publication | SoftwareX, vol. 34, Art. no. 102662, 2026. doi:10.1016/j.softx.2026.102662 |
| License | MIT, according to the repository |
If you use DataAiPrep in your research, please cite the SoftwareX article above.
Power_Security_Lib
A library that enhances power system cybersecurity by providing security checks.
Source code on GitHub · MIT license
PhySecGuard
A security toolkit offering physical security assessment capabilities and data analytics.
Source code on GitHub · MIT license
Cybermicrogrid
A microgrid simulation platform with advanced cyber-threat modeling.
Source code on GitHub · MIT license
AI-Cybersecurity platform
An end-to-end vulnerability assessment and model-protection pipeline for AI files.
Source code on GitHub · MIT license
More research code
Code accompanying my published and ongoing research is available on my GitHub profile. To discuss collaboration, please contact me.