The lecturer has the primary role in the educational process in higher education institutions, he has the greatest role in motivating students and arousing their motivation towards learning. To achieve this, his educational plan must include clear goals, organized, flexible and attractive educational procedures, and various educational activities and tools, and encourage them to apply self-evaluation.

This article proposes an approach to develop an artificial intelligence (AI) deep learning robot for simulating a lecturer in Higher Education, create an interactive and highly realistic teaching experience that significantly enhances student learning outcomes is the main goal in this article.

The simulation incorporates cutting-edge natural language processing (NLP) algorithms, advanced deep learning models, gesture recognition, and personalization technique, it includes sophisticated classroom management capabilities, continuous learning mechanisms, and real-time feedback mechanisms.

The proposed system collects data from various sources, including recorded lectures, textbooks, and research papers, to train the robot.

The AI deep learning robot simulation aims to revolutionize higher education by offering a dynamic and engaging learning environment, that is through leveraging its advanced NLP algorithms, the simulation can understand and respond to students' questions and concerns in a natural and conversational manner.

The deep learning models enable the simulation to adapt its teaching style and content to suit individual student needs, fostering personalized learning experiences.

This article contributes to the field of educational technology by showcasing the capabilities of AI and deep learning in creating realistic and effective lecturer simulations.

The findings highlight the importance of incorporating advanced technologies into higher education to optimize the learning experience for students. Future research will focus on refining the simulation's algorithms, expanding its subject matter expertise, and conducting larger-scale studies to further validate its effectiveness.