Aleksandrina Goeva is a Postdoctoral Fellow in the Macosko Lab at the Stanley Center for Psychiatric Research within the Broad Institute of MIT and Harvard. She received her PhD in Mathematics and Statistics at Boston University, where she worked with Henry Lam and Eric Kolaczyk on complexity penalized methods for structured and unstructured data. During her postdoc, Aleksandrina has developed a deep interest in complex biological systems, for which we typically have only an incomplete and noisy set of measurements, and for the impact that expanding our knowledge of basic biological mechanisms can have on improving human disease. Her current research is focused on ill-posed inverse problems in biology, where she combines domain expert knowledge with modeling approaches ranging from linear and non-linear matrix factorizations, to graph attention networks, applied to single-cell RNA-seq and spatial transcriptomics data to answer questions about the mechanisms of interaction between cells and the function of tissues in health and disease, driven by applications to neurodegenerative diseases. In addition to striving to gain useful biological insights, Aleksandrina also works on theoretical problems in mathematics and statistics that arise from her applied work. Aleksandrina has a deep passion for science education and communication directed by her desire to convey complex concepts in simple and accurate terms. She also serves at the Steering Committee of the Models, Inference & Algorithms initiative at the Broad Institute. Aleksandrina believes that any human endeavor can benefit from having different perspectives being represented and strives to promote diversity within her spheres of influence.