most citedHuman-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities

4 citations · 5 across the 3 of their papers we have counts for

collaborators

6 papers

cs.AI2026

When Agentic AI Meets Integrated Sensing and Communication

Kai Li, Conggai Li, Sarah Ali Siddiqui +4

Agentic artificial intelligence (AI) is transforming Integrated Sensing and Communication (ISAC) from a function-oriented physical-layer technology into a goal-driven, closed-loop…

cs.LG20264 cited

Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities

Yousef Emami, Mohammadhossein Homaei, Miguel Gutiérrez Gaitán +4

Machine Learning (ML) has become central to Autonomous Vehicles (AVs), supporting perception, prediction, planning, control, and decision-making in dynamic environments. However, a…

cs.RO20261 cited

On the Use of AI-Driven Immersive Digital Technologies for Designing and Operating UAVs

Yousef Emami, Mohammadhossein Homaei, Miguel Gutierrez Gaitan +3

Uncrewed Aerial Vehicles (UAVs) offer agile, cost-effective, and efficient solutions for communication relay networks. However, their modeling and control are challenging, and the…

cs.CR2025

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things

Kai Li, Conggai Li, Xin Yuan +8

This paper focuses on Zero-Trust Foundation Models (ZTFMs), a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models (FMs) for Internet o…

cs.LG2025

Undermining Federated Learning Accuracy in EdgeIoT via Variational Graph Auto-Encoders

Kai Li, Shuyan Hu, Bochun Wu +3

EdgeIoT represents an approach that brings together mobile edge computing with Internet of Things (IoT) devices, allowing for data processing close to the data source. Sending sour…

cs.CR2025

Towards Resilient Federated Learning in CyberEdge Networks: Recent Advances and Future Trends

Kai Li, Zhengyang Zhang, Azadeh Pourkabirian +3

In this survey, we investigate the most recent techniques of resilient federated learning (ResFL) in CyberEdge networks, focusing on joint training with agglomerative deduction and…