B.Sc. in Computer Engineering
Philadelphia University, Jordan

M.S. in MIS
The Arab Academy, Jordan

Ph.D. in Computer Science
Universiti Utara Malaysia (UUM), Malaysia

• Python Programming

• Fundamentals of Computer Science using Java

• Introduction to Unix/Linux

• Computer Organization and Programming

• Computer Organization and Architecture

• Computer Operating Systems

• Computer Systems

• Research and Technology

• Senior Research in Computer Science

• Senior Capstone

Dr. Baha Ihnaini is an Assistant Professor of Computer Science at Wenzhou-Kean University, specializing in Artificial Intelligence with a particular focus on Natural Language Processing (NLP). He received his Ph.D. in Computer Science from Universiti Utara Malaysia (UUM) in 2019, his M.Sc. in Management Information Systems from The Arab Academy for Banking and Financial Sciences, and his B.Sc. in Computer Engineering from Philadelphia University.

Before joining Wenzhou-Kean University, he worked as a lecturer at Al Khawarizmi International College in Abu Dhabi and as a Research Officer at the InterNetWorks Research Lab at Universiti Utara Malaysia. His current research focuses on Artificial Intelligence, Machine Learning, Deep Learning, Large Language Models, Natural Language Processing, Multimodal Learning, Computer Vision, Explainable AI, and AI applications in healthcare, education, and social media.

Dr. Ihnaini actively supervises student research leading to journal and conference publications and AI competitions. He also contributes to university academic service as Chair of the Grievance Committee and as a member of the Curriculum Committee, Search Committee, and Final Thesis Project Committee. He is also the Founder and Director of the AI Student Club and the WKU Institute of Advanced NLP.

• Artificial Intelligence and Neural Networks

• Machine Learning and Deep Learning

• Large Language Models

• Natural Language Processing

• Multimodal Learning

• Computer Vision

• Explainable Artificial Intelligence

• AI Applications in Healthcare, Education, and Social Media

• Sentiment Analysis

1. Ihnaini, B., Zeng, X., Yan, H., Fang, F., & Sangi, A. R. (2025). Leveraging Large Language Models for Departmental Classification of Medical Records. Applied Sciences, 15(12), 6525.

2. Ihnaini, B., Li, J., & Yu, Z. (2025). Evaluating Large Language Models for Depression Detection in Text: A Comparative Analysis. International Conference on Neural Information Processing (ICONIP). Springer.

3. Cheng, Z., Wu, Y., Li, Y., Cai, L., & Ihnaini, B. (2025). A Comprehensive Review of Explainable Artificial Intelligence (XAI) in Computer Vision. Sensors, 25(13), 4166.

4. Bowen, L., Zhuoqing, Z., Hengyu, Z., et al. (2025). Improving Negative Rejection Ability in Language Models: A Review of Fine-Tuned LLMs, RAG, and RAFT. Journal of King Saud University – Computer and Information Sciences.

5. Ihnaini, B., Deng, Y., He, Y., Geng, L., & Xu, J. (2025). Detection of Alzheimer’s Disease Using Fine-Tuned Large Language Models. Forum for Linguistic Studies, 7(8), 373–384.

6. Ihnaini, B., & Xu, J. (2024). The Moral Foundations Weibo Corpus. Proceedings of the 1st Workshop on NLP for Science (NLP4Science) at ACL 2024, 155–165.

7. Ihnaini, B., Abuhaija, B., Mills, E. A., & Mahmuddin, M. (2024). Semantic Similarity on Multimodal Data: A Comprehensive Survey with Applications. Journal of King Saud University–Computer and Information Sciences, 102263.

8. Ihnaini, B., & Mahmuddin, M. (2020). Valence Shifter Rules for Arabic Sentiment Analysis, International Journal of Multi-disciplinary Sciences and Advanced Technology, 1 (2), 167-184.

9. Ihnaini, B., & Mahmuddin, M. (2020). Phonology Matching Algorithm to Construct Palestinian Sentiment Lexicon, International Journal of Multidisciplinary Sciences and Advanced Technology, 1 (3), 35-51.

10. Ihnaini, B., & Mahmuddin, M. (2018). Lexicon-Based Sentiment Analysis of Arabic Tweets: A Survey. Journal of Engineering and Applied Sciences, 13(17), 7313-7322.

11. Ihnaini, B., & Mahmuddin, M. (2018). An Expandable and Up-to-Date Lexicon for Sentiment Analysis of Arabic Tweets, COMPUSOFT, 7 (11), 2884-2891.