Islam Akef Ebeid, PhD

Assistant Professor, TWU Division of Computer Science

Contact

Office: MCL 412
Email: iebeid@twu.edu
Website

Biography

Islam Akef Ebeid, PhD, is an assistant professor of computer science at Texas Woman's University, where he brings a unique blend of academic rigor and practical experience to his research and teaching. His career is marked by a commitment to data-driven discovery, focusing on the intersection of artificial intelligence, information science, and biomedical informatics.

Ebeid is dedicated to fostering a deep understanding of data science concepts. He has developed and taught courses including Introduction to Data Mining, Data Warehousing, Foundations of Data Science, Fundamentals of Informatics, and Statistical Programming.

Education

BS, Electrical and Computer Engineering, Ain Shams University in Cairo, Egypt
MS, Computer and Information Science, University of Arkansas at Little Rock
PhD, Computer and Information Science, University of Arkansas at Little Rock

Research interests

• Artificial intelligence
• Data quality, storage and mining
• Natural language processing and information retrieval
• Graph theory and network science
• Biomedical informatics and network biology
• Human-computer interaction and eye-tracking

Teaching interests

• Data science
• Algorithms
• Programming
• Database

Service interests

• Developing data science education for underrepresented groups
• Promoting ethical development of artificial intelligence
• Researching sustainable computing

Professional experience

Ebeid's worked at Intel Inc., AbbVie and the Texas Advanced Computing Center

Research Interests

• Artificial intelligence
• Information science
• Data mining
• Network science
• Database and information retrieval
• Data quality in artificial intelligence - investigates the critical role of data quality in training artificial intelligence models, particularly in scientific domains where data integrity is essential.
• Biomedical data integration - develops innovative techniques for integrating large biomedical datasets extracted from digital libraries with omics datasets using the knowledge graph data model.
• Graph-based representation learning - develops efficient graph-based representation learning techniques to leverage the power of integrated datasets for applications in information retrieval, search engines, and entity matching.

Publications

Ebeid has been published in Scientometrics, Scientific Data, KDD and the iConference. He is a peer reviewer for SIGKDD and the Journal of Natural Language Engineering.

Awards

• Best Short Paper Award at the ACM SIGCHI Symposium on Eye Tracking in 2019
• Outstanding Doctoral Graduate Award from UALR in 2022
• Professional Development Award from UT Austin in 2019

Organizations

• Association for Computing Machinery
• Institute of Electrical and Electronics Engineers
• American Association of University Professors