In many ways, “vision science” can serve as a fruitful proxy for research in neuroscience and artificial intelligence. That is, given that a significant fraction of our nervous systems is geared towards processing visual information (and the subsequent cognitive and behavioral effects), the study of vision provides a rich means to explore a rich variety of cutting-edge topics of broad interest in science and technology. For example, vision researchers are a mix of experimentalists (e.g., neurophysiology, psychophysics), engineers (e.g., computer vision), biophysical & mathematical modelers (e.g., theoretical frameworks of learning), and translational scientists (e.g., development of retinal protheses). As such, vision research is a focal point where many efforts in applied mathematics come together.

 

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Topics to cover include:

•     Biophysics of vision (e.g., physiology and perception)
•     Models of neural processing of visual information
•     Machine/deep learning in modeling of physical constraints in computer vision
•     Information theory & efficient coding
•     Pattern recognition and machine learning
•     Statistical communication theory
•     Associated mathematical concepts (e.g., dynamical systems theory, Bayesian inference, convolutional networks)