Yağmur joined the Allen Institute in 2026, where she builds computational workflows that integrate multimodal datasets—EM connectivity, neuron morphology, axonal projections, and gene expression—making common features from diverse data types explorable in one place. Through her work on the Knowledge Engineering team, she contributes to making complex neuroscience data accessible to the research community and is interested in the systems and coordination that enable collaborative science.She completed her Ph.D. in 2024, supervised by Prof. Moritz Helmstaedter at the Max Planck Institute for Brain Research in Frankfurt and Prof. Mehmet Fatih Yanik at ETH Zurich. Her doctoral work focused on automated astrocyte segmentation in EM connectomics, uncovering specificity in astrocyte–synapse interactions with implications for synapse stability and learned states. Yağmur holds a B.Sc. in Electrical and Electronics Engineering from Bilkent University and an M.Sc. in Neuroengineering from the Technical University of Munich. An engineer and scientist by training, she was drawn to neuroscience by the parallels between engineered and biological systems. That perspective has guided her from circuits to connectomes.