• SuperPower Project: Designing algorithms to examine effects of parameter uncertainty on statistical power and identify regions of robustness/reactivity in specified parameter values over a high‑dimensional parameter space. Research article detailing our approaches incoming soon. Some more information found here SuperPower

  • FedPerf: Developing methods to characterize Private Federated Learning Systems and identify and track the performance of Federated Algorithms over varied environments with a single easy‑to‑use metric. Development and open-source deployment underway. Original Proposal found here Manuscript Link