Marc Langheinrich

Local AI models now predict user well-being from passive computer activity, offering explainable feedback directly within a workplace sensing application.

CRF-based aggregation in federated learning significantly boosts model performance by accurately reflecting client reliability and interactions, especially under data heterogeneity.

KANs become far more robust and interpretable with in-context symbolic regression, achieving near-perfect error reduction in hyperparameter sweeps.