Ling-Qi Zhang

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Ling-Qi Zhang /

I study how animals solve ecologically relevant computational problems efficiently by exploiting statistical and structural regularities of their environment. To approach this question, I develop theory and models of complex, natural behavior and neural computation.

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Overview

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I am fascinated by how biological systems can solve challenging computational problems with remarkable efficiency. My long-term research goal is to understand how structures of neural circuits enable this efficiency, and how inductive biases of animals are aligned with their ecological environments.

My graduate work studied these ideas in the context of early sensory systems, focusing on how statistics of the visual environment shape both behavior and neural representation (i.e., efficient coding). At Janelia, I study theory of inductive biases and learning, while collaborating closely with experimentalists to develop models of animal behavior in naturalistic environments.

I received my Ph.D. from the University of Pennsylvania, working with David Brainard and Alan Stocker. I also hold an M.A. in Statistics from Penn. Before that, I got my B.E. in Computer Science from Southern University of Science and Technology, in Shenzhen, China.

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Ling-Qi Zhang