Journal publications
(*: corresponding authors, +: co-first authors)
Google scholar citations
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[52] Lee J. H., Heo S Y., Lee S. W.*
Controlling human causal inference through in-silico task design
Cell Report (2024).
(media: Digital Chosun (interview), Donga Science, YTN, Herald Economy, news1, AI Times, Veritas-a, Asia Economy, etnews, enews Today, Chosun Biz, Robot News, Lecture News, Tech World, Shina Daily, Goodmorning Economy, University News, CCN News, Robot News, Global Economic, IT Daily, Cheonmae News, Medical Today, Work Today, Aju Economy, Newstreet, 4th)
[51] Kang Y. H., Khorasani A., Flint R., Farrokhi B., Lee S. W.*
Editorial: Neural Computations for Brain Machine Interface Applications
Frontiers in Human Neuroscience (2023).
[50] Yaman A., Leibo J. Z., Iacca G., Lee S. W.
The emergence of division of labor through decentralized social sanctioning
Proceedings of the Royal Society B: Biological Sciences (2023).
[49] Hwang S.-H., Park D., Paeng S., Lee S. W., Lee S.-H., Kim H. F.
Pneumatic tactile stimulus delivery system for studying brain responses evoked by active finger touch with fMRI
Journal of Neuroscience Methods (2023).
[48] Baker M.+, Kang S.+, Hong S., Song M, Yang M, Peyton L, Essa H, Lee S. W., Choi DS.
External globus pallidus input to the dorsal striatum regulates habitual seeking behavior in male mice
Nature Communications (2023).
[47] Kang S.+, Hong I.+, Kang S., Song M., Yang M. A., Essa H., Baker M., Lee J., Bruce R. A., Lee S. W., Choi DS.
Astrocyte activities in the external globus pallidus regulate action-selection strategies in reward-seeking behaviors
Science Advances (2023).
[46] Ruan Z., Seger C., Yang Q., Kim D., Lee S. W., Chen Q, and Peng Z.
Impairment of arbitration between model-based and model-free reinforcement learning in obsessive-compulsive disorder
Frontiers in Psychiatry (2023).
[45] Kwon M., Lee S. W., Lee S.-H.
Hippocampal integration and separation processes with different temporal and spatial dynamics during learning for associative memory
Human Brain Mapping (2023).
[44] Lee J., Leibo J. Z., An S. J., Lee S. W.*
Importance of prefrontal meta control in human-like reinforcement learning
Frontiers in Computational Neuroscience (2022).
[43] Yaman A.*, Bredeche N., Caylak O., Leibo J., Lee S. W.*
Meta-control of social learning strategies
PLOS Computational Biology (2022).
[42] Kim, D., Jeong J., Lee S. W.*
Prefrontal solution to the bias-variance tradeoff during reinforcement learning
Cell Reports (2021).
(media: AITimes, Korea Economy, Korea IT News, Seoul Economy, Seoul Economy -BioICT, Donga Science, Newsis, Daily Post, ZD Net Korea, News free zone, The Report, CC Daily News, iNews24, Web Economy, News1, Veritas-a, Newsband, Pusan Daily, SafeTimes, WorkToday, eNewsToday, eDHNews, UNN, CCN News, Lecture News, IT Daily, Wikitree, Medical Today, Economic Review, Asia Economy, Industry News, eDaily, Aju Business, Hello DD, Today Korea, etc.)
[41] Kim J., Lee S. W., Yoon, S., Park H., Jeong B.,
Neurocomputational mechanism of controllability inference under a multi-agent setting
PLOS Computational Biology (2021).
[40] Heo S., Sung Y., Lee S. W.*
Effects of subclinical depression on prefrontal–striatal model-based and model-free learning
PLOS Computational Biology (2021).
[39] J. Seo and S. W. Lee*
Neural network-based intuitive physics for non-inertial reference frames
IEEE Access (2021).
[38] O’Doherty J. P.*, Lee S. W., TadayonNejad R., Cockburn J., Iigaya K., Charpentier C.
Why and how the brain weights contributions from a mixture of experts
Neuroscience and Biobehavioral Reviews (2021).
[37] Ke, F., Choi S. J., Kang, Y. H., Cheon K-A* and Lee S. W.*
Exploring the structural and strategic bases of autism spectrum disorders with deep learning
IEEE Access (2020).
