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Shravani018/README.md

Hi, I'm Shravani

Master's student in Applied Data Science at Frankfurt School of Finance & Management. With one year of experience as a Data Scientist in fintech, I have worked across automation, analytics, and machine learning. My work involved building automation pipelines and executive dashboards, as well as developing ML-driven solutions such as OCR-based KYC workflows, market sentiment analysis, and customer segmentation models.

🔍 Current Focus

Researching explainable AI and model interpretability frameworks, with an emphasis on fairness-aware approaches for building transparent ML systems in regulated financial environments.

🖥️ Tech Stack

Programming & Data

Python R SQL

Analytics & Business Intelligence

Power BI Tableau Streamlit

Data Engineering & Automation

Apache Spark Apache Hadoop Databricks Selenium n8n

Cloud & Development Tools

AWS Docker

📫 Let's Connect

Email

Open to collaborations, discussions on Explainable ML & data science, or just a friendly chat about AI ethics!

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  1. interpreting-transformer-hallucinations interpreting-transformer-hallucinations Public

    Mechanistic interpretability of transformer hallucinations via attention flow, residual stream geometry, and head-level attribution analysis.

    HTML

  2. xai-credit-risk-analysis xai-credit-risk-analysis Public

    A credit risk prediction project that compares multiple machine learning models and applies explainable AI methods to interpret and analyze model decisions.

    Jupyter Notebook

  3. deepfractals deepfractals Public

    Visualizing deep learning dynamics as fractals in the complex plane

    Python

  4. llm-audit-bench llm-audit-bench Public

    A modular pipeline that audits 5 small HuggingFace LLMs across transparency, fairness, robustness, explainability, and privacy. Produces per-pillar scores across the 5 pillars of AI trustworthiness.

    Jupyter Notebook

  5. Decoding-ESG-Measuring-Clarity-and-Greenwashing-in-Corporate-Disclosures Decoding-ESG-Measuring-Clarity-and-Greenwashing-in-Corporate-Disclosures Public

    Analyzes 10 years of SEC 10-K filings from S&P 50 firms using NLP and Guided LDA to evaluate ESG communication clarity and detect greenwashing. Introduces the Greenwashing Risk Index (GRI) to measu…

    Jupyter Notebook 1 1

  6. tennis-elo-probabilistic-model tennis-elo-probabilistic-model Public

    End-to-end probabilistic tennis modeling pipeline using Elo ratings and Monte Carlo simulation.

    Jupyter Notebook