Explores challenges and solutions for scalable and trustworthy learning in heterogeneous networks, emphasizing data heterogeneity, privacy, fairness, and robustness.
Explores bug-finding, verification, and the use of learning-aided approaches in program reasoning, showcasing examples like the Heartbleed bug and differential Bayesian reasoning.