(media: Medical Express, Brinkwire, Mirage, JoongAng, Seoul news, ChosunMedia, Sports Khan, Bokuen news, Medinfo, eDaily, Kuki news, MediSobiza, Bosa news, etc.)
[36] Zuo, S., Wang, L., Shin, J. H., Cai, Y., Lee, S. W., Appiah, K., Zhou, Y., Kwok S. C.
Behavioral evidence for memory replay of video episodes in the macaque
eLife (2020).
[35] Song, M. and Lee S. W.*
Dynamic resource allocation during reinforcement learning accounts for ramping and phasic dopamine activity
Neural Networks (2020).
[34] Kim, D., Park, G. Y., O’Doherty J. P.*, Lee S. W.*
Task complexity interacts with state-space uncertainty in the arbitration process between model-based and model-free reinforcement-learning at both behavioral and neural levels
Nature Communications (2019).
(media: SBS News, IT Choson, Science Times, AI Times, Wired KR, Veritas-a, KBS World Radio, Hello DD, Korea Science Economy, Robot News, Syegye News, Asia News Agency, NewsWorks, Seoul Economy Daily, ENewsKorea, Asia Economy, IT News, ZD Net Korea, etnews, e Daily, Yonhap news, Science Monitor, Korea IT News, Industry News, Science Daily, EurekAlert, INGENTIUM, ACM Tech News, Knowledia, etc.)
[33] Weissengruber S.+, Lee S. W.+, O'Doherty J, Ruff C.
Neurostimulation reveals context-dependent arbitration between model-based and model-free learning
Cerebral Cortex (2019).
[32] Lee S. W. * and Seymour B.*
Decision-making in brains and robots - the case for an interdisciplinary approach
Current Opinion in Behavioral Science (2019).
[31] Lee, J. H.+, Seymour, B.+* Leibo, J. S., An, J., Lee, S. W.*
Towards high-performance, memory-efficient, and fast reinforcement learning: lessons from decision neuroscience
Science Robotics (2019).
(media: Dongascience, Veritas-a, Yonhap news, Korea IT news, Seoul daily newspaper, Money today, Science monitor, Robot news, Daily today, Global economic, etnews, etc.)
[30] Wang, O., Lee, S.W., O’Doherty, J., Seymour, B., and Wako, Y.
Model-based and model-free pain avoidance learning
Brain and Neuroscience Advances (2018).
[29] Kralik, J. D., et al.
Metacognition for a common model of cognition
Procedia Computer Science (2018). (post conference proceedings)
[28] Joo, H., Kim, J., and Lee, S.W.*
Model-based reinforcement learning using probabilistic simulation
J. Korean Inst. Intelligent System 27, 1–5 (2018). (written in Korean)
[27] Lee, S. W.*
Reinforcement learning: from algorithms to neuroscience
Commun. KIISE 36, 8–16 (2018). (written in Korean)
[26] Choung, O., Lee, S. W.* & Jeong, Y.*
Exploring feature dimensions to learn a new policy in an uninformed reinforcement learning task
Scientific Reports (2017).
[25] Lee, S. W.*, Yi, T., Han, J.-S., Jung, J.-W., and Bien, Z
Design of a gait phase recognition system that can cope with EMG electrode location variation
IEEE Transactions on Automation Science and Engineering 14(3) (2017).
[24] An, S. J. & Lee, S. W.*
A study on the exploration-exploitation dilemma using an uncertainty-driven state space learning algorithm
J. Korean Inst. Intelligent System 27, (2017). (written in Korean)
[23] Lee, S.W.*, O'Doherty, J.P., and Shimojo, S.
Neural computations mediating one-shot learning in the human brain
PLOS Biology 13(4): e1002137 (2015).
(synopsis "How one-shot learning unfolds in the brain" by Weaver, J.)
[22] O'Doherty, J.P., Lee, S.W., McNamee, D.
The structure of reinforcement-learning mechanisms in the human brain
Current Opinion in Behavioral Sciences 1, 94-100 (2015).
[21] Lee, S.W.*, Shimojo, S., and O'Doherty, J.P.
Neural computations underlying arbitration between model-based and model-free learning
Neuron 81, 687-699 (2014).
(front cover; preview "Decisions about decisions" by Yoshida, W. and Seymour, B.)
[20] Lee, S.W.*, Prenzel, O., and Bien, Z.
