Creating innovative bio-convergent technologies for better human life

이 상완
  • 부교수
  • 연구실: 516호, E16-1
  • 연구실명 : 뇌기계지능 연구실(Laboratory for Brain and Machine Intelligence (BML))
  • +82-42-350-4334
  • 2009 KAIST 전기및전자공학과 박사

계산신경과학, 뇌 기반 인공지능

  • 2020 ~ 현재

    한국과학기술원(KAIST) 바이오및뇌공학과 부교수

  • 2019 ~ 현재

    한국과학기술원(KAIST) 신경과학-인공지능 융합연구센터장

  • 2017 ~ 현재

    한국과학기술원(KAIST) 인공지능연구소 겸임교수

  • 2016 ~ 현재

    한국과학기술원(KAIST) 헬스사이언스 연구소 겸임교수

  • 2011 ~ 2015

    미국 Caltech, Della Martin Postdoctoral Scholar

  • 2010 ~ 2011

    미국 MIT, Postdoctoral Associate

주요 학회 활동 (학회장, 위원회 활동 등)


·         Program committee, Organization for Computational Neurosciences (OCNS) (2022-2023)

·         Director of general affairs, Korean Society for Computational Neuroscience (2016-present)

·         Board member, Korean Insitute of Inteliigent Systems (2016-present)

·         Board member, Korean Society of Human Brain Mapping (2017-2018)

·         Board member, KIISE Articial Intelligence Society (2016-present)

·         Steering committee, Machine Intelligence and Robotics Research Group (2017-2020)


국내외 학술대회 활동 (조직위원, 기조강연, 등)


·         General chair

Annual symposium of Korean Society for Computational Neuroscience (KSCN) 2021

Annual symposium of Korean Society for Computational Neuroscience (KSCN) 2019

·         Organizer

Next-generation AI: Toward Human-level Intelligence 2020

Google DeepMind talk series: Neuroscience-inspired AI 2019

KAIST-Harvard Joint Worshop on Neuroscience-inspired AI 2019

KAIST Half-day Workshop on Brain-inspired AI 2018

KAIST Computational Psychiatry Seminar Series 2017

KAIST International Workshop on Computational Psychiatry 2016

KAIST Neural Computation Workshop 2016

·         Conference committee

Organizing committee, AI World Cup (2018-2019)

Organizing committee, KSCN Winter School (2017-present)

Finance chair, Intl. Conference on Robot Intelligence Technology and Applications 2019

Session chair, SNU-KAIST Joint Symposium on Adaptive Intelligence 2020

Session chair, Annual conference of Korean Society of Biological Psychiatry 2018

Special session chair, IEEE/IEIE Intl' Conference on Consumer Electronics Asia 2018

Program committee, Advanced Course & Symposium on AI and Neuroscience (2021-2022)

Program committee, IEEE International Winter Conference on BCI (2016-present)

Program committee, The 21st Intl. Conference on Control, Automation, and Systems 2021

Program committee, Intl Conf on Robot Intelligence Technology and Applications 2017-2018


Program committee, Perception, Action, and Cognitive Systems Symposium (PACS) 2017


주요 학술지 활동 (편집장 및 편집위원)


·         Editorial board, Frontiers in Human Neuroscience (2021-present)

·         Journal review: Science Robotics, Science Advances, Nature Human Behavior, PLOS Computational Biology, Journal of Neuroscience, The Neuroscientist, etc. 

수상 경력: 교내, 교외


·         IBM Academic Awards (2021)

·         Google Faculty Research Award (2016)

·         KAIST International Cooperation Award (2022)

·         KAIST Songam Distinguished Research Award (2019)

·         KAIST Institute Faculty Award (2019)

·         KIIS Young Investigator Award (2016)

·         ICROS Young Investigator Award (2016)


대표 연구실적


  •        D. Kim, J. Jeong, S. W. Lee*, “Prefrontal solution to the bias-variance tradeoff during reinforcement learning,” Cell Reports, vol. 37, no. 13, 2021.

  • D. Kim, G. Y. Park, J. P. O’Doherty*, and S. W. Lee*, “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, 10, 5738, 2019.
  • J. H. Lee, B. Seymour, J. Z. Leibo, S. J. Ah, S. W. Lee*, “Towards high performance, memory efficient, and fast reinforcement learning - lessons from decision neuroscience,” Science Robotics, vol. 4, no. 26, 2019.
  • S. Weissengruber+, S. W. Lee+, John P. O'Doherty, Christian C. Ruff, “Neurostimulation reveals context-dependent arbitration between model-based and model-free reinforcement learning,” Cerebral Cortex, 2019 (+: co-first authors).
  • O. Choung, S. W. Lee*, and Y. Jeong*, “Exploring Feature Dimensions to Learn a New Policy in an Uninformed Reinforcement Learning Task,” Scientific Reports, vol. 7, no. 1, p. 17676, 2017.
  • S. W. Lee*, T. Yi, J.-W. Jung, and Z. Bien, “Design of a Gait Phase Recognition System That Can Cope With EMG Electrode Location Variation,” IEEE Trans. Autom. Sci. Eng., vol. 14, no. 3, pp. 1429–1439, 2017.
  • S. W. Lee*, J. P. O’Doherty, and S. Shimojo, “Neural Computations Mediating One-Shot Learning in the Human Brain.,” PLoS Biol., vol. 13, no. 4, p. e1002137, Apr. 2015. (Synopsis “How one-shot learning unfolds in the brain” by Weaver, J.)
  • S. W. Lee*, S. Shimojo, and J. P. O’Doherty, “Neural Computations Underlying Arbitration between Model-Based and Model-free Learning,” Neuron, vol. 81, no. 3, pp. 687–699, Feb. 2014. (Front cover; preview “Decisions about decisions” by Yoshida, W. and Seymour, B.)
  • S. W. Lee*, O. Prenzel, and Z. Bien, “Applying human learning principles to user-centered IoT systems,” IEEE Comput., vol. 46, no. 2, pp. 46–52, Feb. 2013. (cover feature)
  • S. W. Lee, Y. S. Kim, and Z. Bien, “A Nonsupervised Learning Framework of Human Behavior Patterns Based on Sequential Actions,” IEEE Trans. Knowl. Data Eng., vol. 22, no. 4, pp. 479–492, Apr. 2010.
  • S. W. Lee and Z. Bien, “Representation of a Fisher criterion function in a kernel feature space.,” IEEE Trans. Neural Networks, vol. 21, no. 2, pp. 333–339, Feb. 2010