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1 follower · 7 following
  • Independent Researcher / Unemployed
  • Lahore, Pakistan
  • 20:25 (UTC +05:00)
  • X @Seemi_Rauf

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S33mi/README.md

Hi there 👋

I'm a data enthusiast and researcher | Turning past work into open, reproducible projects

"Just trying to do great things" — one simulation, notebook, and optimization at a time.

🔧 Background & Key Projects

Data Analysis & Machine Learning

  • Credit Fraud Analytics — Analysis of credit card transaction data for fraud detection using anomaly detection techniques → credit-fraud-analytics (MIT)

  • Know Your Style — Fashion-MNIST EDA + CNN classification (~90-92% accuracy) → know-your-style (MIT)

  • Financial News Mining — Sentiment analysis & stock correlation → financial-news-mining (MIT)

  • Machine Learning Journey — Coursework implementations (CS-567, CS-667) and experiments → machine-learning-journey (MIT)

  • Paper Reimplementations — Previously reimplemented research papers during my PhD. Starting with DataPrep.EDA EDA tools → paper-reimplementations (MIT)

Systems & Optimization

  • Data Center Networks — TCP performance simulations using NS-3 → research-development-data-center-networks (BSD-2-Clause)

  • IoT Routing Simulations — RPL-based experiments in Contiki-Cooja (energy, latency analysis, modified code & setups) → iot-routing-contiki (BSD-3-Clause)

  • Intelligent 2D Packing Optimization — Heuristics & metaheuristics (Genetic Algorithm, Simulated Annealing, Cuckoo Search, NFP, Bottom-Left-Fill) for irregular nesting → intelligent-optimization (MIT)

Finance & Business Python

Other Explorations

More coming soon: JP Morgan python training for Bussiness Analysts (publicly available now), more on paper reimplementations, and data analysis notebooks.

🔗 Learning & External Training

🛠️ Skills Snapshot

Python · C++ · C basics · MATLAB · Pandas · Scikit-learn · TensorFlow/Keras · Data Visualization · Machine Learning · Deep Learning · Data Analysis · Jupyter · Anomaly Detection · Sentiment Analysis · Tableaue · NS-3 · Contiki/Cooja · Network Simulation · Optimization Algorithms

🚀 Currently Exploring

Bridging networking/simulations with data pipelines (publicaly avaiable now) , fraud detection, and frontier AI (daily Grok user & prompt tinkerer).

  • Deep Learning & LLMs
  • Prompt engineering with Grok
  • Real-world applications in fintech, sustainability, and fashion analytics

Fun unrelated note: Professionally bad at tennis 🎾 → casual thoughts on X: @Seemi_Rauf

Open to Data Analyst, Business Analyst, or ML-related opportunities.

📫 X: @Seemi_Rauf

Feel free to star, fork, or reach out — happy to collaborate, let's build something useful! 🌟

Pinned Loading

  1. credit-fraud-analytics credit-fraud-analytics Public

    Anomaly detection for credit card fraud on imbalanced transaction data - experiments with Isolation Forest and more

    Jupyter Notebook

  2. know-your-style know-your-style Public

    Fashion clothing analysis — Classification and exploratory data analysis on fashion/clothing products — categories, prices, trends, using open datasets

    Jupyter Notebook

  3. jpmc-python-training-notes jpmc-python-training-notes Public

    Forked from jpmorganchase/python-training

    Forked notebooks from JPMorgan Chases's Python training for business analysts and traders

    Jupyter Notebook

  4. machine-learning-journey machine-learning-journey Public

    Implementations & Notes from CS-567 Machine Learning & CS-667 Advanced Machine Learning (Deep Learning) during my MPhil @PUCIT

    Jupyter Notebook

  5. daily-motivation-tennis-fun daily-motivation-tennis-fun Public

    Fun daily agent: motivational quotes + tennis tips (Grok-inspired)

    Jupyter Notebook

  6. powerbi-tableau-dashboards powerbi-tableau-dashboards Public

    Power BI & Tableau Dashboards. Turning raw data into actionable insights with Python, Power BI & Tableau. Tableau (calculated fields, parameters, dashboard actions)