MRANMAY SHETTY
Master Student
Functional architecture of neural circuits
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AboutMranmay Shetty is an M.Sc. candidate in Modeling for Neuronal and Cognitive Systems at Université Côte d’Azur. With a background in engineering and machine learning, his research has evolved from explainable AI to neural decoding, biologically grounded models of working memory, and cortical circuit analysis. His interests lie at the intersection of systems neuroscience and Neuro-AI, with a particular emphasis on using computational methods to understand brain function. In the lab, he uses the MICrONS dataset to investigate how visual information and synaptic connectivity are organized across cortical circuits. His long-term goal is to combine circuit-level experiments, large-scale neural data analysis, and mechanistic modeling to better understand the principles underlying neural computation. |
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AboutMranmay Shetty is an M.Sc. candidate in Modeling for Neuronal and Cognitive Systems at Université Côte d’Azur. With a background in engineering and machine learning, his research has evolved from explainable AI to neural decoding, biologically grounded models of working memory, and cortical circuit analysis. His interests lie at the intersection of systems neuroscience and Neuro-AI, with a particular emphasis on using computational methods to understand brain function. In the lab, he uses the MICrONS dataset to investigate how visual information and synaptic connectivity are organized across cortical circuits. His long-term goal is to combine circuit-level experiments, large-scale neural data analysis, and mechanistic modeling to better understand the principles underlying neural computation. |