Natalia Khuri

Dr. Natalia Khuri is an interdisciplinary researcher and educator with a broad background in computer science, biomedical data science and machine learning. She is an Assistant Professor in the Department of Computer Science and a Z. Smith Reynolds Faculty Fellow at Wake Forest University where she conducts data mining research and teaches undergraduate and graduate CS courses. Natalia holds a PhD and an MBA.

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Teaching

Classes taught:

• CSC 102 – Problem Solving with Python
• CSC 321 – Database Management Systems

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Publications

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Research

The research in DataMine laboratory focuses on the development of novel tools and approaches for data-centric artificial intelligence (DCAI). Unlike model-centric artificial intelligence (MCAI), which treats training data as auxiliary to the learning process and spends extraordinary time on optimizing the parameters of the model, DCAI aims to achieve better outcomes by keeping the model and its parameters unchanged and spends more time on improving the quality of the training data. Using non-trivial and automated data selection approaches, in our past research, we showed that accurate models may be trained with significantly less data, thus, requiring fewer computing resources and reducing the carbon footprint of MCAI.