Publications
Browse our research papers published in top-tier conferences and journals in machine learning, computer vision, natural language processing, and AI ethics.
GenECA: A General-Purpose Framework for Real-Time Adaptive Multimodal Embodied Conversational Agents
We present GenECA, a general-purpose framework for creating real-time adaptive multimodal embodied conversational agents. Our framework integrates advanced natural language processing, computer vision, and speech synthesis to create more natural and effective human-computer interactions. Accepted to the Show & Tell Track
PhysNav-DG: A Novel Adaptive Framework for Robust VLM-Sensor Fusion in Navigation Applications
We present PhysNav-DG, a novel adaptive framework for robust vision-language model (VLM) and sensor fusion in navigation applications. Our framework addresses the challenges of integrating visual perception with other sensor modalities in dynamic and uncertain environments.
CPS-Guard: Multi-Role Orchestration System for Dependability Assurance of AI-Enhanced Cyber-Physical Systems
We present CPS-Guard, a multi-role orchestration system for ensuring the dependability and security of AI systems in critical infrastructure and cyber-physical systems. Our system provides comprehensive monitoring, verification, and adaptation capabilities for AI-enhanced CPS.
VIZ: Virtual & Physical Navigation System for the Visually Impaired
We present VIZ, a navigation system that helps visually impaired individuals navigate both physical and virtual environments with greater confidence and independence. VIZ uses computer vision and natural language processing to provide real-time guidance and information.
Towards Leveraging Semantic Web Technologies for Automated UI Element Annotation
We present a novel approach to automated UI element annotation using semantic web technologies. Our approach improves the accessibility of web and mobile applications by providing more accurate and meaningful annotations for screen readers and other assistive technologies.
GenECA: A Generalizable Framework for Real-Time Multimodal Embodied Conversational Agents
Introduces a robust framework for multimodal interactions with embodied conversational agents, emphasizing emotion-sensitive interaction.