Research: Large-scale Deep Learning

In recent years, deep learning models such as CNN and DBN have emerged as a new and powerful paradigm for pattern recognition and classification. We are doing research on a scale-out deep learning system exploiting the computing power of GPUs. We are also interested in developing a deep interpretation model of multi-channel signals, especially invasive brain signal such ECoG. Currently, we focus on interpretation of real-time 32-channel signals through medical experiments using mouse as animal model.

Large-scale Deep Learning 

Related Projects

Development of Intelligent Interaction Technology Based on Context Awareness and Human Intention Understanding

IITP AI Flagship, Ministry of Science, Korea
Dec. 2016 ~ Aug. 2021

BigLearning: A Large-scale Optimization System of Deep Neural Network Models (PI)

Samsung Research Funding Center, Samsung Electronics, Korea
Dec. 2015 ~ Nov. 2018

Rehabilitation and replacement technology for brain damage employing electrical method

DGIST, Ministry of Science, Korea
Jan. 2012 ~ Dec. 2016

Related Papers

Coming soon…


Robot avatar system using hybrid interface and command server and sensory server therefor

Kim, M.-S., Son, S. H., Kim, J., Jeon, K., and Hong, I.
Korean Patent, Appl. No. 2013-0000646, Jan. 3, 2013, Reg. No. 10-1343860, Dec. 16, 2013.