Loading [MathJax]/extensions/MathMenu.js
Sharifa Alghowinem - IEEE Xplore Author Profile
Subscribe
ADVANCED SEARCH

Author details

< Back

Sharifa Alghowinem

Publications
24
Citations
589
Publications by Year
20132024
Co-Authors:
Show All Co-Authors (41)
Image of author Sharifa Alghowinem

Sharifa Alghowinem

Affiliation

Media Lab
MIT
Cambridge, USA

Publication Topics

Biography

Sharifa Alghowinem received the BSc degree in computer applications from King Saud University, in 2004, the MSc degree in software engineering from the University of Canberra, in 2010, and the PhD degree from the Australian National University, Computer Science Research School, in 2015. Her research interests include speech processing, computer vision, affective computing, and machine learning. She worked as a lecturer with the University of Canberra, in 2011, and currently holds a research and teaching position with Prince Sultan University.(Based on document published on 1 December 2016).
Publications
24
Citations
589
Publications by Year
20132024
Co-Authors:
Show All Co-Authors (41)
Author's Published Works

Showing 1-24 of 24 results

  • Sort

Filter Results

Show

Sort By

Results

Developing AI Leadership Competencies While Supporting Organization Capacity Building

Sharifa Alghowinem;Aikaterini Bagiati;Andrés F. Salazar-Gómez;Cynthia Breazeal

2024 IEEE Frontiers in Education Conference (FIE)
Year: 2024 | Conference Paper |
In this research-to-practice full paper, we present the third iteration of our educational framework that advances AI-informed leadership - a much-needed competency in this era of rapid AI transformation. Our study aimed to evaluate our proposed content and pedagogy and whether it can be made widely accessible to non-technical leaders. We focused on modifying our existing curriculum and research p...Show More

Developing AI Leadership Competencies While Supporting Organization Capacity Building

Sharifa Alghowinem;Aikaterini Bagiati;Andrés F. Salazar-Gómez;Cynthia Breazeal

Year: 2024 | Conference Paper |

A HeARTfelt Robot: Social Robot-Driven Deep Emotional Art Reflection with Children

Isabella Pu;Golda Nguyen;Lama Alsultan;Rosalind Picard;Cynthia Breazeal;Sharifa Alghowinem

2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)
Year: 2024 | Conference Paper |
Social-emotional learning (SEL) skills are essential for children to develop to provide a foundation for future relational and academic success. Using art as a medium for creation or as a topic to provoke conversation is a well-known method of SEL learning. Similarly, social robots have been used to teach SEL competencies like empathy, but the combination of art and social robotics has been minima...Show More

A HeARTfelt Robot: Social Robot-Driven Deep Emotional Art Reflection with Children

Isabella Pu;Golda Nguyen;Lama Alsultan;Rosalind Picard;Cynthia Breazeal;Sharifa Alghowinem

Year: 2024 | Conference Paper |

Doodlebot: An Educational Robot for Creativity and AI Literacy

Randi Williams;Safinah Ali;Raúl Alcantara;Tasneem Burghleh;Sharifa Alghowinem;Cynthia Breazeal

2024 19th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
Today, Artificial Intelligence (AI) is prevalent in everyday life, with emerging technologies like AI companions, autonomous vehicles, and AI art tools poised to significantly transform the future. The development of AI curricula that shows people how AI works and what they can do with it is a powerful way to prepare everyone, and especially young learners, for an increasingly AI-driven world. Edu...Show More

Doodlebot: An Educational Robot for Creativity and AI Literacy

Randi Williams;Safinah Ali;Raúl Alcantara;Tasneem Burghleh;Sharifa Alghowinem;Cynthia Breazeal

Year: 2024 | Conference Paper |

Integrating Flow Theory and Adaptive Robot Roles: A Conceptual Model of Dynamic Robot Role Adaptation for the Enhanced Flow Experience in Long-term Multi-person Human-Robot Interactions

Huili Chen;Sharifa Alghowinem;Cynthia Breazeal;Hae Won Park

2024 19th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
Year: 2024 | Conference Paper |
In this paper, we introduce a novel conceptual model for a robot’s behavioral adaptation in its long-term interaction with humans, integrating dynamic robot role adaptation with principles of flow experience from psychology. This conceptualization introduces a hierarchical interaction objective grounded in the flow experience, serving as the overarching adaptation goal for the robot. This objectiv...Show More

