Aliaksandr

Alvinskiy

Portfolio demo of a reproducible Python workflow for messy order exports. It validates dates, quantities and USD prices, removes exact duplicates, quarantines conflicting records and calculates completed-only order totals. Outputs include clean CSVs, exception logs, monthly summaries, a SHA-256 audit manifest and a searchable offline HTML report. The supplied synthetic run reconciles 622 input rows into 582 accepted orders, 18 duplicates and 22 quarantined records. Includes 23 passing unit tests and focused browser checks. No paid-client results are claimed.

Independent educational web project built with Next.js, React, TypeScript and Tailwind CSS. It connects illustrated textbook chapters, guided physics experiments, worked examples and practice. The featured mean-speed lesson lets learners change travel times and distinguish average speed from average velocity. The implementation includes textbook search and class filters, local progress, saved explanations and progress backup/restore. The attached case uses actual project screenshots. This is an in-development product with partial curriculum coverage.

University research project on low-energy spectra of superelliptic tight-binding quantum dots. The dataset covers 140 geometries across four boundary exponents, five sizes and seven aspect ratios. Work includes lattice-model construction, direct Kwant calculations, scientific Python analysis and compact regression models. Validation withholds complete size or aspect-ratio groups. The attached case reconstructs the model geometry and plots saved Ridge error summaries from the public repository. This is a controlled model study, not material-specific DFT or a paid client project.