Research

My current research interests are in computational/theoretical neuroscience. Specifically, I am interested in studying the algorithms behind different brain regions across different organisms, and how neural dynamics contribute to these computations from a theoretical perspective. I strongly believe in Richard Feynman’s quote: “What I cannot create, I do not understand.”. We are clear examples that these systems do work, and it’s all about what we can understand given our limited time.

My research focuses on computational modeling of the Drosophila olfactory system: to understand how information-rich inputs are transformed to lower-dimensional meaningful valence representation along deep layers of the olfactory system. These representations facilitate the fly to make appropriate actions by guiding other brain regions responsible for navigation and motor control.

My work within modeling is primarily focused on using fly Connectomes (Hemibrain and BANC) to build the olfactory system architecture with simple Multi-Layer Perceptron (MLP) and generating temporal responses for various odors firing rates published in Database of Odor Responses (DoOR) and finetuning the network activies to match the experimental data.

Research Experience

Teaching

Research Projects