Integrating Flow Theory and Adaptive Robot Roles: A Conceptual Model of Dynamic Robot Role Adaptation for the Enhanced Flow Experience in Long-term Multi-person Human-Robot Interactions

Huili Chen;Sharifa Alghowinem;Cynthia Breazeal;Hae Won Park

Year: 2024 | Conference Paper |

Fostering Parent-Child Interactions through Behavioral Understanding of Synchrony

Jocelyn Shen;Ying Li;Javaria Hassan;Sharifa Alghowinem;Hae Won Park;Cynthia Breazeal;Rosalind Picard

2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
High-quality, social interactions between parents and their children are crucial for young children’s development. In order to develop affective, intelligent interactions between parents and children, it is important to understand how the parent’s nonverbal behavior influences the child’s affective state. In this paper, we explore the role of a parent’s nonverbal cues on a child’s engagement durin...Show More

Fostering Parent-Child Interactions through Behavioral Understanding of Synchrony

Jocelyn Shen;Ying Li;Javaria Hassan;Sharifa Alghowinem;Hae Won Park;Cynthia Breazeal;Rosalind Picard

Year: 2023 | Conference Paper |

Expresso-AI: An Explainable Video-Based Deep Learning Models for Depression Diagnosis

Felipe Moreno;Sharifa Alghowinem;Hae Won Park;Cynthia Breazeal

2023 11th International Conference on Affective Computing and Intelligent Interaction (ACII)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Given the widespread prevalence of depression and its consequential impact on individuals and society, it is crucial to obtain objective measures for early diagnosis and intervention. As a multidisciplinary topic, these objective measures should be interpretable and accessible to health care professionals, ensuring effective collaboration and treatment planning in the realm of mental health care. ...Show More

Expresso-AI: An Explainable Video-Based Deep Learning Models for Depression Diagnosis

Felipe Moreno;Sharifa Alghowinem;Hae Won Park;Cynthia Breazeal

Year: 2023 | Conference Paper |

Innovating AI Leadership Education

Xiaoxue Du;Sharifa Alghowinem;Matthew Taylor;Kate Darling;Cynthia Breazeal

2023 IEEE Frontiers in Education Conference (FIE)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
This research to practice full paper explores a new educational framework for AI-informed leadership and evaluates its curriculum and pedagogical approach through a novel, tailored, research instrument. Artificial Intelligence continues to rapidly transform many aspects of markets, solutions, and organizational culture across companies, agencies, and institutions in the public and private sectors....Show More

Innovating AI Leadership Education

Xiaoxue Du;Sharifa Alghowinem;Matthew Taylor;Kate Darling;Cynthia Breazeal

Year: 2023 | Conference Paper |

DRONEscape: Designing an Educational Escape Room for Adult AI Literacy

Daniella DiPaola;Jocelyn Shen;Rachelle Hu;Sharifa Alghowinem;Cynthia Breazeal

2023 IEEE Conference on Games (CoG)
Year: 2023 | Conference Paper |
Escape rooms have become increasingly popular as a form of entertainment, in addition to being adopted by educators for their effectiveness in improving student engagement and learning. While they have been introduced in various educational contexts, from nursing to mathematics, and for different age groups, including K-12 and university students, little research has been conducted on the benefits...Show More

DRONEscape: Designing an Educational Escape Room for Adult AI Literacy

Daniella DiPaola;Jocelyn Shen;Rachelle Hu;Sharifa Alghowinem;Cynthia Breazeal

Year: 2023 | Conference Paper |

Dyadic Affect in Parent-Child Multimodal Interaction: Introducing the DAMI-P2C Dataset and its Preliminary Analysis

Huili Chen;Sharifa Alghowinem;Soo Jung Jang;Cynthia Breazeal;Hae Won Park

IEEE Transactions on Affective Computing
Year: 2023 | Volume: 14, Issue: 4 | Journal Article |
Cited by: Papers (8)
High-quality parent-child conversational interactions are crucial for children's social, emotional, and cognitive development. However, many children have limited exposure to these interactions at home. As increasingly accessible and scalable interventions in child development, interactive technologies, such as social robots, have great potential for facilitating parent-child interactions. However...Show More

