Ildar A.

💼 Expert in developing physics-based and data-driven models for forecasting (energy industry, fluid dynamics). Objectives (Python 3): ML/Math Model Prototyping (incl. from scratch), searching-for (math) bottlenecks in modelling pipelines, EDA.

📈 Author of three Scopus-indexed publications on mathematical modeling, covering data mining, inverse problems, and numerical methods:
➤ https://ui.adsabs.harvard.edu/abs/2020AIPC.2293P0071A/abstract
➤ https://onepetro.org/OIJ/article-abstract/2021/09/76/471866/Production-forecast-method-based-on-statistical
➤ https://onepetro.org/OIJ/article-abstract/2020/01/46/187383/Identification-of-fractal-properties-and

🎓 Master in Applied Math and CS (Russia).

💻 Full List of Projects & Publications available on Github Pages.

🔬 Research Competencies

📐 Mathematical Modeling

• Partial Differential Equations (2D quasilinear diffusion)
• Finite Element Methods (FiPy implementation)
• Fractal derivatives in physical systems
• Numerical analysis of singular models

📊 Data Science

• Monte Carlo simulations
• Gradient Boosting (XGBoost)
• Statistical analysis (pandas, statsmodels)
• Feature engineering for physical systems

💻 Implementation

• Python (numpy, matplotlib, sklearn)
• VBA for Excel automation
• Maple for symbolic computation

🔎 Methodological Focus

• Physics-constrained machine learning
• Numerical solution of hydrodynamic equations
• Interpretable models for engineering applications