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Majid Komeili is an Associate Professor in the School of Computer Science at Carleton University. His research focuses on machine learning, emphasizing the development of interpretable machine learning models and deep neural networks. He explores transfer learning and the creation of machine learning models that maintain explainability, striving to develop methods that elucidate existing black-box machine learning models. Additionally, he studies the capacity of machine learning models to learn and perform new tasks with a limited amount of labeled data, mirroring the capabilities of human cognition in these domains.
Includes MEng and MASc options.