Saad Elbeleidy

Peerbots

Recent work on Socially Assistive Robotics in Therapy has revealed a dual-cycle model, with the vast majority of prior work on Socially Assistive Robotics narrowly focused on the human-robot interaction, termed the "inner cycle". In contrast, little attention has been paid to the activities performed before and after the interaction, termed the "ou...

End-user development (EUD) in Human-Robot Interaction (HRI) aims to expand access and applicability of robotics by allowing people with minimal robotics expertise to use and benefit from robots. To develop these systems, HRI researchers often rely on human-centered design methods that focus on the robot user. These design methods justifiably center...

Researchers have called for the development of dedicated authoring interfaces that can support caregivers in authoring socially assistive robot content. In this paper, we present an authoring interface specifically designed for authoring robot dialogue for reading a book with a child. Our interface incorporates past research on Socially Assistive R...

Socially assistive robots play an effective role in children’s therapy and education. Robots engage children and provide interaction that is free of the potential judgment of human peers and adults. Research in socially assistive robots for children generally focuses on therapeutic and educational outcomes for those children, informed by a vision o...

Some labor is overlooked or devalued, while necessary within the context of paid employment. This is "invisible labor". Invisible labor is often performed by minoritized groups and is typically invisible to those in power. Novel technologies can introduce new sociotechnical labor paradigms that reduce labor visibility. In this paper, we consider ho...

Socially Assistive Robots (SARs) have shown promise, but there are still practical challenges to their widespread adoption. Recent research has demonstrated the advantages of teleoperated systems in this space and called for better guidelines for teleoperation interfaces. We ran group usability tests with therapists with no experience with robots t...

To enable natural and fluid human-robot interactions, robots need to not only be able to communicate with humans through natural language, but also do so in a way that complies with the norms of human interaction, such as politeness norms. Doing so is particularly challenging, however, in part due to the sensitivity of such norms to a host of diffe...

Socially Assistive Robots (SARs) show significant promise in a number of domains: providing support for the elderly, assisting in education, and aiding in therapy. Perhaps un-surprisingly, SAR research has traditionally focused on providing evidence for this potential. In this paper, we argue that this focus has led to a lack of critical reflection...

Socially Assistive Robots are effective at supporting autistic children in a variety of different therapies. Therapists can control the robots' motions and verbalizations to engage children and deliver therapeutic interventions based on their needs. We present teleoperation capabilities to support therapists in customizing therapy to their clients'...

Therapist-operated robots can play a uniquely impactful role in helping children with autism practice and acquire social skills. While extensive research within Human-Robot Interaction has focused on teleoperation interfaces for robots in general, little work has been done on teleoperation interface design for robots in the context of therapy for c...

Objective: Longitudinal neuroimaging data have been widely used to predict clinical scores for automatic diagnosis of Alzheimer's Disease (AD) in recent years. However, incomplete temporal neuroimaging records of the patients pose a major challenge to use these data for accurately diagnosing AD. In this paper, we propose a novel method to learn an...

Therapist-operated robots can play a uniquely impactful role in helping children with Autism Spectrum Disorder (ASD) practice and acquire social skills. While extensive research within Human Robot Interaction has focused on teleoperation interfaces for robots in general, little work has been done on teleoperation interface design for robots in the...

A critical challenge in using longitudinal neuroimaging data to study the progressions of Alzheimer's Disease (AD) is the varied number of missing records of the patients during the course when AD develops. To tackle this problem, in this paper we propose a novel formulation to learn an enriched representation with fixed length for imaging biomarke...

Alzheimer's Disease (AD) is a chronic neurodegenerative disease that severely impacts patients' thinking, memory and behavior. To aid automatic AD diagnoses, many longitudinal learning models have been proposed to predict clinical outcomes and/or disease status, which, though, often fail to consider missing temporal phenotypic records of the patien...

AIDS is a syndrome caused by the HIV. During the progression of AIDS, a patient's immune system is weakened, which increases the patient's susceptibility to infections and diseases. Although antiretroviral drugs can effectively suppress HIV, the virus mutates very quickly and can become resistant to treatment. In addition, the virus can also become...

Incomplete or inconsistent temporal neuroimaging records of patients over time pose a major challenge to accurately predict clinical scores for diagnosing Alzheimer’s Disease (AD). In this paper, we present an unsupervised method to learn enriched imaging biomarker representations that can simultaneously capture the information conveyed by all the...

Acquired immunodeficiency syndrome (AIDS) is a syndrome caused by the human immunodeficiency virus (HIV). During the progression of AIDS, a patient’s the immune system is weakened, which increases the patient’s susceptibility to infections and diseases. Although antiretroviral drugs can effectively suppress HIV, the virus mutates very quickly and c...

Place recognition plays an important role to perform loop closure detection of large-scale, long-term simultaneous localization and mapping in loopy environments. The long-term place recognition problem is challenging because the environment appearance exhibits significant long-term variations across various times of the day, months, and seasons....