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Emily P. Yang

dblp:117/2280 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1

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-AI interaction · 44% Human-robot interaction · 44% Collaborative and social computing · 13%
Artificial intelligence
1 paper
Legged, aerial and field robots · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
emotional intelligence
0.412019
Exploring Perceived Emotional Intelligence of Personality-Driven Virtual Agents in Handling User Challenges · WWW 2019
Human-AI interaction
virtual agents
0.412019
Exploring Perceived Emotional Intelligence of Personality-Driven Virtual Agents in Handling User Challenges · WWW 2019
Robotics › Legged, aerial and field robots › aerial robots
micro aerial vehicle
0.112012
Kinematic design of an asymmetric in-phase flapping mechanism for MAVs · ICRA 2012
Collaborative and social computing
social interaction
0.112019
Exploring Perceived Emotional Intelligence of Personality-Driven Virtual Agents in Handling User Challenges · WWW 2019

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

within-subject experiment · 0.4personality modeling · 0.4kinematic analysis · 0.1four-bar mechanism · 0.1RRPR mechanism · 0.1
YearPublicationVenuePosition
2019 Exploring Perceived Emotional Intelligence of Personality-Driven Virtual Agents in Handling User Challenges
abstract
An effective virtual agent (VA) that serves humans not only completes tasks efficaciously, but also manages its interpersonal relationships with users judiciously. Although past research has studied how agents apologize or seek help appropriately, there lacks a comprehensive study of how to design an emotionally intelligent (EI) virtual agent. In this paper, we propose to improve a VA's perceived EI by equipping it with personality-driven responsive expression of emotions. We conduct a within-subject experiment to verify this approach using a medical assistant VA. We ask participants to observe how the agent (displaying a dominant or submissive trait, or having no personality) handles user challenges when issuing reminders and rate its EI. Results show that simply being emotionally expressive is insufficient for suggesting VAs as fully emotionally intelligent. Equipping such VAs with a consistent, distinctive personality trait (especially submissive) can convey a significantly stronger sense of EI in terms of the ability to perceive, use, understand, and manage emotions, and can better mitigate user challenges.
Xiaojuan Ma, Emily P. Yang, Pascale Fung
WWW2
2012 Kinematic design of an asymmetric in-phase flapping mechanism for MAVs
abstract
The thorax of an insect has direct flight muscles that can independently control the flapping amplitude, relative phase, and mean position of its left and right wings. This feature allows insects to modulate lateral dynamics during hovering flight, resulting in high flight maneuverability. This paper introduces the development and characterization of a novel flapping mechanism for MAVs, denoted as AIFM (Asymmetric In-phase Flapping Mechanism), that is capable of achieving controlled, asymmetric in-phase wing flapping as inspired by similar features in insects. The system consists of two 4-bar mechanisms that create basic flapping motions and two RRPR mechanisms that control the asymmetric flapping motion. The kinematics of the mechanism was investigated and optimized in such a way that enables the mechanism to produce reliable, in-phase wing motion during asymmetric flapping flight. The kinematics of the wings was evaluated both computationally and experimentally. It was shown that asymmetric wing flapping can be successfully achieved without affecting the in-phase flapping motion.
Joon Hyuk Park, Emily P. Yang, Sunil K. Agrawal
ICRA2