Dyadic Affect in Parent-Child Multimodal Interaction: Introducing the DAMI-P2C Dataset and its Preliminary Analysis

Huili Chen;Sharifa Alghowinem;Soo Jung Jang;Cynthia Breazeal;Hae Won Park

Year: 2023 | Volume: 14, Issue: 4 | Journal Article |

Interpretation of Depression Detection Models via Feature Selection Methods

Sharifa Alghowinem;Tom Gedeon;Roland Goecke;Jeffrey F. Cohn;Gordon Parker

IEEE Transactions on Affective Computing
Year: 2023 | Volume: 14, Issue: 1 | Journal Article |
Cited by: Papers (37)
Given the prevalence of depression worldwide and its major impact on society, several studies employed artificial intelligence modelling to automatically detect and assess depression. However, interpretation of these models and cues are rarely discussed in detail in the AI community, but have received increased attention lately. In this article, we aim to analyse the commonly selected features usi...Show More

Interpretation of Depression Detection Models via Feature Selection Methods

Sharifa Alghowinem;Tom Gedeon;Roland Goecke;Jeffrey F. Cohn;Gordon Parker

Year: 2023 | Volume: 14, Issue: 1 | Journal Article |

Practical Guidelines for Intent Recognition: BERT with Minimal Training Data Evaluated in Real-World HRI Application

Matthew Huggins;Sharifa Alghowinem;Sooyeon Jeong;Pedro Colon-Hernandez;Cynthia Breazeal;Hae Won Park

2021 16th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
Year: 2021 | Conference Paper |
Intent recognition models, which match a written or spoken input’s class in order to guide an interaction, are an essential part of modern voice user interfaces, chatbots, and social robots. However, getting enough data to train these models can be very expensive and challenging, especially when designing novel applications such as real-world human-robot interactions. In this work, we first invest...Show More

Practical Guidelines for Intent Recognition: BERT with Minimal Training Data Evaluated in Real-World HRI Application

Matthew Huggins;Sharifa Alghowinem;Sooyeon Jeong;Pedro Colon-Hernandez;Cynthia Breazeal;Hae Won Park

Year: 2021 | Conference Paper |

Body Gesture and Head Movement Analyses in Dyadic Parent-Child Interaction as Indicators of Relationship

Sharifa Alghowinem;Huili Chen;Cynthia Breazeal;Hae Won Park

2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)
Year: 2021 | Conference Paper |
Cited by: Papers (6)
Parent-child nonverbal communication plays a crucial role in understanding their relationships and assessing their interaction styles. However, prior works have seldom studied the exchange of these nonverbal cues between the dyad and focused on isolated cues from one person at a time. In contrast, this work analyzes both parents' and children's individual and dyadic nonverbal behaviors in relation...Show More

Body Gesture and Head Movement Analyses in Dyadic Parent-Child Interaction as Indicators of Relationship

Sharifa Alghowinem;Huili Chen;Cynthia Breazeal;Hae Won Park

Year: 2021 | Conference Paper |

Beyond the Words: Analysis and Detection of Self-Disclosure Behavior during Robot Positive Psychology Interaction

Sharifa Alghowinem;Sooyeon Jeong;Kika Arias;Rosalind Picard;Cynthia Breazeal;Hae Won Park

2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
Self-disclosure is an important part of mental health treatment process. As interactive technologies are becoming more widely available, many AI agents for mental health prompt their users to self-disclose as part of the intervention activities. However, most existing works focus on linguistic features to classify self-disclosure behavior, and do not utilize other multi-modal behavioral cues. We p...Show More

Beyond the Words: Analysis and Detection of Self-Disclosure Behavior during Robot Positive Psychology Interaction

Sharifa Alghowinem;Sooyeon Jeong;Kika Arias;Rosalind Picard;Cynthia Breazeal;Hae Won Park

Year: 2021 | Conference Paper |

A Robotic Positive Psychology Coach to Improve College Students’ Wellbeing

Sooyeon Jeong;Sharifa Alghowinem;Laura Aymerich-Franch;Kika Arias;Agata Lapedriza;Rosalind Picard;Hae Won Park;Cynthia Breazeal

