activity
20222026
most citedAutoFR: Automated Filter Rule Generation for Adblocking

3 citations · 6 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.HC2026

TeamLLM: Exploring the Capabilities of LLMs for Multimodal Group Interaction Prediction

Diana Romero, Xin Gao, Daniel Khalkhali +1

Predicting group behavior, how individuals coordinate, communicate, and interact during collaborative tasks, is essential for designing systems that can support team performance th…

cs.HC2025

M-CALLM: Multi-level Context Aware LLM Framework for Group Interaction Prediction

Diana Romero, Xin Gao, Daniel Khalkhali +1

This paper explores how large language models can leverage multi-level contextual information to predict group coordination patterns in collaborative mixed reality environments. We…

cs.HC2025

MURMR: A Multimodal Sensing Framework for Automated Group Behavior Analysis in Mixed Reality

Diana Romero, Yasra Chandio, Fatima Anwar +1

When teams coordinate in immersive environments, collaboration breakdowns can go undetected without automated analysis, directly affecting task performance. Yet existing methods re…

cs.HC2025

What Sensors See, What People Feel: An Exploratory Study of Subjective Collaboration Perception in Mixed Reality

Yasra Chandio, Diana Romero, Salma Elmalaki +1

Mixed Reality (MR) enables rich, embodied collaboration; however, it is uncertain whether sensor- and system-logged behavioral signals capture how users experience that collaborati…

cs.HC2024

GroupBeaMR: Analyzing Collaborative Group Behavior in Mixed Reality Through Passive Sensing and Sociometry

Diana Romero, Yasra Chandio, Fatima Anwar +1

Understanding group behavior is crucial for enhancing collaboration and productivity in mixed reality (MR). This paper introduces a framework for group behavior analysis in MR, or…

cs.HC2023

GaitGuard: Protecting Video-Based Gait Privacy in Mixed Reality

Diana Romero, Athina Markopoulou, Salma Elmalaki

Mixed Reality (MR) systems capture continuous video streams that expose bystanders' and collaborators' gait patterns -- a biometric revealing sensitive attributes including age, ge…

cs.HC2023★ 2 cited

BehaVR: User Identification Based on VR Sensor Data

Ismat Jarin, Yu Duan, Rahmadi Trimananda +3

Virtual reality (VR) platforms enable a wide range of applications, however, pose unique privacy risks. In particular, VR devices are equipped with a rich set of sensors that colle…