Machine Learning Engineer specializing in Computer Vision and Deep Learning, with a focus on healthcare applications. Currently working as a Computer Vision Developer at The Disrupt Lab, developing innovative solutions for workplace safety and monitoring.

🎓 BS Computer Science | University of Peshawar | CGPA: 3.54/4.0

• Major: Computer Science
• Minor: Artificial Intelligence

• Optimizing Reinforcement Learning Agents in Games (Computer Animation and Virtual Worlds, Submitted)
• Alzheimer's Disease Detection using Deep CNN (Pre-Print)
• Diabetic Retinopathy Detection Framework (Bachelor Thesis)

• Computer Vision Developer @ The Disrupt Lab (2024-Present)

  • Labor behavior detection
  • PPE monitoring for Unilever
  • Emergency situation tracking
  • Workplace safety systems

• Machine Learning Intern @ NCAI UET-Peshawar (2022-2023)

  • Drowsiness detection (83% accuracy)
  • Image clustering
  • Pose estimation systems

{
    "Languages": ["Python", "R", "SQL", "HTML", "CSS"],
    "ML/DL": ["TensorFlow", "PyTorch", "Keras", "Scikit-learn"],
    "Computer Vision": ["OpenCV", "Ultralytics", "Roboflow"],
    "Web Frameworks": ["Flask","Django", "Streamlit", "Gradio", "Dash"],
    "Cloud": ["AWS", "Azure"],
    "Hardware": ["Jetson Nano", "Raspberry Pi"]
    "Tools": ["Git", "Linux", "Tableau", "Power BI"]
}

• Machine Learning Specialization (Deeplearning.ai)
• Deep Learning Specialization (Deeplearning.ai)
• Practical Data Science on AWS Cloud
• Meta Back-End Developer
• Google Advance Data Analytics Professional Certificate

1. Alzheimer's Disease Classification

   • Custom neural network with 99.99% accuracy
   • Ternary classification system
   • Comprehensive Kaggle dataset

2. Brain Tumor Classification

   • Custom CNN architecture
   • MRI image processing
   • Advanced medical imaging analysis

3. Urdu Language Audio Classification

   • Audio preprocessing pipeline
   • Machine learning classification model
   • Custom dataset development

⭐️ From Muhammad-237