{"id":631,"date":"2016-07-18T13:14:49","date_gmt":"2016-07-18T17:14:49","guid":{"rendered":"http:\/\/carleton.ca\/scs\/?post_type=cu-people&p=631"},"modified":"2026-05-26T09:08:19","modified_gmt":"2026-05-26T13:08:19","slug":"olga-baysal","status":"publish","type":"cu-people","link":"https:\/\/carleton.ca\/scs\/people\/olga-baysal\/","title":{"rendered":"Olga Baysal"},"content":{"rendered":"

Research Interests<\/h3>\n

Software Engineering, Artificial Intelligence, Machine Learning, Data Science.<\/span><\/p>\n

Specific Research Interests<\/h3>\n

AI for Software Engineering (AI4SE), Software Engineering for AI-enabled Systems, Mining Software Repositories, Software Maintenance and Evolution, Human Aspects of Software Engineering, Trustworthy AI.<\/p>\n

Current Research<\/h3>\n

Dr. Baysal’s work lies within the field of mining software repositories and is focused on analyzing large data sets by applying software analytics and providing ways to synthesize knowledge from the development artifacts such as reported issues, source code, discussions, community contributions, etc. Much of her work focuses on understanding how software engineers create, use, and maintain software systems. She applies empirical software engineering techniques to study software development processes and leverages software analytics to support practitioners\u2019 decision making.<\/p>\n

Biography<\/h3>\n

Dr. Baysal is an Associate Professor at the School of Computer Science and the Director of the Institute for Data Science, Carleton University. During 2020\u20132022, she was a Graduate Director (Admission and Recruitment) at the School of Computer Science, Carleton University. Baysal received her MMath and PhD degrees in Computer Science from the University of Waterloo and completed a short NSERC Postdoctoral Fellowship at the University of Toronto. Her work lies within the field of AI4SE (Artificial Intelligence for Software Engineering) and is focused on applying AI, ML, and NLP techniques to tackle software engineering problems and providing ways to synthesize knowledge from the development artifacts such as reported issues, source code, community contributions and discussions, etc. Much of Baysal\u2019s work focuses on understanding how software engineers create, use, and maintain software systems. She applies empirical software engineering techniques to study software development processes and leverages software analytics to support practitioners\u2019 decision making.<\/p>\n

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