Bio

Professional Education


  • Doctor of Philosophy, Stanford University, CS-PMN (2020)
  • Doctor of Philosophy, Stanford University, ME-PHD (2020)
  • Master of Science, Stanford University, ME-MS (2016)
  • Bachelor, University of Illinois at Urbana-Champaign, Mechanical Engineering (2013)
  • Masters, Stanford University, Mechanical Engineering (2015)

Stanford Advisors


Publications

All Publications


  • Investigating Tangible Collaboration for Design Towards Augmented Physical Telepresence DESIGN THINKING RESEARCH: MAKING DISTINCTIONS: COLLABORATION VERSUS COOPERATION Siu, A. F., Yuan, S., Pham, H., Gonzalez, E., Kim, L. H., Le Goc, M., Follmer, S., Plattner, H., Meinel, C., Leifer, L. 2018: 131–45
  • UbiSwarm: Ubiquitous Robotic Interfaces and Investigation of Abstract Motion as a Display Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Kim, L. H., Follmer, S. 2017; 1 (3): 20

    View details for DOI 10.1145/3130931

  • Zooids: Building Blocks for Swarm User Interfaces UIST 2016: PROCEEDINGS OF THE 29TH ANNUAL SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY Le Goc, M., Kim, L. H., Parsaei, A., Fekete, J., Dragicevic, P., Follmer, S. 2016: 97-109
  • Haptic Edge Display for Mobile Tactile Interaction CHI '16 Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems Jang, S., Kim, L. H., Tanner, K., Ishii, H., Follmer, S. 2016: 3706–3716

    View details for DOI 10.1145/2858036.2858264

  • Effects of Master-Slave Tool Misalignment in a Teleoperated Surgical Robot Kim, L. H., Bargar, C., Che, Y., Okamura, A. M., IEEE IEEE COMPUTER SOC. 2015: 5364–70
  • Design and Evaluation of a Trilateral Shared-Control Architecture for Teleoperated Training Robots Shamaei, K., Kim, L. H., Okamura, A. M., IEEE IEEE. 2015: 4887–93

    Abstract

    Multilateral teleoperated robots can be used to train humans to perform complex tasks that require collaborative interaction and expert supervision, such as laparoscopic surgical procedures. In this paper, we explain the design and performance evaluation of a shared-control architecture that can be used in trilateral teleoperated training robots. The architecture includes dominance and observation factors inspired by the determinants of motor learning in humans, including observational practice, focus of attention, feedback and augmented feedback, and self-controlled practice. Toward the validation of such an architecture, we (1) verify the stability of a trilateral system by applying Llewellyn's criterion on a two-port equivalent architecture, and (2) demonstrate that system transparency remains generally invariant across relevant observation factors and movement frequencies. In a preliminary experimental study, a dyad of two human users (one novice, one expert) collaborated on the control of a robot to follow a trajectory. The experiment showed that the framework can be used to modulate the efforts of the users and adjust the source and level of haptic feedback to the novice user.

    View details for Web of Science ID 000371717205041

    View details for PubMedID 26737388

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