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IliassSjm/README.md

Iliass Sijelmassi

Visiting Student Researcher at Stanford University (ML for cardiology) — MSc Data Science & AI, École Polytechnique & HEC Paris. Interested in quantitative research and machine learning on messy real-world data: markets, clinical records, tracking feeds.

Selected work

  • crypto-perps-alpha — cross-sectional ML alpha on 411 crypto perpetual futures; ranked 1st of 13 teams on out-of-sample Sharpe (HEC ML for Financial Markets), with honest alpha-decay and cost analysis.
  • cognitive-alpha — per-pass decision quality on 2022 World Cup tracking data: trained Expected Threat, Spearman-style pitch control, scout-validated optimality gap.
  • Research paper (in progress at Stanford): predicting severe pericardial tamponade after cardiac surgery — pdf.

iliasssijelmassi.com · iliass.sijelmassi-idrissi@polytechnique.edu

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  1. crypto-perps-alpha crypto-perps-alpha Public

    Cross-sectional ML alpha on crypto perpetual futures — Ridge+XGBoost under rolling walk-forward, alpha-decay and transaction-cost analysis

    Python

  2. options-market-maker-sim options-market-maker-sim Public

    Market Making Simulator for European Options

    Jupyter Notebook

  3. cognitive-alpha cognitive-alpha Public

    Spatial decision-making analytics on 2022 World Cup tracking data — pitch control, trained xT, per-pass decision quality (Streamlit)

    Python