I am an aspiring AI researcher with a strong background in artificial intelligence, machine learning, and computer vision. I am particularly interested in predictive analysis, medical imaging, agronomy applications, and explainable AI (XAI). I am currently seeking PhD or MSc opportunities where I can further develop my expertise and contribute to innovative research that solves real-world problems.

I am seeking a PhD or MSc position where I can leverage my background in AI, machine learning, and computer vision to contribute to impactful research and advance my skills in a challenging academic environment.

• B.Sc. in Electronics & Telecommunication Engineering
  Rajshahi University of Engineering & Technology, Bangladesh
  CGPA: 3.10/4.00
  Year: 2019-2024

• Research Assistant
  Qatar University Machine Learning Group
  September 2024 - Present

  • Focus areas: Computer Vision, Predictive Analysis, Segmentation, and Natural Language Processing (NLP).

• Machine Learning Engineer Intern
  Anwar Technologies
  July 2024 - September 2024

  • Developed an Optical Character Recognition (OCR) system and worked on real-world applications of ML.

• Programming Languages: C, C++, Python, JavaScript, HTML, CSS
• Frameworks/Libraries: PyTorch, TensorFlow, Keras, Scikit-learn
• AI/ML Techniques: CNN, RNN, Transformers, Attention Mechanism, Explainable AI (XAI), GAN
• Databases: MySQL, MongoDB
• Version Control: Git, GitHub
• Development Tools: Google Colab, Kaggle, VS Code, MATLAB, Codeblocks, Heroku, Netlify

1. An End-to-End Lightweight Multi-Scale CNN for the Classification of Lung and Colon Cancer with XAI Integration

   • Developed a custom lightweight CNN model with integrated Grad-CAM and SHAP for interpretability.
   • Publication Link

2. Prediction of Fetal Brain Gestational Age Using Multi-Head Attention with Xception

   • Created a model using Xception with multi-head attention for accurate gestational age prediction.
   • Publication Link

1. Brain Tumor Detection Using Feature Extraction and Ensemble Learning with a Smart Web Application

   • Built a brain tumor detection model integrating feature extraction, ensemble learning, and web application support.
   • Publication Link

2. Early Prediction of Crop Yield in Bangladesh Using Ensemble Learning (Accepted)

   • Created a predictive model for crop yield forecasting using ensemble learning techniques.

• Explainable Automated Brain Tumor Detection Using CNN
  • Developed a CNN model for brain tumor classification with Grad-CAM for interpretability.
  • Chapter Link

• Email: [email protected]
• Phone: +8801817226718
• LinkedIn: linkedin.com/in/asif-hasan-6865101a9
• ResearchGate: researchgate.net/profile/Mohammad-Hasan225

Thank you for visiting my profile! Please feel free to contact me if you are interested in collaboration, research opportunities, or learning more about my work.