Dr. Koutis and his former MS student Richard Garcia-Lebron have developed new optimization-based methods for semi-automatic segmentation of neurons in EM images. These methods produce segmentations whose quality comes close to that of human experts. These methods require very little human intervention, and complete the segmentation in a small fraction of the time needed for manual segmentation. At the heart of these algorithms are recently discovered solvers and optimization techniques in which Dr Koutis has been a key contributor. This ongoing project offers many opportunities for undergraduate students with different sets of skills and interests and at various levels. Conversely, the contribution of undergraduate students is beneficial for the project as it can provide the lower-level support for more advanced students, and a stream of potential contributors to the larger field of Connectomics, under the auspices of NIH’s BRAIN initiative.
Dr. Koutis bring to the project knowledge in theoretical computer science, with expertise in spectral graph theory, numerical linear algebra and parameterized algorithms for hard combinatorial problems.