Special Session 5

Advancing Higher Education Research through Industry 4.0, Deep Learning, NLP, and Large Language Models

This special session is organised and supported by  the following educational partner

University of Anbar, Iraq

Session Chair:

  • Prof Dr Mushtak Talib Salih Nada Al-Ouqaili

Session Co-Chair:

  • Prof Dr Salah A. Salman
  • Assist Prof Dr Ahmed J. Aljaaf




The rapid integration of new technologies continues to drive the evolution of higher education research. With the advent of Industry 4.0 and the incredible advancements in Deep Learning, Natural Language Processing, and epically Large Language Models LLM, exciting new opportunities have opened for enhancing academic research methods and results. This special session aims to promote a better understanding of the impact of Industry 4.0 on higher education research, and to showcase the challenges and potential of using Machine Learning/Deep Learning, NLP and LLM to solve research questions and facilitate data analysis and optimise decision processes within the higher education industry. This special session welcomes original research articles, case studies and reviews that address a wide range of topics related the application of Industry 4.0 technologies, NLP and LLM as well as other AI supported technologies to support higher education.


Therefore, this special session invites authors to submit high-quality research papers on  topics which include (but are not limited to) the following:

  • AI and Deep learning applications on campus operations.
  • AI and deep learning to improve educational content.
  • Natural Language Processing for information extraction and understanding.
  • Leveraging LLM and AI techniques to handle global challenges.
  • Natural Language Processing for educational content analysis.
  • AI and Predictive analytics in higher education.
  • AI solutions and Industry 4.0 in research for higher education.
  • Virtual and Augmented Reality in learning and research methods.
  • Image classification and recognition using AI and machine learning.
  • AI algorithms to improve big data analytics.
  • Enhanced models for Cloud, IoT, and Smart Traffic systems using AI.

Paper Submission:

Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system.