2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
Year: 2020 | Conference Paper |
Cited by: Papers (37)
A significant number of college students suffer from mental health issues that impact their physical, social, and occupational outcomes. Various scalable technologies have been proposed in order to mitigate the negative impact of mental health disorders. However, the evaluation for these technologies, if done at all, often reports mixed results on improving users' mental health. We need to better ...Show More

A Robotic Positive Psychology Coach to Improve College Students’ Wellbeing

Sooyeon Jeong;Sharifa Alghowinem;Laura Aymerich-Franch;Kika Arias;Agata Lapedriza;Rosalind Picard;Hae Won Park;Cynthia Breazeal

Year: 2020 | Conference Paper |

Interpretation of Occluded Face Detection Using Convolutional Neural Network

Huaer Li;Sharifa Alghowinem;Sabrina Caldwell;Tom Gedeon

2019 IEEE 23rd International Conference on Intelligent Engineering Systems (INES)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
With the rapid development of artificial intelligence in past decades, great attention has been drawn to the field of face detection and recognition. Humans show a high degree of variability in their expressions, poses and appearance. Thus, limitations such as disguised and occluded faces, make it hard to implement high-accuracy face detection in real life. Although several algorithms have been pr...Show More

Interpretation of Occluded Face Detection Using Convolutional Neural Network

Huaer Li;Sharifa Alghowinem;Sabrina Caldwell;Tom Gedeon

Year: 2019 | Conference Paper |

Multimodal Depression Detection: Fusion Analysis of Paralinguistic, Head Pose and Eye Gaze Behaviors

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Julien Epps;Matthew Hyett;Gordon Parker;Michael Breakspear

IEEE Transactions on Affective Computing
Year: 2018 | Volume: 9, Issue: 4 | Journal Article |
Cited by: Papers (114)
An estimated 350 million people worldwide are affected by depression. Using affective sensing technology, our long-term goal is to develop an objective multimodal system that augments clinical opinion during the diagnosis and monitoring of clinical depression. This paper steps towards developing a classification system-oriented approach, where feature selection, classification and fusion-based exp...Show More

Multimodal Depression Detection: Fusion Analysis of Paralinguistic, Head Pose and Eye Gaze Behaviors

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Julien Epps;Matthew Hyett;Gordon Parker;Michael Breakspear

Year: 2018 | Volume: 9, Issue: 4 | Journal Article |

Cross-cultural detection of depression from nonverbal behaviour

Sharifa Alghowinem;Roland Goecke;Jeffrey F. Cohn;Michael Wagner;Gordon Parker;Michael Breakspear

2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)
Year: 2015 | Conference Paper |
Cited by: Papers (44)
Millions of people worldwide suffer from depression. Do commonalities exist in their nonverbal behavior that would enable cross-culturally viable screening and assessment of severity? We investigated the generalisability of an approach to detect depression severity cross-culturally using video-recorded clinical interviews from Australia, the USA and Germany. The material varied in type of intervie...Show More

Cross-cultural detection of depression from nonverbal behaviour

Sharifa Alghowinem;Roland Goecke;Jeffrey F. Cohn;Michael Wagner;Gordon Parker;Michael Breakspear

Year: 2015 | Volume: 1 | Conference Paper |

Eye movement analysis for depression detection

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Gordon Parker;Michael Breakspear

2013 IEEE International Conference on Image Processing
Year: 2013 | Conference Paper |
Depression is a common and disabling mental health disorder, which impacts not only on the sufferer but also on their families, friends and the economy overall. Despite its high prevalence, current diagnosis relies almost exclusively on patient self-report and clinical opinion, leading to a number of subjective biases. Our aim is to develop an objective affective sensing system that supports clini...Show More

Eye movement analysis for depression detection

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Gordon Parker;Michael Breakspear

Year: 2013 | Conference Paper |

Head Pose and Movement Analysis as an Indicator of Depression

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Gordon Parkerx;Michael Breakspear

