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wajeeha-sajid/README.md

👩‍💻 Wajeeha Sajid

🎓 MS in Electrical and Computer Engineering
💡 Deep Learning, Machine Learning & Computational Intelligence
🧬 Researching Disease Detection via Gene Expression Data
🖥️ Background in GPU Computing & Medical Imaging
🔍 Open to Research, RA, and AI-related Opportunities

📚 About Me

I’m an Electrical and Computer Engineer with a growing interest in applying AI techniques to real-world problems — especially in healthcare and life sciences. My academic journey has equipped me with hands-on experience in deep learning, machine learning, and computational intelligence, and I’m currently exploring gene expression data for disease prediction as part of my master's thesis. I'm passionate about learning, building, and contributing to AI-driven solutions that make a meaningful impact.

🎓 Education

  • MS in Electrical and Computer Engineering
    Air University, Pakistan
    *CGPA: 3.64 *

  • BS in Electrical Engineering
    Graduated: 2021

🧪 Research & Thesis

  • 🧬 Thesis
    “Detection of Diseases Using Gene Expression Data with Deep Learning and Machine Learning Techniques”
    Focused on applying modern AI models to identify disease patterns from high-dimensional genetic datasets.

🧠 Research Interests

  • Gene-Based Disease Prediction using ML/DL
  • Deep Learning for Healthcare & Bioinformatics
  • Computational Intelligence
  • Data-Driven Diagnostics
  • Image Processing
  • GPU Computing

🛠️ Technical Skills

  • Languages: Python, C/C++, MATLAB
  • Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn
  • Tools: Git, Jupyter, Google Colab, CUDA, VS Code
  • Concepts: CNNs, Feature Selection, Transfer Learning, Dimensionality Reduction

📁 Projects

🌐 Let's Connect

“Turning genetic data into intelligent diagnostics — one model at a time.”

Pinned Loading

  1. Tech-Stock-prediction-LSTM Tech-Stock-prediction-LSTM Public

    Time-series forecasting with deep learning to predict stock prices of major tech companies including Apple, Google, Microsoft, and Amazon.

    Jupyter Notebook

  2. crop-yield-prediction-ml-dl crop-yield-prediction-ml-dl Public

    Hands-on implementation of multiple AI models (RF, XGBoost, CNN, LSTM) for crop yield prediction. Demonstrates preprocessing, model evaluation, and visualization.

    Jupyter Notebook

  3. tourism-hypotheses-ml tourism-hypotheses-ml Public

    Machine learning and deep learning models applied to validate hypotheses on tourist satisfaction, loyalty, and destination image in behavioral research.

    Jupyter Notebook

  4. wajeeha-sajid wajeeha-sajid Public