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Sugandha Sharma is a Ph.D. candidate at MIT advised by Prof. Ila Fiete and Prof. Josh Tenenbaum. She explores the computational and theoretical principles underlying higher cognition in the brain by constructing neuro-inspired models and mathematical tools to discover how the brain navigates the world, or how to construct memory mechanisms that don’t exhibit catastrophic forgetting. In this episode, we chat about biologically inspired neural architectures, how memory could be implemented, why control theory is underrated, and much more.
Below are some highlights from our conversation as well as links to the papers, people, and groups referenced in the episode.
Some highlights from our conversation
“Neuroscience is such an open field still, it’s so nascent, so in its early stages, that there are so many important questions. My perspective is that we really need to sync theory and experiment; whatever questions we address, we really need to think about how we can create this loop between theory and experiments so that we can test the predictions made by our models and then come back and correct our models based on the experiments and findings.”