most citedIntegrating Physiological Data with Large Language Models for Empathic Human-AI Interaction

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.GR2025

CrossSet: Unveiling the Complex Interplay of Two Set-typed Dimensions in Multivariate Data

Kresimir Matkovic, Rainer Splechtna, Denis Gracanin +1

The interactive visual analysis of set-typed data, i.e., data with attributes that are of type set, is a rewarding area of research and applications. Valuable prior work has contri…

cs.GR2025

Transcending Dimensions using Generative AI: Real-Time 3D Model Generation in Augmented Reality

Majid Behravan, Maryam Haghani, Denis Gracanin

Traditional 3D modeling requires technical expertise, specialized software, and time-intensive processes, making it inaccessible for many users. Our research aims to lower these ba…

cs.HC2024

Multilingual Standalone Trustworthy Voice-Based Social Network for Disaster Situations

Majid Behravan, Elham Mohammadrezaei, Mohamed Azab +1

In disaster scenarios, effective communication is crucial, yet language barriers often hinder timely and accurate information dissemination, exacerbating vulnerabilities and compli…

cs.HC2024

A digital twin based approach to smart lighting design

Elham Mohammadrezaei, Alexander Giovannelli, Logan Lane +1

Lighting has a critical impact on user mood and behavior, especially in architectural settings. Consequently, smart lighting design is a rapidly growing research area. We describe…

cs.HC2024

Empowering Mobility: Brain-Computer Interface for Enhancing Wheelchair Control for Individuals with Physical Disabilities

Shiva Ghasemi, Denis Gracanin, Mohammad Azab

The integration of brain-computer interfaces (BCIs) into the realm of smart wheelchair (SW) technology signifies a notable leap forward in enhancing the mobility and autonomy of in…

eess.SP20242 cited

Integrating Physiological Data with Large Language Models for Empathic Human-AI Interaction

Poorvesh Dongre, Majid Behravan, Kunal Gupta +2

This paper explores enhancing empathy in Large Language Models (LLMs) by integrating them with physiological data. We propose a physiological computing approach that includes devel…