Developing capable robotic systems & understandable robot interactions

Zhao Han

Meet Zhao Han

he/him · /’jau̇-‘hän/ · 韩昭


Zhao Han is a Post-Doctoral Fellow and Adjunct Faculty of Computer Science at Colorado School of Mines, joining Dr. Tom WilliamsMines Interactive Robotics Research Lab (MIRRORLab) in August 2021.

His research lies broadly in human-robot interaction (HRI), robotics, artificial intelligence (AI), and augmented reality (AR), including insights from psychology and cognitive science. Specifically, he focuses on designing and studying novel robotic systems and interactions, for embodied robots being more capable in human environments and more understandable while interacting with humans.

Dr. Han is an award-winning researcher. He has won the best long-paper award at INLG 2022 and the best late-breaking report third prize at HRI 2022. He also received the 2022 Mines Diversity, Inclusion & Access (DI&A) Award.

Previously, he had led teams to win multiple robot competitions: first place in the Panasonic Prototype 3D LiDAR Challenge, second place in the FetchIt Mobile Manipulation Challenge at ICRA 2019, and a finalist in the Analog Devices (ADI) Real-Time Sensor Fusion Challenge.

Service is important and beneficial to academic life. Dr. Zhao Han is a General Co-Chair of the 2022 AI-HRI symposium, and is actively involved in HRI standardization (more in CV). At Mines, he founded the Mines Asian Community Alliance and is a founding officer of Mines’ Postdoctoral Affairs Program. He believes in STEM outreach to broaden participation and involve under-represented, under-resourced communities.

Dr. Han received his Ph.D. (2021) in Computer Science from the University of Massachusetts Lowell in the Human-Robot Interaction Lab, directed by AAAI Fellow Dr. Holly Yanco. Previously, he received his M.S. (advised by Dr. Carson Leung in the Database and Data Mining Lab) and B.S. degrees in Computer Science at the University of Manitoba in Canada.

His Research


Human grasp effort is detected and the participant took the object with ease

Human-Robot Interaction
(HRI)

fetch large gear

Robotics

Robot Failure Explanation Algorithm with Behavior Trees

Artificial Intelligence
(AI)

nav path to

Augmented Reality
(AR)


Recent Publications


Communicating Missing Causal Information to Explain a Robot’s Past Behavior
Zhao Han and Holly A. Yanco

Communicating Missing Causal Information to Explain a Robot’s Past Behavior

THRI, 2022
Mixed-Reality Robot Behavior Replay: A System Implementation
Zhao Han, Tom Williams, Holly A. Yanco

Mixed-Reality Robot Behavior Replay: A System Implementation

AI-HRI 2022
Best of Both Worlds? Combining Different Forms of Mixed Reality Deictic Gestures
Landon Brown*, Jared Hamilton*, Zhao Han*†, Albert Phan*, Thao Phung*, Eric Hansen, Nhan Tran, and Tom Williams

Best of Both Worlds? Combining Different Forms of Mixed Reality Deictic Gestures

THRI, 2022
Givenness Hierarchy Informed Optimal Document Planning for Situated Human-Robot Interaction
Kevin Spevak*, Zhao Han*, Tom Williams, and Neil T. Dantam

Givenness Hierarchy Informed Optimal Document Planning for Situated Human-Robot Interaction

IROS 2022
Evaluating Referring Form Selection Models in Partially-Known Environments
Zhao Han, Polina Rygina, Tom Williams

Evaluating Referring Form Selection Models in Partially-Known Environments

INLG 2022
Towards Formalizing HRI Data Collection Processes
Zhao Han and Tom Williams

Towards Formalizing HRI Data Collection Processes

HRI Methods & Metrics 2022
Towards an Understanding of Physical vs Virtual Robot Appendage Design
Zhao Han*, Albert Phan*, Amia Castro*, Fernando Sandoval Garza* and Tom Williams

Towards an Understanding of Physical vs Virtual Robot Appendage Design

VAM-HRI 2022
“Why Didn’t I Do It?” A Study Design to Evaluate Robot Explanations
Gregory LeMasurier, Alvika Gautam, Zhao Han, Jacob W. Crandall, Holly A. Yanco

“Why Didn’t I Do It?” A Study Design to Evaluate Robot Explanations

WYSD 2022
Causal Robot Communication Inspired by Observational Learning Insights
Zhao Han, Boyoung Kim, Holly A. Yanco, Tom Williams

Causal Robot Communication Inspired by Observational Learning Insights

AAAI-SSS 2022

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