Human-Robot Interaction (HRI) · Augmented Reality (AR) · Robotics · AI


Developing capable robotic systems & understandable robot interactions


*Shown is a mobile manipulation testbed to evaluate my research

Zhao Han

Meet Zhao Han

he/him · /’jau̇-‘hän/ · 韩昭


Zhao Han is an Assistant Professor of Computer Science and Engineering at the University of South Florida. He leads the Reality, Autonomy, and Robot Experience (RARE) Lab.


Dr. Han’s research lies broadly in human-robot interaction (HRI), augmented reality (AR), robotics, and AI. He focuses on designing, developing, and evaluating novel robotic systems and interactions, for embodied robots to be more capable and understandable while interacting, collaborating, and teaming up with humans.

To advance this work, Dr. Han takes an interdisciplinary and human-centered approach, developing broad expertise in robot explanations for trust, projector-based and head-worn AR for communication, mobile manipulation for real-world evaluation, cognitive status-informed references, robot failures for robustness, and more.

Dr. Han has published over 40 peer-reviewed papers, collaborating across universities like CMU and disciplines like Psychology. He received the best long-paper award at INLG 2022, the best late-breaking report third prize at HRI 2022, and a best late-breaking report nominee at HRI 2023. He also led teams to win multiple international and national robot competitions.

He believes professional service benefits academic life by fostering friendship, collaboration, leadership, and communities, serving as publications co-chair of HRI 2024, program committee member of HRI 2023, 2024, & 2025 and general co-chair of AI-HRI 2022. He also co-organizes multiple workshops, chairs paper sessions, and edits journal special issues.

Recognized with two university-wide Diversity, Equity, and Inclusion (DEI) awards, Dr. Han founded the Mines Asian Community Alliance and co-organized the Inclusive HRI Workshop. He is also active in outreach to engage under-represented groups.

Valuing inclusive excellence, Dr. Han received the university-wide Excellence in Mentoring Undergraduate Research Award (Faculty) at USF in 2024. For teaching, Dr. Han’s Augmented Reality course was rated 4.72/5.0, confirming his real-world and student-focused approach.

Prior to USF, Dr. Han was a Post-Doctoral Fellow at Colorado School of Mines, mentored by Dr. Tom Williams, and received a Ph.D. in Computer Science from UMass Lowell, advised by AAAI Fellow Dr. Holly Yanco. He holds M.S. and B.S. degrees in Computer Science from the University of Manitoba in Canada.

Read recent news on the RARE Lab website →

  • Sep 14, 2024

    [HRI ’25] I will serve on the program committee of HRI 2025 to help the community grow!

  • Jun 13, 2024

    I will serve as an associate editor (AE) for RO-MAN 2024!

  • May 1, 2024

    I received the university-wide Excellence in Mentoring Undergraduate Research Award – Faculty today!

  • Mar 16, 2024

    I gave a keynote talk at the VAM-HRI workshop at HRI ’24!

  • Feb 5, 2024

    We had two papers [1, 2] accepted to the VAM-HRI 2024 workshop!

  • Dec 1, 2023

    We had a short contribution paper accepted to HRI 2024!

His Research


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

Human-Robot Interaction
(HRI)

nav path to

Augmented Reality
(AR)

crop 0 0 856 1142 0 fetch large gear

Robotics

crop 0 0 1492 1765 0 Robot Failure Explanation Algorithm with Behavior Trees

Artificial Intelligence
(AI)


Recent Publications


Do Results in Experiments with Virtual Robots in Augmented Reality Transfer To Physical Robots? An Experiment Design
Xiangfei Kong and Zhao Han

Do Results in Experiments with Virtual Robots in Augmented Reality Transfer To Physical Robots? An Experiment Design

WYSD 2024
To Understand Indicators of Robots’ Vision Capabilities
Hong Wang, Tam Do, and Zhao Han

To Understand Indicators of Robots’ Vision Capabilities

VAM-HRI 2024
Designing Indicators to Show a Robot’s Physical Vision Capability
Hong Wang, Tam Do, and Zhao Han

Designing Indicators to Show a Robot’s Physical Vision Capability

IEEE VR 2024 Poster
Reactive or Proactive? How Robots Should Explain Failures
Gregory LeMasurier, Alvika Gautam, Zhao Han, Jacob Crandall, and Holly Yanco

Reactive or Proactive? How Robots Should Explain Failures

HRI 2024
Causal-HRI: Causal Learning for Human-Robot Interaction
Jiaee Cheong, Nikhil Churamani, Luke Guerdan, Tabitha Edith Lee, Zhao Han, and Hatice Gunes

Causal-HRI: Causal Learning for Human-Robot Interaction

HRI 2024 Workshop Abstract
3rd Workshop on Inclusive HRI: Equity and Diversity in Design, Application, Methods, and Community
Raj Korpan*, Amy Eguchi, Zhao Han, Anastasia K. Ostrowski, Sindhu Ravindranath, and Ana Tanevska

3rd Workshop on Inclusive HRI: Equity and Diversity in Design, Application, Methods, and Community

HRI 2024 Workshop Abstract

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