Lei Yang, Assistant Professor, Information Sciences and Technology, received funding for the project: “Achieve Fairness in AI-Assisted Mobile Healthcare Apps through Unsupervised Federated Learning.”
Yang aims to develop fair AI-assisted mobile dermatology diagnosis technology through unsupervised federated learning.
Yang and her collaborators plan to develop a federated on-device learning framework, which can continuously learn from new users’ data when they are using the mobile applications.
The researchers will also develop an unsupervised federated learning (FL) framework with heterogeneous hardware and develop an automatic neural architecture search (NAS) framework, specifically to ensure the participation from all socioeconomic populations and find the network with the best unsupervised learning capability while ensuring fairness and hardware constraints.
Yang received $85,700 from the University of Pittsburgh on a subaward from the National Institutes of Health for this project. Funding began in Aug. 2022 and will end in late April 2023.
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