Biography
Luling is a Ph.D. student in FSPH/IUSM Biostatistics and Health Data Science. Her research focuses on developing Bayesian methodology for complex networks, particularly brain and protein networks. She suspects that much of what we observe is a projection from a much higher-dimensional space, and that the most interesting part of a dataset often lies in its latent structure rather than the features we directly measure. With a background in mathematics, she is drawn to graph theory and its applications in neuroscience for this reason. In her spare time, she loves rock climbing, researching the art of raising cats, photographing nebulae and galaxies, and predicting people's destinies with star charts.