Welcome to Interactive AI Agent

Interactive AI Agents are sophisticated software programs designed to engage with users in a dynamic, responsive manner. These agents use a combination of natural language processing, machine learning, and sometimes even emotional intelligence to interpret and respond to human inputs. The primary goal of these AI systems is to facilitate an intuitive and efficient user experience, whether for customer service, personal assistance, educational purposes, or entertainment. Interactive AI agents are capable of learning from interactions to improve their responses over time, making them increasingly effective at handling complex inquiries and tasks. Their ability to operate autonomously and assist across various platforms makes them invaluable in today’s technology-driven world.

Representative Publications

Generative AI for Low-Carbon Artificial Intelligence of Things
Jinbo Wen, Ruichen Zhang, Dusit Niyato, Jiawen Kang, Hongyang Du, Yang Zhang, Zhu Han
Under review

This paper explores the potential of GAI for carbon emissions reduction and proposes a novel GAI-enabled solution for low-carbon AIoT.
Paper

Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse
Guangyuan Liu, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Abbas Jamalipour, Shiwen Mao, Dong In Kim
Under Review

The paper explores the potential of mixture of experts with generative AI, focusing on mobile edge Metaverse.
Paper | Code

Generative AI Agent for Next-Generation MIMO Design: Fundamentals, Challenges, and Vision
Zhe Wang, Jiayi Zhang, Hongyang Du, Ruichen Zhang, Dusit Niyato, Bo Ai, Khaled B. Letaief
Under Review

This paper studies the generative AI agent for next-generation MIMO design.
Paper | Code

Generative AI for Game Theory-based Mobile Networking
Long He, Geng Sun, Dusit Niyato, Hongyang Du, Fang Mei, Jiawen Kang, Mérouane Debbah, Zhu Han
Under Review

The paper explores the combination of LLM with game theory, focusing on mobile network optimization.
Paper

Generative AI for Advanced UAV Networking
Geng Sun, Wenwen Xie, Dusit Niyato, Hongyang Du, Jiawen Kang, Jing Wu, Sumei Sun, Ping Zhang
Under Review

This paper proposed a framework for UAV networking, which augments with RAG and generative diffusion model.
Paper

Interactive Al with Retrieval-Augmented Generation for Next-Generation Networking
Ruichen Zhang, Hongyang Du, Yinqiu Liu, Dusit Niyato, Jiawen Kang, Sumei Sun, Xuemin Shen, H. Vincent Poor
Under Review

This paper explores an integration and enhancement of interactive AI (IAI) in networking.
Paper | Code

Semantic communications for artificial intelligence generated content (AIGC) toward effective content creation
Guangyuan Liu, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Xuemin Shen
IEEE Network Magazine

In this paper, a novel comprehensive conceptual model for the integration of AIGC and SemCom is developed.
Paper | YouTube | Bilibili

Generative AI for Secure Physical Layer Communications: A Survey
Changyuan Zhao, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Xuemin (Sherman) Shen, Khaled B. Letaief
Under review

This paper offers an extensive survey on the various applications of GAI in enhancing security within the physical layer of communication networks.
Paper

Generative AI for Space-Air-Ground Integrated Networks (SAGIN)
Ruichen Zhang, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Abbas Jamalipour, Ping Zhang, Dong In Kim
IEEE Wireless Communications Magazine

This paper explores an integration of generative AI in SAGIN, focusing on potential applications and case study.
Paper | YouTube | Bilibili

AI-Generated Incentive Mechanism and Full-Duplex Semantic Communications for Information Sharing
Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim
IEEE Journal on Selected Areas in Communications

This paper proposes a contract theoretic AI-generated incentive mechanism that generates the optimal contract design.
Paper | Code

Generative AI for Integrated Sensing and Communication: Insights from the Physical Layer Perspective
Jiacheng Wang, Hongyang Du, Dusit Niyato, Jiawen Kang, Shuguang Cui, Xuemin Shen, Ping Zhang
IEEE Wireless Communications Magazine

The paper showcases the use of generative AI in integrated sensing and communications, especially from the physical layer.
Paper | YouTube | Bilibili

Guiding AI-Generated Digital Content with Wireless Perception
Jiacheng Wang, Hongyang Du, Dusit Niyato, Zehui Xiong, Jiawen Kang, Shiwen Mao, Xuemin (Sherman) Shen
IEEE Wireless Communications Magazine

The paper explains the use of wireless sensing data for input of AIGC applications to generate images and videos.
Paper | YouTube | Bilibili

Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Study
Ruichen Zhang, Ke Xiong, Hongyang Du, Dusit Niyato, Jiawen Kang, Xuemin Shen, H. Vincent Poor
IEEE Network Magazine

The paper summarizes and showcases how generative AI can be used in healthcare applications.
Paper | YouTube | Bilibili

A Revolution of Personalized Healthcare: Enabling Human Digital Twin with Mobile AIGC
Jiayuan Chen, Changyan Yi, Hongyang Du, Dusit Niyato, Jiawen Kang, Jun Cai, Xuemin (Sherman) Shen
IEEE Network Magazine

The paper summarizes and showcases how generative AI can be used in healthcare applications.
Paper | YouTube | Bilibili

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