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Nada Basit

Nada Basit

Lecturer in Computer Science

Office: Rice Hall, Room 405
Phone: 434-982-2213
Home Page:

Department of Computer Science
School of Engineering and Applied Science
University of Virginia
85 Engineer's Way, P.O. Box 400740
Charlottesville, Virginia 22904-4740

Areas Of Interest

Machine Learning, Bioinformatics, Data Mining, Pattern Recognition, Security, Biometrics, Computer Science Education

Biographical Sketch

Nada Basit is a full-time lecturer in the Computer Science Department at the University of Virginia. She received her PhD in Computer Science from George Mason University and earned her MS degree at GMU as well. She received her BS in computer science from University of Mary Washington. In addition, she has a Graduate Certificate in Biometrics from the Volgenau School of Engineering at George Mason University (2010). While a graduate student at George Mason University, she had extensive teaching experience both as a Graduate Teaching assistant to a number of graduate level courses there, and as an Adjunct faculty member teaching a number of undergraduate courses at University of Mary Washington. She was also selected to be a Research Fellow in the summer of 2001 at the Pratt School of Engineering at Duke University.


Nada's research interests within the field of computer science center on applications, among others, to biology (bioinformatics) and data mining. Specific areas of interest that support her research include artificial intelligence (machine learning, pattern recognition), biometrics, and computational mutagenesis.

Selected Publications

•    Nada Basit and Harry Wechsler, “Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction,” Advances in Bioinformatics, vol. 2011, Article ID 958129, 9 pages, 2011. doi:10.1155/2011/958129.
•    N. Basit and H. Wechsler “On-line Learning using Semi-Supervised Learning (SSL) and Transduction as New Learning Technology for Undergraduate Bioinformatics Studies”. Faculty Academy on Teaching and Learning Technologies, University of Mary Washington, Stafford, Virginia, May 11-12, 2011.
•    N. Basit and H. Wechsler “Function Prediction for in silico Protein Mutagenesis Using Transduction and Active Learning”. IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2011), Atlanta, Georgia, Nov. 12-15, 2011.
•    Nada Basit and Harry Wechsler, “Explanation and Prediction of nsSNP-Induced Pathology Using Association Mining, Transduction, and Active Learning,” Advanced Studies in Biology, vol. 5, no. 5, pp. 199-214, 2013.