FACULTY Professor
Neuro-inspired Artificial Intelligence Lab
Ki-Jung Yoon Professor
Ph. D., University of Texas at Austin, USA
2019 ~ Present Assistant Professor at Hanyang University
2018 ~ 2019 Assistant Professor at Hongik University
2016 ~ 2018 Postdoc Fellow at Rice Univ. & Baylor College of Medicine



Neuro-inspired Artificial Intelligence Lab

Our group is interested in understanding principles that underlie inference, information processing and learning, mainly by using tools from deep machine learning.

1. Probabilistic Graphical Models
Probabilistic graphical models (PGMs) can efficiently represent the structure of many complex data and processes by making explicit conditional independences among random variables. We use PGMs as an adequate generative structure (inductive biases), allowing for rich integration into more complex systems.
2. Deep Learning
Deep learning is a representation-learning method with special emphasis on compositionality. We use its capability of learning complex functions with end-to-end design philosophy to solve complex structured problems.
3. Computational Neuroscience
What kinds of network connectivity or organization support integration, memory, and gating in the brain? We study these questions through the aforementioned tools.


Machine Learning, Artificial Intelligence, and Computational Neuroscience