Explores spatial ergodicity for SPDEs, covering basic formulations, initial data effects, and results on ergodicity and CLT.
Explores causal inference, directed graphs, and fairness in algorithms, emphasizing conditional independence and the implications of DAGs.
Introduces a virtual seminar on stochastic analysis, covering a wide range of topics and focusing on the mathematical challenges of the COVID-19 crisis.
Explores directed networks with asymmetric relationships and hypergraphs that generalize graphs by allowing edges to connect any subset of nodes.
