Virginia Smith

Virginia Smith, an assistant professor at Carnegie Mellon University, delves into her innovative work on federated learning. She discusses her research on fairness and robustness, highlighting the challenges of maintaining model performance across diverse data inputs. The conversation touches on her findings from the paper 'Ditto', exploring the trade-offs in AI ethics. Additionally, she shares insights on leveraging data heterogeneity in federated clustering to enhance model effectiveness and the balance between privacy and robust learning.