About me

I am a proactive Ph.D. candidate in Computer Science. My research aims to address complex cybersecurity issues, such as Penetration Testing and Vulnerable Code Detection, using innovative algorithms and computational techniques such as Reinforcement Learning, Natural Language Processing (NLP), and Graph Neural Networks. I have also worked on projects related to Optical Character Recognition (OCR), Few-shot learning, and graph-based recommendation engines. As a researcher, I make it a priority to remain updated on business trends and apply my knowledge to practical applications.

Skills

• AI and ML:
  • Reinforcement Learning (e.g., Q-Learning, Deep Q-Networks, Actor-Critic Models)
  • Natural Language Processing
  • Graph Neural Networks (e.g., GCN, GAT, GIN)
  • Few-shot Learning (e.g. Prototypical Networks, Siamese Networks, MAML)
• Programming Languages: Python, Java, SQL, JavaScript, C/C++
• Python Libraries: Pandas, NumPy, SciPy
• ML Frameworks: PyTorch, TensorFlow
• Graph Neural Network Libraries: DGL, PyTorch Geometric
• Data visualization tools: Tableau, Matplotlib