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@neshatsh
neshatsh
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Neshat Sharbatdar neshatsh

Data Scientist/ ML Engineer - M.Sc. from the University of Waterloo, with a Computer Science background.

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  1. RiskLens RiskLens Public

    Agentic AI risk intelligence system for banks — multi-agent LangGraph pipeline monitoring credit, market, and operational risk with Basel III compliance and human-in-the-loop review

    Python

  2. DocuLens-RAG-platform DocuLens-RAG-platform Public

    Production-grade RAG platform for legal, financial & insurance documents - BERT reranking, VLM extraction, FastAPI, Docker, ChromaDB

    Python

  3. Financial-Fraud-Detection-System Financial-Fraud-Detection-System Public

    Fraud detection on 590K transactions — AutoEncoder anomaly detection vs. XGBoost/LightGBM ensembles, with SHAP explainability and MLflow tracking.

    Jupyter Notebook

  4. Customer-Churn-Prediction-Pytorch Customer-Churn-Prediction-Pytorch Public

    End-to-end customer churn prediction using PyTorch, XGBoost, SHAP, Lime, Optuna & MLflow — with business ROI analysis and FastAPI serving.

    Jupyter Notebook

  5. Clickbait-Spoiling Clickbait-Spoiling Public

    This project addresses the two subtasks from the SemEval-2023 Clickbait Spoiling Challenge: Task 1: Spoiler Type Classification and Task 2: Spoiler Generation

    Jupyter Notebook

  6. Spotify-Heterogeneous-GNN-Recommender Spotify-Heterogeneous-GNN-Recommender Public

    Heterogeneous graph neural network music recommender with Playlist-Track-Artist relations. Extends Stanford CS224W article with 5 GNN architectures.

    Jupyter Notebook 1

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