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Himanshi Lalwani

dblp:404/5776 · DBLP profile ↗
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3ranked-venue papers
3as first author
3since 2021 · last 2025
0009-0008-6680-9650ORCID · corroborated

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

Artificial intelligence and machine learning · 3 · 3 first-author · 3 since 2021Human-computer interaction and ubiquitous computing · 3 · 3 first-author · 3 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 2 first-author · 2 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 · 67% Health and well-being technologies · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies › cognitive support
ADHD support
0.912025
A Study Companion for Productivity: Exploring the Role of a Social Robot for College Students with ADHD · HRI 2025
Human-robot interaction › assistive robotics
socially assistive robotics
0.912025
A Study Companion for Productivity: Exploring the Role of a Social Robot for College Students with ADHD · HRI 2025

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

user study · 0.9
YearPublicationVenuePosition
2025 A Study Companion for Productivity: Exploring the Role of a Social Robot for College Students with ADHD
abstract
Attention-Deficit Hyperactivity Disorder (ADHD) significantly impacts the academic, social, and mental well-being of young adults. While Socially Assistive Robots have shown promise in supporting individuals with ADHD, most existing systems focus on children and lack productivity tools for college students. To address this gap, we developed Alex, a study companion that assists with task prioritization, scheduling, and maintaining focus during work sessions. In a study involving 15 university students self-reporting ADHD symptoms, Alex's support alleviated overwhelm and improved focus. Notably, 12 participants expressed interest in using it again, demonstrating its potential to enhance productivity.
Himanshi Lalwani, Mira Saleh, Hanan Salam
HRI1
2025 Supporting Productivity Skill Development in College Students through Social Robot Coaching: A Proof-of-Concept
abstract
College students often face academic challenges that hamper their productivity and well-being. Although self-help books and productivity apps are popular, they often fall short. Books provide generalized, non-interactive guidance, and apps are not inherently educational and can hinder the development of key organizational skills. Traditional productivity coaching offers personalized support, but is resource-intensive and difficult to scale. In this study, we present a proof-of-concept for a socially assistive robot (SAR) as an educational coach and a potential solution to the limitations of existing productivity tools and coaching approaches. The SAR delivers six different lessons on time management and task prioritization. Users interact via a chat interface, while the SAR responds through speech (with a toggle option). An integrated dashboard monitors progress, mood, engagement, confidence per lesson, and time spent per lesson. It also offers personalized productivity insights to foster reflection and self-awareness. We evaluated the system with 15 college students, achieving a System Usability Score of 79.2 and high ratings for overall experience and engagement. Our findings suggest that SAR-based productivity coaching can offer an effective and scalable solution to improve productivity among college students.
Himanshi Lalwani, Hanan Salam
RO-MAN1
2025 Ethically-Aware Participatory Design of a Productivity Social Robot for College Students
abstract
College students often face academic and life stressors affecting productivity, especially students with Attention Deficit Hyperactivity Disorder (ADHD) who experience executive functioning challenges. Conventional productivity tools typically demand sustained self-discipline and consistent use, which many students struggle with, leading to disruptive app-switching behaviors. Socially Assistive Robots (SARs), known for their intuitive and interactive nature, offer promising potential to support productivity in academic environments, having been successfully utilized in domains like education, cognitive development, and mental health. To leverage SARs effectively in addressing student productivity, this study employed a Participatory Design (PD) approach, directly involving college students and a Student Success and Well-Being Coach in the design process. Through interviews and a collaborative workshop, we gathered detailed insights on productivity challenges and identified desirable features for a productivity-focused SAR. Importantly, ethical considerations were integrated from the onset, facilitating responsible and user-aligned design choices. Our contributions include comprehensive insights into student productivity challenges, SAR design preferences, and actionable recommendations for effective robot characteristics. Additionally, we present stakeholder-derived ethical guidelines to inform responsible future implementations of productivity-focused SARs in higher education.
Himanshi Lalwani, Hanan Salam
RO-MAN1