Johns Hopkins University

schoolSchoolbar_chart#115 Global Rank

Total Papers

HCI Rank

#115

Research Areas

Years Active

Recent Publications

Latest papers from Johns Hopkins University

CHI '26Brain-Computer Interface (BCI) & Neurofeedback +2

Enhancing Error Awareness Under Cognitive Load: How Neurostimulation Improves Self-Monitoring via Working Memory

Error awareness—the ability to detect errors, adjust strategies, and prevent mistakes—is critical in high-stakes human–computer interaction (e.g., aviation, autonomous system supervision), as well as in everyday life. However, this ability deteriorates under heavy cognitive load, and effective countermeasures remain s…

CHI '26Dark Patterns Recognition +3

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight

The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate tasks from high-level intents, understanding how dark patterns affect agents is incr…

CHI '26Behavior Change & Reflection Technology +2

User Perceptions of Responsible Gambling Messages as Nudges for Gambling Safety

Nudges are subtle interventions designed to influence user behavior without restricting choice. Responsible gambling messages (RGMs) exemplify such nudges by encouraging safer decision-making in gambling environments. Prior research has examined how pop-up messages influence gambling behavior in experimental settings…

CHI '26Human-LLM Collaboration +3

Feedback by Design: Understanding and Overcoming User Feedback Barriers in Conversational Agents

High-quality feedback is essential for effective human–AI interaction. It bridges knowledge gaps, corrects digressions, and shapes system behavior; both during interaction and throughout model development. Yet despite its importance, human feedback to AI is often infrequent and low quality. This gap motivates a critic…

CHI '26Conversational Chatbots +2

Understanding Parents’ Desires in Moderating Children’s Interactions with GenAI Chatbots through LLM-Generated Probes

This paper studies how parents want to moderate children’s interactions with Generative AI Chatbots, with the goal of informing the design of future GenAI parental control tools. We first used an LLM to generate synthetic Child--GenAI Chatbot interaction scenarios and worked with four parents to validate their realism…

CHI '26Honorable MentionCrowdsourcing Task Design & Quality Control +2

Dynamic Compensation Can Enhance User Engagement by Triggering Sensitivity to Financial Losses in Crowd-sourced Studies

Participation in crowd-sourced user studies is often driven by monetary incentives. However, standard payment schemes that reward completion unless responses are of poor quality may not invoke sufficient accountability. By compromising user engagement, a lack of accountability can affect data quality and the study's e…

CHI '26Generative AI (Text, Image, Music, Video) +2

Designing Privacy Choice in Generative AI Chatbot Ecosystems

Generative AI (GenAI) is evolving from standalone tools to interconnected ecosystems that integrate chatbots, cloud platforms, and third-party services. While this ecosystem model enables personalization and extended services, it also introduces complex information flows and amplifies privacy risks. Existing solutions…

CHI '26Conversational Chatbots +2

Cloning the Self for Mental Well-Being: A Framework for Designing Safe and Therapeutic Self-Clone Chatbots

As digital tools increasingly mediate mental health care, self-clone chatbots can offer a uniquely novel approach to intra-personal exploration and self-derived support. Trained to replicate users’ conversational patterns, self-clones allow users to talk to themselves through their digital replicas. Despite the promis…

CHI '26Honorable MentionAI-Assisted Decision-Making & Automation +3

From Future of Work to Future of Workers: Addressing Asymptomatic AI Harms to Foster Dignified Human-AI Interaction

In the future of work discourse, AI is touted as the ultimate productivity amplifier. Yet, beneath the efficiency gains lie subtle erosions of human expertise and agency. This paper shifts focus from the future of work to the future of workers by navigating the AI-as-Amplifier Paradox: AI's dual role as enhancer and e…

CHI '26Human-LLM Collaboration +2

Results-Actionability Gap: Understanding How Practitioners Evaluate LLM Products in the Wild

How do product teams evaluate LLM-powered products? As organizations integrate large language models (LLMs) into digital products, their unpredictable nature makes traditional evaluation approaches inadequate, yet little is known about how practitioners navigate this challenge. Through interviews with nineteen practit…

View all 62 papers →

Quick Actions

Share this page

ios_share

X in mail

https://hci.top/en/institutions/Johns%20Hopkins%20University?source=all

At a Glance

Institution Snapshot

analytics

tag

Display Name

Johns Hopkins University

public

Location

United States · North America

leaderboard

Overall Rank

#115

article

Total Papers

calendar_month

Active Years

2018-2026

groups

Network

36 researchers · 1 collaborators

Research Profile

Top Research Directions

query_stats

AI & Machine Learning Interaction

Human-LLM Collaboration

Privacy, Security & Trust

Privacy by Design & User Control

Accessibility & Inclusive Design

Universal & Inclusive Design

Research Methods & Design Practice

Participatory Design

Ethics, Fairness, Social Justice & Inclusion

Algorithmic Fairness & Bias