B.S. ​Mary Washington College (now University of Mary Washington), 2003M.S. ​George Mason University, 2006Ph.D. ​George Mason University, 2012


​Research interests include:

Machine Learning, Bioinformatics, Data Mining, Pattern Recognition


​Nada Basit is a full-time Assistant Professor 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.

Research Interests

  • Machine Learning
  • Bioinformatics
  • Data Mining
  • Pattern Recognition
  • Biometrics
  • Computer Science Education

Selected Publications

  • “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. Nada Basit and Harry 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, 2011. N. Basit and H. 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. Nada Basit and Harry Wechsler

Courses Taught

  • CS4750 "Database Systems"
  • CS2110 "Software Development Methods"
  • CS1111 "Introduction to Programming" (CS1, for students with prior experience)
  • CS 5010 "Programming and Systems for Data Analysis"
  • CS 5012 "Foundations of Computer Science"
  • CS 6750 "Database Systems"