Dr. Banitaan is currently the director and associate professor at the Mathematics, Computer Science, and Software Engineering department at the University of Detroit Mercy. His research interests include software engineering and data mining. He is a member of the Association for Computing Machinery (ACM), a member of the Institute of Electrical and Electronic Engineers (IEEE), and a member of the IEEE Computer Society. He received a B.S. degree in Computer Science from Yarmouk University, an M.S. degree in Computer and Information Sciences from Yarmouk University, and a Ph.D. degree in Computer Science from North Dakota State University. He taught for five years at the University of Nizwa, Oman. He joined the University of Detroit Mercy in 2013.

Curriculum Vitae, Google Scholar

UDM Mission Statement University of Detroit Mercy, a Catholic university in the Jesuit and Mercy traditions, exists to provide excellent student-centered undergraduate and graduate education in an urban context. A UDM education seeks to integrate the intellectual, spiritual, ethical and social development of our students.

My Courses

CSSE-1710: Intro To Programming I

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CSSE-1720: Intro To Programming II

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CSSE-2130: Java

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CSSE-4490: Operating Systems

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CSSE-4550: Introduction to Artificial Intelligence

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CSSE-5610: Software Testing

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CSSE-5250: Software Design Techniques

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CSSE-5480: Artificial Intelligence

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CSSE-4610: Data Mining

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CSSE-5500: Software Quality Engineering

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Emotion Classification

With the rapid growth of user generated content on microblogging sites such as Twitter, there is a high demand to develop tools for identifying people's emotions expressed in text. Emotion classification can give a very good insight to how people truly feel about a given subject. There are six emotions that are universally recognizable namely fear, disgust, excitement, sadness, happiness, and anger. A labeled training set is needed to build a predictive model. The time required to annotate a training set is a major overhead of the emotion classification task. I am looking to propose different approaches to conducting automatic annotation and classification of tweets.

Class Decomposition and its Application to Cancer Classification

The DNA microarray technology has enabled scientists to measure the expression levels of large number of genes simultaneously in a microarray experiment. This technology has been widely used in medical diagnosis such as cancer classification. The purpose of this study is to develop a method for classifying cancers using machine learning techniques. Although cancer classification has improved over the last decade, there is still a need to improve the classification performance. The main contribution is to apply class decomposition as a preprocessing step to improve the classification accuracy and reduce the effect of noisy data. Class decomposition works by dividing each class into clusters, and by relabeling instances belonging to each cluster with a new class.

Publications List

  1. Kevin Daimi, Shadi Banitaan, Kathy Liszka, "Examining the Performance of Java Static Analyzers", in the 2013 International Conference on Software Engineering Research and Practice (SERP'13), Las Vegas, Nevada, USA.
  2. Shadi Banitaan and Mamdouh Alenezi, "TRAM: An Approach for Assigning Bug Reports using their Metadata", in the third International Conference on Communications and Information Technology (ICCIT 2013), Beirut, Lebanon.
  3. Shadi Banitaan, Mamdouh Alenezi, Kendall Nygard, and Kenneth Magel, "Towards Test Focus Selection for Integration Testing Using Method Level Software Metrics", In the 10th International Conference on Information Technology: New Generations (ITNG Software Testing 2013), Las Vegas, Nevada, USA.
  4. Saeed Salem, Shadi Banitaan, Ibrahim Aljarah and Rami Alroobi , "Mining MaximalHomogeneous Subnetworks using Protein Interaction Networks and Gene Profiles", In the 4th international conference on Bioinformatics and Computational Biology (BICoB) 2012, Las Vegas, Nevada, USA
  5. Saeed Salem, Rami Alroobi, Shadi Banitaan, Loqmane Seridi, Ibrahim Aljarah and James Brewer. “Improving Functional Modules Discovery by Enriching Interaction Networks with Gene Profiles”, Current Bioinformatics, Volume 7, 4 Issues, 2012.
  6. David Horvath, Victor Weigman, Saeed Salem and Shadi Banitaan , “PacBio Sequencing and Assembly of Complex BAC Clones ”, In the Plant and Animal Genome XX Conference January 2012, San Diego, California, USA.
  7. Saeed Salem, Shadi Banitaan, Ibrahim Aljarah, James Brewer and Rami Alroobi, “Discovering Communities in Social Networks using Topology and Attributes”, in Proceedings of the International Conference on Machine Learning and Applications (ICMLA’11), December 2011, Honolulu , Hawaii, USA.
  8. Ibrahim Aljarah, Shadi Banitaan, Sameer Abufardeh, Wei Jin, Saeed Salem. "Selecting discriminating terms for bug assignment: a formal analysis". In Proceedings of the 7th International Conference on Predictive Models in Software Engineering (PROMISE 2011). Banff, Alberta, Canada, September 2011.
  9. Saeed Salem, Rami Alroobi, Shadi Banitaan, Loqmane Seridi, James Brewer, Ibrahim Aljarah. “CLARM: An Integrative Approach for Functional Modules Discovery”, in Proceedings of the International Workshop on Biomolecular Network Analysis (IWBNA’11), August 2011, Chicago, IL, USA.
  10. Shadi Banitaan, Saeed Salem, Wei Jin, and Ibrahim Aljarah. “A Formal Study of Classification Techniques on Entity Discovery and their application to Opinion Mining”. SMUC 2010, the 2nd International Workshop on Search and Mining User-generated Contents in Toronto (Canada), as a workshop of CIKM 2010. pdf , bibtex

Professional Experience

  • August 2017 – ON, Director and Associate Professor, University of Detroit Mercy, Detroit, MI, USA
  • January 2013 – July 2017, Assistant Professor, University of Detroit Mercy, Detroit, MI, USA
  • January 2012 – May 2012, Teaching Assistant, North Dakota State University, Fargo, ND, USA
  • September 2004 - August 2009, Instructor, University of Nizwa, Nizwa, Oman
  • September 2002 - June 2003, Instructor, Model School/Yarmouk University, Irbid, Jordan


  • PhD, Computer Science, North Dakota State University, USA, 2013.
  • M.Sc, Computer & Information Sciences, Yarmouk University, Jordan, 2004.
  • B.Sc, Computer Science, Yarmouk University, Jordan, 2002.