fazila malik | Optimization techniques | Excellence in Innovation

Ms. fazila malik ,Optimization techniques, Excellence in Innovation

Ms. fazila malik at  Iqra international university islamabad H9 campus, Pakistan

Author Profile

Scopus Profile

🌟Summary

Fazila Malik is a dedicated computer science lecturer with expertise in artificial intelligence, data mining, and natural language processing. She holds two master’s degrees in computer science from COMSATS University Islamabad, where she was a batch topper during her MS studies. Fazila has experience teaching at various universities and conducting remote research. Her technical skills include Python, C++, Java, TensorFlow, Scikit-learn, and Latex. Fazila has contributed to multiple research projects and has several publications in reputable journals.

🎓Education

  • Master of Sciences (MS) in Computer Sciences, COMSATS University Islamabad (CUI), Attock Campus, Pakistan (2020-2022) | CGPA: 3.8/4.0 (Batch Topper)
  • Master of Computer Sciences, COMSATS University Islamabad (CUI), Attock Campus, Pakistan (2017-2019) | CGPA: 3.1/4.0

💼 Professional Experience

  • Lecturer, Iqra University Islamabad, H9 Campus (September 2023 – Present)
  • Lecturer (Contract), University of Education, Attock Campus (September 2022 – August 2023)
  • Research Experience (Remotely) (January 2020 – Present)

🔬 Research Interests

My research interests lie at the intersection of artificial intelligence and data science, with a focus on Natural Language Processing (NLP), evolutionary algorithms, and neural networks. I am particularly passionate about developing innovative methods to analyze and interpret complex data patterns. My work in NLP involves creating models for text analysis, sentiment detection, and textual similarities extraction, leveraging machine learning and deep learning techniques. Additionally, I am intrigued by the potential of evolutionary algorithms to solve optimization problems and enhance clustering methods. My ongoing projects explore social media analysis and pattern mining, aiming to uncover hidden insights and contribute to advancements in the field of data science.

📖 Publication Top Noted

Machine-Learning-Based DDoS Attack Detection Using Mutual Information and Random Forest Feature Importance Method

    • Authors: Alduailij, M.; Khan, Q.W.; Tahir, M.; …; Alduailij, M.; Malik, F.
    • Journal: Symmetry
    • Volume: 14
    • Issue: 6
    • Pages: 1095
    • Year: 2022

A Novel Hybrid Clustering Approach Based on Black Hole Algorithm for Document Clustering

    • Authors: Malik, F.; Khan, S.; Rizwan, A.; Atteia, G.; Samee, N.A.
    • Journal: IEEE Access
    • Volume: 10
    • Pages: 97310–97326
    • Year: 2022