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Machine Learning and Mind Lab

KAIST-Mila Prefrontal AI Research Center

Korea Advanced Institute of Science and Technology (KAIST)
Welcome to the Machine Learning and Mind Lab (MLML) at KAIST. Our research aims to “develop machine learning algorithms for human-like general artificial intelligence” that can help us solve the hard problems of humanity. We seek to achieve this by creating learning algorithms fundamental to perception, cognition, and action. We hope that this computational approach will also shed light on the inner workings of the human mind.

 Contact

Email: sungjin.ahn@kaist.ac.kr Address: E3-1 3435, 291 Daehak-ro, Yuseong-gu, Daejeon, South Korea Phone: 042-350-3588

 News - 2024

09/13/24 - Fei Deng has successfully finished his Ph.D. defense. Congratulations Dr. Deng! Fei will be joining Google.
07/29/24 - We have launched KAIST-Mila Prefrontal AI Research Center. We will collaborate with Prof. Yoshua Bengio for the research of System 2 Deep Learning
02/06/24 - We hosted KAIST AGI Seminar Series #2 - Prof. Yoshua Bengio. Visit link for more information!
01/16/24 - Four papers have been accepted at ICLR 2024. One paper on the Spatially-Aware Transformer has been selected as a spotlight paper. Congratulations to all authors!

 News - 2023

11/17/23 - We held the first KAIST Seminar Series on AGI. The speaker for this event was Jim Fan
Three papers are accepted in NeurIPS 2023 with one spotlight paper. Congratulations to all authors!
Sungjin Ahn gave an invited talk at DeepMind about “Toward Neural Systematic Binder”, Feb 2023
“ROOTS: Object-Centric Representation and Rendering for 3D Scenes” is accepted in the Journal of Machine Learning Research
Two papers are accepted in ICML 2021
Our paper “Generative Neurosymbolic Machines” is accepted in NeurIPS 2020 as a spotlight!
Co-organizing ICML 2020 Workshop on Object-Oriented Learning (https://oolworkshop.github.io/)
Teaching in Fall 2020: CS 444: Deep Learning
2 papers accepted in ICLR 2020
Teaching CS 536: Machine Learning in Spring 2020
3 papers accepted in NeurIPS 2019 including one spotlight paper