2013 Humaine Association Conference on Affective Computing and Intelligent Interaction
Year: 2013 | Conference Paper |
Cited by: Papers (81)
Depression is a common and disabling mental health disorder, which impacts not only on the sufferer but also their families, friends and the economy overall. Our ultimate aim is to develop an automatic objective affective sensing system that supports clinicians in their diagnosis and monitoring of clinical depression. Here, we analyse the performance of head pose and movement features extracted fr...Show More

Head Pose and Movement Analysis as an Indicator of Depression

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Gordon Parkerx;Michael Breakspear

Year: 2013 | Conference Paper |

From Joyous to Clinically Depressed: Mood Detection Using Multimodal Analysis of a Person's Appearance and Speech

Sharifa Alghowinem

2013 Humaine Association Conference on Affective Computing and Intelligent Interaction
Year: 2013 | Conference Paper |
Cited by: Papers (12)
Clinical depression is a critical public health problem, with high costs associated to a person's functioning, mortality, and social relationships, as well as the economy overall. Currently, there is no dedicated objective method to diagnose depression. Rather, its diagnosis depends on patient self-report and the clinician's observation, risking a range of subjective biases. Our aim is to develop ...Show More

From Joyous to Clinically Depressed: Mood Detection Using Multimodal Analysis of a Person's Appearance and Speech

Sharifa Alghowinem

Year: 2013 | Conference Paper |

An exploratory study of detecting emotion states using eye-tracking technology

Majdah Alshehri;Sharifa Alghowinem

2013 Science and Information Conference
Year: 2013 | Conference Paper |
Cited by: Papers (2) | Patents (2)
Studying eye movement has proven to be useful in the study of detecting and understanding human emotional states. This paper aims to investigate eye movement features: pupil size, time of first fixation, first fixation duration, fixation duration and fixation count in clips emotional stimulation. Thirty seven subjects' pupil responses were measured while watching two pleasant and unpleasant emotio...Show More

An exploratory study of detecting emotion states using eye-tracking technology

Majdah Alshehri;Sharifa Alghowinem

Year: 2013 | Conference Paper |

AusTalk — The Australian speech database: Design framework, recording experience and localisation

Sharifa Alghowinem;Michael Wagner;Roland Goecke

2013 8th International Conference on Information Technology in Asia (CITA)
Year: 2013 | Conference Paper |
Cited by: Papers (2)
Aiming to create a comprehensive Australian speech database, the “AusTalk” project was carefully designed by 30 speech scientists contributing their disciplinary expertise. Standardised three one-hour audio-visual sessions for each of 1000 speakers around Australia were recorded having diverse components suitable for different research areas. The design of this database provides a good framework f...Show More

AusTalk — The Australian speech database: Design framework, recording experience and localisation

Sharifa Alghowinem;Michael Wagner;Roland Goecke

Year: 2013 | Conference Paper |

Detecting depression: A comparison between spontaneous and read speech

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Julien Epps;Michael Breakspear;Gordon Parker

2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Year: 2013 | Conference Paper |
Cited by: Papers (73)
Major depressive disorders are mental disorders of high prevalence, leading to a high impact on individuals, their families, society and the economy. In order to assist clinicians to better diagnose depression, we investigate an objective diagnostic aid using affective sensing technology with a focus on acoustic features. In this paper, we hypothesise that (1) classifying the general characteristi...Show More

Detecting depression: A comparison between spontaneous and read speech

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Julien Epps;Michael Breakspear;Gordon Parker

Year: 2013 | Conference Paper |

A comparative study of different classifiers for detecting depression from spontaneous speech

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Julien Epps;Tom Gedeon;Michael Breakspear;Gordon Parker

2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Year: 2013 | Conference Paper |
Cited by: Papers (68)
Accurate detection of depression from spontaneous speech could lead to an objective diagnostic aid to assist clinicians to better diagnose depression. Little thought has been given so far to which classifier performs best for this task. In this study, using a 60-subject real-world clinically validated dataset, we compare three popular classifiers from the affective computing literature - Gaussian ...Show More

A comparative study of different classifiers for detecting depression from spontaneous speech

Sharifa Alghowinem;Roland Goecke;Michael Wagner;Julien Epps;Tom Gedeon;Michael Breakspear;Gordon Parker

Year: 2013 | Conference Paper |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.