Yaohui Guo

Yaohui Guo Ph.D. Candidate Department of Industrial & Operations Engineering, University of Michigan at Ann Arbor E-mail: yaohuig-at-umich-dot-edu Research interests: Human-AI/Robot Interaction, Sequential Decision Making, Linear Bandits.

Education

• University of Michigan, Ann Arbor, MI
  Ph.D. in Industrial and Operations Engineering, 2019 - present
  Thesis advisors: Professors X. Jessie Yang and Cong Shi
  M.S. in Mathematics, 2021
  M.S. in Robotics, 2018

• Xi'an Jiaotong University, China
  B.S. in Mechanical Engineering and Automation, 2015

Publications

Book Chapters

• From Trust to Trust dynamics: Combining Empirical and Computational Approaches to Model and Predict Trust Dynamics in Human-Autonomy Interaction,
  X. J. Yang, Y. Guo, C. Schemanske,
  Human-Automation Interaction: Transportation, edited by V. G. Duffy, S. J. Landry, J. D. Lee, N. Stanton, Springer, New York, NY

Journal Publications

• TIP: A Trust Inference and Propagation Model in Multi-Human Multi-Robot Teams,
  Y. Guo, X. J. Yang, C. Shi,
  Autonomous Robots, Vol. 48(20), 2024.

• Reverse Psychology in Trust-Aware Human-Robot Interaction,
  Y. Guo, C. Shi, X. J. Yang,
  IEEE Robotics and Automation Letters, Vol. 6(3), 4851-4858, 2021 (presented at ICRA 2021).

• Modeling and Predicting Trust Dynamics in Human-Robot Teaming: A Bayesian Inference Approach,
  Y. Guo, X. J. Yang,
  International Journal of Social Robotics, Vol. 13, 1899-1909, 2021.

Conference Proceedings

• Reward Shaping for Building Trustworthy Robots in Sequential Human-Robot Interaction,
  Y. Guo, X. J. Yang, C. Shi,
  2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023, Detroit, MI.

• Enabling Team of Teams: A Trust Inference and Propagation (TIP) Model in Multi-Human Multi-Robot Teams,
  Y. Guo, X. J. Yang, C. Shi,
  2023 Robotics: Science and Systems, RSS 2023, Daegu, Korea.

• Modeling Multi-vehicle Interaction Scenarios Using Gaussian Random Field,
  Y. Guo, V. V. Kalidindi, M. Arief, W. Wang, J. Zhu, H. Peng, D. Zhao,
  2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, Auckland, New Zealand

• A Versatile Approach to Evaluating and Testing Automated Vehicles based on Kernel Methods,
  Z. Huang, Y. Guo, M. Arief, H. Lam, D. Zhao,
  2018 Annual American Control Conference, ACC 2018, Milwaukee, WI.

• Evaluation of the Energy Efficiency in a Mixed Traffic with Automated Vehicles and Human Controlled Vehicles,
  X. Gong, Y. Guo, Y. Feng, J. Sun, D. Zhao,
  2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018, Maui, HI.

• TrafficNet: An Open Naturalistic Driving Scenario Library,
  D. Zhao, Y. Guo, Y. J. Jia,
  2017 IEEE Intelligent Transportation Systems Conference, ITSC 2017, Yokohama, Japan.

Short Papers & Abstracts

• TIP: A Trust Inference and Propagation Model in Multi-Human Multi-Robot Teams,
  Y. Guo, X. J. Yang, C. Shi,
  Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023, Stockholm, Sweden.

• Modeling Trust Dynamics in Human-robot Teaming: A Bayesian Inference Approach,
  Y. Guo, C. Zhang, X. J. Yang,
  Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, CHI 2020, Honolulu, HI.

Teaching

• Instructor, IOE 201 - Economic Decision Making, Fall 2023, University of Michigan.

• Teaching Assistant, ME 24677 - Linear Control System, Fall 2018, Carnegie Mellon University.

Awards

• Rackham Predoctoral Fellowship, University of Michigan, 2022

• Rackham Graduate Student Research Grant, University of Michigan, 2022

• Dean and Engineering Graduate Fellowship, University of Michigan, 2019

• Outstanding Graduate, Xi'an Jiaotong University, 2015

• 1st Prize, National Undergraduate Mathematics Competition, Chinese Mathematical Society, 2014

• National Scholarships, Xi'an Jiaotong University, 2013, 2014

• SMC Scholarship, Xi'an Jiaotong University, 2014

• 1st Prize, National Undergraduate Mathematical Contest in Modeling, CSIAM, 2014