VLDB 2026 Research / reviewers in the wild / expert
Kaitlynn Taylor Pineda
dblp:289/3918
· DBLP profile ↗
4ranked-venue papers
1as first author
4since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 4 · 1 first-author · 4 since 2021Artificial intelligence and machine learning · 3 · 1 first-author · 3 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | "See You Later, Alligator": Impacts of Robot Small Talk on Task, Rapport, and Interaction Dynamics in Human-Robot CollaborationabstractSmall talk can foster rapport building in human-human teamwork; yet how non-anthropomorphic robots, such as collaborative manipulators commonly used in industry, may capitalize on these social communications remains unclear. This work investigates how robot-initiated small talk influences task performance, rapport, and interaction dynamics in human-robot collaboration. We developed an autonomous robot system that assists a human in an assembly task while initiating and engaging in small talk. A user study$(N=58)$was conducted in which participants worked with either a functional robot, which engaged in only task-oriented speech, or a social robot, which also initiated small talk. Our study found that participants in the social condition reported significantly higher levels of rapport with the robot. Moreover, all participants in the social condition responded to the robot's small talk attempts; 59% initiated questions to the robot, and 73% engaged in lingering conversations after requesting the final task item. Although active working times were similar across conditions, participants in the social condition recorded longer task durations than those in the functional condition. We discuss the design and implications of robot small talk in shaping human-robot collaboration. Kaitlynn Taylor Pineda, Ethan Brown, Chien-Ming Huang 0001 |
HRI | 1 |
| 2023 | Older adults' expectations, experiences, and preferences in programming physical robot assistance
Gopika Ajaykumar, Kaitlynn Taylor Pineda, Chien-Ming Huang 0001 |
Int. J. Hum. Comput. Stud. | 2 |
| 2022 | "We Make a Great Team!": Adults with Low Prior Domain Knowledge Learn more from a Peer Robot than a Tutor RobotabstractIn peer tutoring, the learner is taught by a colleague rather than by a traditional tutor. This strategy has been shown to be effective in human tutoring, where students have higher learning gains when taught by a peer instead of a traditional tutor. Similar results have been shown in child-robot interactions studies, where a peer robot was more effective than a tutor robot at teaching children. In this work, we compare skill increase and perception of a peer robot to a tutor robot when teaching adults. We designed a system in which a robot provides personalized help to adults in electronic circuit construction. We compare the number of learned skills and preferences of a peer robot to a tutor robot. Participants in both conditions improved their circuit skills after interacting with the robot. There were no significant differences in number of skills learned between conditions. However, participants with low prior domain knowledge learned significantly more with a peer robot than a tutor robot. Furthermore, the peer robot was perceived as friendlier, more social, smarter, and more respectful than the tutor robot, regardless of initial skill level. Nicole Salomons, Kaitlynn Taylor Pineda, Adérónké Adéjàre, Brian Scassellati |
HRI | 2 |
| 2021 | Challenges Deploying Robots During a Pandemic: An Effort to Fight Social Isolation Among ChildrenabstractThe practice of social distancing during the COVID-19 pandemic resulted in billions of people quarantined in their homes. In response, we designed and deployed VectorConnect, a robot teleoperation system intended to help combat the effects of social distancing in children during the pandemic. VectorConnect uses the off-the-shelf Vector robot to allow its users to engage in physical play while being geographically separated. We distributed the system to hundreds of users in a matter of weeks. This paper details the development and deployment of the system, our accomplishments, and the obstacles encountered throughout this process. Also, it provides recommendations to best facilitate similar deployments in the future. We hope that this case study about Human-Robot Interaction practice serves as an inspiration to innovate in times of global crises. Nathan Tsoi, Joe Connolly, Emmanuel Adéníran, Amanda Hansen, Kaitlynn Taylor Pineda, Timothy Adamson, Sydney Thompson, Rebecca Ramnauth, Marynel Vázquez, Brian Scassellati |
HRI | 5 |