Our group focuses on developing methodologies for solving the "nanostructure inverse problem": the problem of determining the structure of materials at the atomic scale to help understand structure-synthesis-property relationships in complex and functional materials . We develop and utilize experimental procedures at high flux x-ray and neutron and electron producing facilities coupled with computational and applied mathematical/AI solutions for inverting the inverse problem.  These methods can be applied to high throughput structural analysis, solution, and prediction of materials at the nanoscale, including materials "in action" (out of their ground-state). These approaches can be applied to many materials systems from amorphous and nanostructured pharmaceuticals and molecular materials,  through nanoscale fluctuations in exotic quantum materials, materials for energy and environmental remediation, among many other topics.  We are also interested in developing the data structures that can be used for building autonomous self-driving laboratories that couple synthesis with characterization in automated loops.