Leila is a Scientist in the Brain Science Accelerator focused on the analysis and integration of dense connectomics data. She develops computational tools and pipelines to analyze Light Microscopy based Connectomics (LICONN) in conjunction with electron microscopy based datasets. Her work is focused on building scalable approaches that extract biological insights from large structural data. Leila is particularly interested in multimodal alignment and developing tools to bridge our understanding of cell-types across connectomics and other biological modalities.Prior to this role, Leila completed her PhD in Computational Neuroscience at the University of Washington, co-advised by John Tuthill and Forrest Collman. Her graduate work spanned mammalian and invertebrate connectomics where she developed pipelines for single-cell classification from perisomatic structure, designed unsupervised methods for rare cell discovery, and mapped the somatotopic organization of the Drosophila leg circuit supporting spatially targeted grooming. She holds a BA in Neuroscience from Wellesley College and received the Harold M. Weintraub Graduate Student Award in recognition of her graduate research.Before her doctoral work, Leila worked at the Allen Institute from 2016-2020. On the Network Anatomy team, she built and trained models for segmentation and volumetric image analysis. On the Synapse Biology team, she developed high-throughput imaging pipelines for array tomography and trained deep learning models for cell-type clustering and segmentation of transcriptomic data. She is deeply committed to making science open and accessible. She has taught at multiple local and international workshops, mentored high school and undergraduate students, and is an active volunteer for science outreach across career stages.