Projects
KANWISHER LAB
As the Data Scientist for the MGH-MIT InBRAIN Collaboration, I worked with Professor Nancy Kanwisher at MIT Brain and Cognitive Sciences to find category-selective regions during visual encoding. We presented a subset of images from the Natural Scenes Dataset to epilepsy patients with depth electrodes implanted all over the brain. Using deep tensor factorization, we isolated distinct neuronal populations that respond selectively to faces, bodies, scenes, and objects.
PRECISION MEDICINE
Glioblastoma multiforme (GBM) is known as the most aggressive form of brain cancer. An inherent limitation of measuring structural changes in GBM, and high grade gliomas generally, is the lack of an aprori patient-specific set of genes responsible for tumor growth. Solving this problem is crucial for the development of an effective curative therapy for patients with GBM, who have an average life expectancy of 14-16 months after diagnosis. To solve this problem, I present a network-based approach for the estimation of driver oncogenes within individual patients. I rely on spectral graph theory to predict gene regulation from single-patient tumor samples.
Glioblastoma multiforme. AANS. (2024, April 15). https://www.aans.org/patients/conditions-treatments/glioblastoma-multiforme/
VISION NEUROSCIENCE
For 9.012 Cognitive Science, a core course for the PhD program at MIT Brain and Cognitive Sciences, I presented on human intracranial findings of vision. This presentation will be relevant to folks interested in human intracranial neuroscience as well as anyone interested in the neural circuitry of vision.
