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Fatemeh Nargesian, the James P. Wilmot Distinguished Assistant Professor in the Department of Computer Science, has received a 2024 Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF).

CAREER awards are the NSF’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.

The award will fund Nargesian’s research in the data-efficiency of machine learning, focusing on developing a novel paradigm for model-driven data preparation and summarization to ensure accurate, fair, and efficient model training. A model-driven view of data considers not only the completeness and correctness of data but also the performance of downstream models. This co-optimization of data and model involves treating the key dimensions of model quality—such as accuracy, fairness, and robustness—as first-class citizens during data acquisition and data generation interventions. Furthermore, learning from massive datasets requires substantial computational resources, which consume significant energy and contribute to a large carbon footprint. Summarizing data so that machine learning can be done efficiently, without significant loss in other aspects of model quality, is therefore crucial to reducing these costs and goes hand in hand with model-driven data preparation. The proposed work advocates for a paradigm shift toward model-driven data preparation, emphasizing model-aware data acquisition, coreset (weighted subset) construction, and the eventual declarative handling of the data preparation process.

Learn more about Nargesian’s project.

Fatemeh will be running in the Chicago Marathon next week, it will be her 10th.