Subgroup 04 | Data Reporting
Zhao Han (co-chair)
| Assistant Professor, University of South Florida (USA) Website: https://zhaohanphd.com/
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. 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, and general co-chair of AI-HRI 2022. He also co-organizes multiple workshops, chairs paper sessions, and edits journal special issues.
Paul Pridham (co-chair)
| University of Michigan (USA)
Connor Esterwood
| University of Michigan (USA)
Connor Esterwood is a Ph.D. Candidate at the University of Michigan’s School of Information. His research investigates the capacity of robots to repair and restore trust in the aftermath of errors. In addition, he also explores how individual differences such as personality and mind perception impact human–robot interaction. His work has appeared in leading journal sand conferences across the human–robot interaction and human–computer interaction space including publication in Nature Scientific Reports, Computers in Human Behavior (CHB), International Journal of Human–Computer Interaction (IJHCI), IEEE Robotics and Automation Letters (RA-L), the ACM/IEEE Conference on Human-Robot Interaction (HRI), the ACM Conference on Human Factors in Computing Systems (CHI), and, the IEEE Conference on Robot & Human Interactive Communication (RO-MAN).
Snehesh Shrestha
| UMD PhD Candidate/ NIST PREP Researcher (USA) Website: https://www.snehesh.com
Snehesh Shrestha is a Ph.D. candidate at the University of Maryland College Park. He works in the Perception and Robotics Group (PRG) lab in the Department of Computer Science under the guidance of Prof. Yiannis Aloimonos (CS), Dr. Cornelia Fermüller (UMAICS), Dr. Ge Gao (INFO), and Dr. Irina Muresanu (School of Music). His research is at the intersection of robotics, artificial intelligence, human factors, arts, and culture. He is interested in multidisciplinary research aimed at building rich and intuitive experiences that ‘amplify human abilities, empowering people and ensuring human control.’ His recent work includes natural repair mechanisms in HRI and AI-empowered music education.
Shelly Bagchi
| Electrical Engineer, US National Institute of Standards and Technology (USA), Website: https://www.nist.gov/people/shelly-bagchi
Shelly Bagchi is an Electrical Engineer at the National Institute of Standards and Technology in Gaithersburg, Maryland. Shelly is the Project Lead for the Digital Twins and Emerging Technology for SMEs Project within the Measurement Science for Manufacturing Robotics Program at NIST. Her research interests are in human-robot interaction, replicability & reproducibility, and augmented reality. Shelly chairs the IEEE Standards Group P3108, Recommended Practice for Human-Robot Interaction Design of Human Subject Studies, and is the secretary for IEEE P3107, Standard Terminology for Human-Robot Interaction. She serves as a volunteer organizer for several events, including the International Symposium on Technological Advances in Human-Robot Interaction (tahri.org) and the annual ACM/IEEE International Conference on Human-Robot Interaction (humanrobotinteraction.org).
Curtis Gittens
| University of the West Indies
Daniel Hernandez Garcia
| Heriot-Watt University (UK) Website: https://dhgarcia.github.io/
Daniel Hernández García is a Research Fellow at the Interaction Lab, School of Mathematical and Computer Sciences, Heriot-Watt University. His research lies at the intersection of HRI and AI, with a focus on developing socially aware intelligent autonomous systems that can work with and for humans, particularly in assistive, collaborative or education scenarios. He works on the application of data-driven and deep learning approaches for deploying autonomous systems applications in real scenarios with human users.
Liz Carter
| Carnegie Mellon University (USA)