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lebedeffson/README.md

👋 Hi there! I'm Alex Lebedev

🚀 About Me

2nd year student of "Computer Science and Engineering" at "Dubna" University. Passionate about developing artificial intelligence systems with focus on:

  • 🧠 Machine Learning
  • 🔬 Explainable AI

🛠️ Tech Stack

Programming Languages:

Python C#

Data Science & ML Frameworks:

Pandas NumPy Scikit-learn XGBoost LightGBM CatBoost

Deep Learning Frameworks:

TensorFlow PyTorch Keras

Explainable AI Libraries:

SHAP LIME Captum DALEX Alibi InterpretML

Fuzzy Logic & ANFIS:

ANFIS xanfis scikit-fuzzy

Visualization & Analysis:

Matplotlib Plotly Seaborn

Development Tools:

Jupyter Git

.NET Ecosystem:

.NET Avalonia

Research Tools:

LaTeX Overleaf

📊 GitHub Statistics

GitHub Stats

Top Languages

🔬 Research Activities

  • 🧮 ANFIS Research - investigating neuro-fuzzy systems and their applications
  • 📊 Explainable AI - working on methods for interpreting ML model decisions
  • 📄 Trust-ADE Protocol - developing comprehensive trust assessment protocol for AI systems

🎓 Education

  • Bachelor's Degree in "Computer Science and Engineering" - "Dubna" University (2024-2028)
  • ORCID: 0009-0001-1046-5982

📫 Connect with Me

ORCID GitHub Email

📈 Activity

GitHub Activity Graph

🔥 Streak Stats

GitHub Streak

🌱 Currently Learning

  • Advanced Deep Learning architectures
  • Causal AI and causal inference
  • Neurosymbolic AI systems

Pinned Loading

  1. FuzzyAttentionNetworks FuzzyAttentionNetworks Public

    Python

  2. fims9000/KAN-XAI-2.0-System fims9000/KAN-XAI-2.0-System Public

    Python

  3. fims9000/XAI-CausalLayered fims9000/XAI-CausalLayered Public

    A research framework for next-generation Explainable AI (XAI 2.0) based on multi-layer neuro-symbolic architectures. The project advances from post-hoc explanations toward embedded causal interpret…

    Python 1

  4. fims9000/Trust-ADE fims9000/Trust-ADE Public

    Trust-ADE (Trust Assessment through Dynamic Explainability) is a comprehensive protocol for quantitative trust assessment of artificial intelligence systems, based on the scientific research "From …

    Python

  5. fims9000/XAI-2.0-SHAP-regularized-ANFIS fims9000/XAI-2.0-SHAP-regularized-ANFIS Public

    Implementation of Explainable AI 2.0: SHAP-regularized ANFIS for interpretable and robust machine learning. Combines neuro-fuzzy systems with SHAP values to enhance explainability, feature attribut…

    Python 1