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Christina Wasylyshyn

dblp:20/8243 · DBLP profile ↗
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7ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 7 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 6 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
trust in robots
0.912025
Trusting a Disobedient Robot: Rejecting a Command for Constructive Reasons Improves Evaluations of Trust · HRI 2025
Human-robot interaction
robot autonomy
0.312025
Trusting a Disobedient Robot: Rejecting a Command for Constructive Reasons Improves Evaluations of Trust · HRI 2025

Methods — techniques the papers use, named apart from their topics

vignette-based study · 0.9
YearPublicationVenuePosition
2025 Trusting a Disobedient Robot: Rejecting a Command for Constructive Reasons Improves Evaluations of Trust
abstract
Increasing autonomy and anticipation of the prevalence of human-robot teams has lead to focus on how humans trust robots. Additionally, some researchers argue that robots should be capable of intelligent disobedience, either in situations of epistemic misalignment (i.e., situational misunderstanding) or normative conflict (i.e., when obedience to normative principle supersedes compliance). Little work exists on the effects of robot disobedience on trust, and what does exist focuses primarily on normative conflict scenarios. Here we present novel results showing differences in trust evaluations between robots that exhibit strict obedience to commands versus those that exhibit intelligent disobedience. Specifically, we report on a vignette-based study designed to test the effect of intelligent disobedience by a robotic agent on evaluations of trust in situations of epistemic misalignment.
Gordon Briggs, Christina Wasylyshyn
HRI2
2019 Neither the time nor the place: Omissive causes yield temporal inferences
Gordon Briggs, Hillary Harner, Christina Wasylyshyn, Paul Bello, Sangeet S. Khemlani
CogSci3
2019 Elicitation of Quantified Description Under Time Constraints
Gordon Briggs, Christina Wasylyshyn, Paul Bello
CogSci2
2018 Enumeration by pattern recognition requires attention: Evidence against immediate holistic processing of canonical patterns
Gordon Briggs, Christina Wasylyshyn, Paul Bello
CogSci2
2017 Contrasts in reasoning about omissions
Paul Bello, Christina Wasylyshyn, Gordon Briggs, Sangeet S. Khemlani
CogSci2
2016 Attentive and Pre-Attentive Processes in Multiple Object Tracking: A Computational Investigation
Paul Bello, Will Bridewell, Christina Wasylyshyn
CogSci3
2016 Audio-Visual Task Switching in Multisensory Environments
Christina Wasylyshyn
CogSci1