Dr. Al-Mubaid received his Ph.D. degree in Computer Science from University of Texas at Dallas (Dallas, Texas, USA) with distinguished dissertation award in 2000. He is currently an Associate professor of Computer Science and Computer Information Systems and Program Chair of Computer Information Systems at the University of Houston-Clear Lake, Houston, Texas, USA. Dr. Al-Mubaid’s main research interests are centered around natural language processing and bioinformatics and include data mining, machine learning, and biomedical text mining. Dr. Al-Mubaid is one of few people working to prove in the virtue of the context-based approach to natural language processing (NLP). He developed several algorithms and systems to prove the point including: detecting and correcting context-based errors, word prediction, word classification, text categorization and document clustering. He devised a (new) way of learning from ‘good’ versus ‘bad’ features in context-based NLP. He is currently writing a book on “Natural Language Processing: Context-based Approach”. Moreover, Dr. Al-Mubaid, with his students, developed an efficient method for measuring semantic similarity of biomedical terms using multiple ontologies within the UMLS framework. That similarity measure has been developed (by interested researchers and volunteers) in CPAN and available freely through: UMLS-Similarity-0.17 > UMLS::Similarity::nam: http://search.cpan.org/~btmcinnes/UMLS-Similarity-0.17/lib/UMLS/Similarity/nam.pm. Besides, he has research projects and publications in learning and educational based research (e.g. Self-regulated learning). He serves as program chair and committee member of many regional and international conferences. He also serves in the editorial, technical board and reviewer for several journals. He is in the board of directors of ISCA, a member in ACM, IEEE, IEEE computer society, ACL, and other professional organizations. His teaching experience includes large number of undergraduate and graduate computer science courses.

See his publications.