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I am an Assistant Professor in the School of Electronic and Electrical Engineering at Hongik University.

I was a postdoctoral researcher in Xaq Pitkow's lab at Baylor College of Medicine and Rice University. My recent work lies on the intersection of probabilistic graphical models and neural networks, to reproduce the brain's inference algorithm.

Prior to that, I obtained a PhD in 2015 in the Department of Electrical and Computer Engineering at UT Austin, in Ila Fiete's lab. My research in the Fiete group focused on neural coding, dynamics of neural networks, and Bayesian inference for studying neural representations of space in the brain.


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Graphic by KiJung Yoon

Inference in probabilistic graphical models by graph neural networks
Yoon, KJ., Liao, R., Xiong, Y., Zhang, L., Fetaya, E., Urtasun, R., Zemel, R., & Pitkow, X.
In review [arXiv:1803.07710]
(ICLR Workshop, 2018)

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Graphic by Xaq Pitkow

Reviving and improving recurrent backpropagation
Liao, R., Xiong, Y., Fetaya, E., Zhang, L., Yoon, KJ., Pitkow, X., Urtasun, R., & Zemel, R.
ICML (2018) [pdf]

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Graphic by Yi Gu

A map-like micro-organization of grid cells in the medial entorhinal cortex
Gu, Y., Lewallen, S., Kinkhabwala, A. A., Domnisoru, C., Yoon, KJ., Gauthier, J., Fiete, I. R., and Tank, D. W.
Cell (2018) [In press]

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Graphic by KiJung Yoon

Grid cell responses in 1D environments assessed as slices through a 2D lattice
Yoon, KJ.*, Lewallen, S.*, Kinkhabwala, A. A., Tank, D. W., and Fiete, I. R.
Neuron (2016) [pdf],[SI]

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Graphic by KiJung Yoon

Specific evidence of low-dimensional continuous attractor dynamics in grid cells
Yoon, KJ., Buice, M. A., Barry, C., Hayman, R., Burgess, N., and Fiete, I. R.
Nature Neuroscience (2013)

Conference abstracts


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