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Работа из дома
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Работа из дома
4 followers · 8 following
  • Dubna State University

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Achievement: Pull SharkAchievement: Quickdraw

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fims9000/README.md

Yuri Trofimov

AI Researcher | Explainable AI (XAI) | Hybrid Neuro-Symbolic Systems | AI for Sustainable Development

Working at the frontier of Artificial Intelligence:

  • Building transparent & interpretable ML
  • Designing hybrid neuro-fuzzy & symbolic architectures
  • Applying AI to medicine, sustainability & decision support systems

💡 Bridging deep technical AI with real-world impact.

🔬 Research & Expertise

  • Explainable & Interpretable AI (XAI)
  • Hybrid Neuro-Fuzzy & Neuro-Symbolic Systems
  • Decision Support Systems (medicine, sustainability, ecological risk)
  • Knowledge Representation & Reasoning
  • GeoAI & Spatial ML for Sustainability

⚙️ Technical Stack

  • Languages: Python, C++, R, MATLAB
  • ML/DL: PyTorch, TensorFlow, Keras, Scikit-learn
  • XAI: SHAP, LIME, Captum, Alibi Explain, InterpretML
  • Data & MLOps: SQL, NoSQL, Neo4j, Docker, DVC, MLflow, Airflow
  • GIS: QGIS, ArcGIS, GeoPandas, Rasterio, Shapely, Remote Sensing

📂 GitHub Projects

  • XAI Frameworks – interpretable ML and custom explainers
  • Hybrid Neuro-Fuzzy Systems – DSS prototypes
  • Medical DSS – AI models for preventive healthcare
  • GeoAI for Sustainability – GIS + ML for ecological risk
  • Knowledge Graph + ML Pipelines – hybrid reasoning + ML

🎯 Current Focus

  • Next-gen interpretable AI frameworks
  • Neuro-symbolic architectures for trustable AI
  • AI for sustainability & medicine
  • Systemic & theoretical foundations of XAI

📫 Contacts

Pinned Loading

  1. XAI-2.0-SHAP-regularized-ANFIS 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

  2. Trust-ADE 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

  3. XAI-CausalLayered 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. CAS_ISIC CAS_ISIC Public

    Python

  5. SYNT_ISIC SYNT_ISIC Public

    Графическое приложение для синтетики ISIC на DDPM (UNet2D) с Time-SHAP — временной атрибуцией важности по шагам денойзинга — и каузальной валидацией через контрафактуальные интервенции (noise/blur/…

    Python 1