KAIST
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Associate Professor
School of Computing
Graduate School of AI
KAIST-Mila Prefrontal AI Research
New York University
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Affiliated Faculty
I am currently an Associate Professor in the School of Computing at KAIST and an affiliated faculty member at New York University. Prior to joining KAIST, I served as an Assistant Professor of Computer Science at Rutgers University, where I was also affiliated with the Center for Cognitive Science. I direct the Machine Learning and Mind Lab, which operates at both KAIST and Rutgers, as well as the KAIST-Mila Prefrontal AI Research Center. You can find my research interests here. My academic journey includes earning a Ph.D. from the University of California, Irvine, where I studied scalable approximate Bayesian inference under Prof. Max Welling's supervision. Subsequently, I completed a postdoctoral fellowship at MILA, focusing on deep learning under the mentorship of Prof. Yoshua Bengio. My complete CV is available here.
Contact
Email: sjn.[lastname]@gmail.com or [firstname].[lastname]@kaist.ac.kr
Office: E3-1 3435, KAIST
Services
Conference Organization Committee
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NeurIPS 2022 (Workshop Chair)
Workshop Organizing Committee
Area Chair
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NeurIPS (2021~)
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ICML (2021~)
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ICLR (2023~)
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AAAI(2021~)
Reviewer
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NeurIPS (2015-2020)
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ICML (2015-2020)
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ICLR(2015-2022)
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AISTATS(2015 - 2020)
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AAAI(2015 - 2020)
Awards
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2016, Best Paper Award, International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning)
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2012, Best Paper Award, International Conference on Machine Learning (ICML)
Teaching
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2024-Spring, CS492, Deep Reinforcement Learning, KAIST
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2023-Fall, CS672, Reinforcement Learning (Graduate-Level), KAIST
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2023-Spring, CS492, Deep Reinforcement Learning, KAIST
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2022-Fall, CS570: Artificial Intelligence and Machine Learning, KAIST
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2022-Spring, CS376: Machine Learning, KAIST
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2021-Spring, CS536: Machine Learning, Rutgers University
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2020-Fall, CS444: Topics in Computer Science: Deep Learning, Rutgers University
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2020-Spring, CS536: Machine Learning, Rutgers University
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2019-Fall, CS535: Pattern Recognition, Rutgers University
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2019-Spring, CS671: Probabilistic Agent Learning, Rutgers University
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2012-Fall, Project in AI, UC Irvine (Teaching Assistant)
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2012-Summer, Undergraduate Summer Research in Machine Learning, UC Irvine (Teaching Assistant)
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2012-Spring, Recommender Systems, UC Irvine (Teaching Assistant)
Invited Talks
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“In Search of Neural Language of Thought Models,” Language Intelligence Research Lab, ETRI, July, 2024
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“In Search of Neural Language of Thought Models,” Embodied Intelligence Research Lab, ETRI, June, 2024
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“In Search of Neural Language of Thought Models,” CVPR Workshop on Causal and Object-Centric Representations for Robotics, June 17, 2024
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“World Models for High-Level Cognition”, CNIR Symposium on Brain, Mind, and Computation, Sungkyunkwan University, July, 2022
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“Unsupervised Discovery of World Structure”, KCC Machine Learning Workshop, Jeju, July 11, 2022
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“Deep Learning for Understanding the World like Humans”, Colloquium at KAIST Software Graduate Program, Mar 31, 2022
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“Unsupervised Discovery of World Structure”, Samsung Research, Mar 31, 2022
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Handong Global University, Feb. 2021
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Element AI, Canada, Nov. 2019
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Center for Cognitive Science, Rutgers University, Nov. 2019
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New York University, USA, Nov. 2019
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KAIST, Korea, Aug. 6, 2018
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Naver, Korea, Aug. 3, 2018
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Kakao Brain, Korea, Aug. 2, 2018
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Kakao Brain, Korea, Aug. 18, 2017
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Vector Institute, Toronto, May. 9, 2017
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Rutgers University, New Jersey, May. 1, 2017
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Microsoft Research, Redmond, Apr. 28, 2017
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Microsoft Maluuba, Montreal, Apr. 19, 2017
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Element AI, Montreal, Apr. 7, 2017
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IBM T. J. Watson Research, New York, Mar. 6, 2017
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Naver Labs, Korea, Jan. 24, 2017
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University of Southern California, Jan. 17, 2017
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Yonsei University, Korea, Jan. 13, 2017
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Seoul National University, Korea, Jan. 12, 2017
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SK T-Brain, Korea, Jan. 11, 2017
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KAIST, Korea, Jan. 6, 2017
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SK-Telecom Research, Korea, Dec. 2016
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Agency for Defence Development, Korea, Dec. 2016
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KAIST, Korea, 2015
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University of Toronto, Toronto, Machine Learning Group, Spring 2015
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University of Montreal, MILA, Montreal, Spring 2015
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ID Analytics Inc., San Diego, 2012
Students Supervision
Ph.D. Degree
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Fei Deng (Rutgers), Sep 2024, → Google
M.S. Program (Sorted by Graduation Date)
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Minseung Lee, Jun 2024, → MLML PhD Program
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Hany Hamed, KAIST, Jun 2024, → MLML PhD Program
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Yeongbin Kim, KAIST, Feb 2024, → Cocone M
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Chang Chen, Rutgers, Aug 2019, → MLML PhD Program
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Jindong Jiang, Rutgers, Aug 2020, → MLML PhD Program
Current Ph.D. Program
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Yohan Lee, KAIST, Sep 2024 - present
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Minseung Lee, KAIST, Sep 2024 - present
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Hany Hamed, KAIST, Sep 2024 - present
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Junmo Cho, KAIST, Sep 2022 - present
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Jaesik Yoon, KAIST, Sep 2023 - present
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Jindong Jiang, Rutgers, Feb 2019 - present
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Yi-Fu Wu, Rutgers, Sep 2019 - present
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Chang Chen, Rutgers, Sep 2019 - present
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Gautam Singh, Rutgers, Sep 2018 - present