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Bio:
Yeganeh is a member of the Informatics and Data team at the Institute. Her current research is focused on cellular analysis and the cell taxonomies using multimodal integration of electrophysiology and transcriptomic data. Yeganeh received her PhD in Electrical Engineering from Northeastern University. During her PhD, she was applying a combination of machine learning and signal processing techniques to develop communication tools such as brain-computer interfaces for people with neurological disorders. In particular, she developed an active recursive estimation method for enhancing the communication’s precision and speed. Yeganeh obtained her MS and BS in Biomedical Engineering from Amirkabir University of Technology (Tehran Polytechnic).
Research Focus:
Using computational methods in order to understand the brain function as a structural system is my primary research interest. There are countless strategies for understanding the brain as a system. A crucial step in understanding the brain is to examine the numerous cell groups and their connections to each other. Moreover, studying how the structure and function are related to each other is particularly insightful. These are the types of questions I attempt to answer by employing mathematical tools.
Machine Learning
Statistical Signal Processing
