Dr Dobolyi joined GWU in the fall of 2021, having previously taught computer science at George Mason University for eight years. Her interests in computer science education focus on how to retain and increase the number of students in such courses, especially under-represented groups, via techniques such as self-pacing, active learning, test-driven development, automated feedback, student-led discussions, and focusing on non-traditional computer science applications. She has also worked in industry as a data scientist at a startup, and as an applied deep learning researcher at the non-profit IQT Labs, specializing in biomedical applications of computer vision and NLP. Her current research interests include automated testing for deep learning models and characterizing uncertainty in research on emerging infectious diseases.
- Ph.D., University of Virginia, 2010
- M.S., University of Virginia, 2008
- B.S., University of Maryland, 2004
- Software Testing
- Computer Science education
- Computer vision and NLP applied to biomedical challenges
- A Novel Self-Paced Model for Teaching Programming. Jeff Offutt, Paul Ammann, Kinga Dobolyi, Chris Kauffmann, Jaime Lester, Upsorn Praphamontripong, Huzefa Rangwala, Sanjeev Setia, Pearl Wang, and Liz White. Fourth Annual ACM Conference on Learning at Scale ([email protected]), April 2017, Cambridge MA, USA.
- How Do Interruptions During Designing Affect Design Cognition? John S. Gero, Hao Jiang, Kinga Dobolyi, Brooke Bellows, and Mick Smythwood. Design Computing and Cognition 2014: pp 119-133.
- Automating regression testing using web-based application similarities. Kinga Dobolyi, Elizabeth Soechting, Westley Weimer. Journal on Software Tools for Technology Transfer 13(2): 111-129 (2011)
- Modeling Consumer-Perceived Web Application Fault Severities for Testing. Kinga Dobolyi, Westley Weimer. International Symposium on Software Testing and Analysis (ISSTA) 2010: 97-106
- Harnessing Web-based Application Similarities to Aid in Regression Testing. Kinga Dobolyi, Westley Weimer. International Symposium on Software Reliability Engineering (ISSRE) 2009: 97-106