Applying human learning principles to user-centered IoT systems
IEEE Computer 46, 46-52 (2013). (cover feature)
[19] Han, J.-S., Lee, S.W.*, and Bien, Z.
Feature subset selection using separability index matrix
Information Sciences 223, 102-118 (2013).
[18] Jung, J.-W., Lee S. W., Bien Z. and Sato T.
Person Recognition Method using Sequential Walking Footprints via Overlapped Foot Shape and Center-Of-Pressure Trajectory
J. Syst., vol. 11, no. 4, pp. 34–39, 2013.
[17] Isik, L., Leibo, J.Z., Mutch, J., Lee, S.W., and Poggio, T.
A hierarchical model of peripheral vision
MIT CSAIL Technical Report, MIT-CSAIL-TR-2011-031 (2011).
[16] Jeon, M., Lee, S.W., and Bien, Z.
Hand gesture recognition using multivariate fuzzy decision tree and user adaptation
International Journal of Fuzzy System Applications 1, 15-31 (2011).
[15] Bien, Z. and Lee, S.W.
Learning structure of human behavior patterns in a smart home system.
Advances in Intelligent and Soft Computing 82, 1-15 (2010).
[14] Lee, S.W., Kim, Y.S., and Bien, Z.
A non-supervised learning framework of human behavior patterns based on sequential actions
IEEE Transactions on Knowledge and Data Engineering 22, 479-492 (2010).
[13] Lee, S.W. and Bien, Z.
Representation of a fisher criterion function in a kernel feature space
IEEE Transactions on Neural Networks 21, 333-339 (2010).
[12] Lee, S.W., Kim, Y.S., Park, K.-H., and Bien, Z.
Iterative bayesian fuzzy clustering toward flexible icon-based assistive software for the disabled
Information Sciences 180, 325-340 (2010).
[11] Grigorescu, S.M., Lee, S.W., and Ristic-Durrant, D.
Robust object recognition in service robotics
Proceedings of 30th Colloquium of Automation (2009).
[10] Song, J.-H., Jung, J.-W., Lee, S.W., and Bien, Z.
Robust EMG pattern recognition to muscular fatigue effect for powered wheelchair control
Journal of Intelligent & Fuzzy Systems 20, 3-12 (2009).
[9] Prenzel, O., Lee, S.W., Bien, Z., and Graeser, A.
A study on the application of the software framework MASSiVE in KAIST's intelligent sweet home system
International Journal of Assistive Robotics and Mechatronics 9 (2008).
[8] Jeon, M., Do, J.-H., Lee, S.W., Park, K.-H., and Bien, Z.
A personalized hand gesture recognition system using soft computing techniques
Journal of Korea Institute of Intelligent Systems 18, 53-59 (2008). (written in Korean)
[7] Bien, Z., Han, J.-S., and Lee, S.W.
Feature subset selection of biosignals for rehabilitation system
Proceedings of 28th Colloquium of Automation (2007).
[6] Kim, S., Jeon, M., Lee, S.W., Park, K.-H., and Bien, Z.
Development of assistive software for disabled and aged people based on user characteristics - unified user interface for special work chair
Journal of the Institute of Electronics Engineers of Korea 44 (2007). (written in Korean)
[5] Bien Z., Lee, H.-E., Lee, S. W., and Park, K.-H.
Learning Techniques in Service Robotics Environment
Appl. Artif. Intell., pp. 5–7, 2006.
[4] Kim, Y.S., Lee, S.W., Kang, S., Baek, Y.S., Hwang, S. and Bien, Z.
Supervised IAFC neural network based on the fuzzification of learning vector quantization
Lecture Notes in Computer Science 4253, 248-254 (2006).
[3] Lee, S.W., Kim, D.-J., Kim, Y.S., and Bien, Z.
Adaptive Gabor wavelet neural network-based facial expression recognition system
Journal of Fuzzy Logic and Intelligent System 16, 1-7 (2006). (written in Korean)
[2] Lee, S.W., Kim, D.-J., Kim, Y.S., and Bien, Z.
Training of feature extractor via new cluster validity - application to adaptive facial expression recognition
Lecture Notes in Artificial Intelligence 3864, 542-547 (2005).
[1] Kwon, Y.-J., Kim, D.-J., Lee, S.W., and Bien, Z.
Development of half-mirror interface system and its application for ubiquitous environment
Journal of Control, Automation and System Engineering 11, 1-7 (2005). (written in Korean)