Guest Editor
Prof. ZHANG, Wei, Tsinghua University
Prof. ZHOU, Weihua, Zhejiang University
Dr. CHABLAT, Damien, Action Robotique, Agence Nationale de la Recherche, France
Dr. ZHENG, Pai, Hongkong Polytechnic University
Dr. MA, Liang, Tsinghua University, Email: liangma@tsinghua.edu.cn
Call for papers
Background
Modern engineering systems are entering a new era driven by the rapid growth of Artificial Intelligence. Unlike traditional software that simply follows commands, the rise of autonomous AI agents and robotic systems represents a major shift. Today’s major engineering projects, smart manufacturing, urban infrastructure, and supply chains require systems that can perceive their environment, reason through complex problems, and act independently in dynamic engineering settings. The integration of Large Language Models (LLMs) and advanced robotics is redefining how humans and machines work together, moving the focus of engineering operations from "human-led automation" to true "human-machine teaming."
Aim and Scope
While AI agents and robotics promise major improvements in productivity, safety, and efficiency, they also bring significant challenges. The engineering sector faces obstacles such as harsh physical environments, the need for human professionals to adapt (e.g., building trust and learning new skills), and the need to connect data across different platforms. Furthermore, restructuring workflows for "hybrid human-AI teams," addressing ethical concerns, and ensuring the economic value of these technologies remain key topics of debate.
This special issue explores Human-AI Collaboration within complex engineering systems. We welcome papers on topics ranging from technical system designs and organizational studies to practical applications across the lifecycle of a project. Our goal is to connect technical achievements in AI and robotics with a deeper understanding of the human, operational, and ethical factors involved in modern engineering.
Topics to be covered include, but are not limited to
l Advances in AI agents and embodied AIs
n Emergent behaviors and physical anomalies: Unpredictability, resilience, and safety of autonomous agents in complex tasks
n Humanoid and non-humanoid robots: Task-specific capabilities, limitations, and operational synergies in engineering environments
n Agent-driven supply chains: Multi-agent optimization algorithms and applications in engineering logistics and material procurement
n Fundamental architectures and system designs of AI agents and embodied robotics for engineering applications
l Human's adaptation and augmentation to AI agents and embodied AIs
n Cognitive augmentation and human-AI teaming: Amplifying human intellect and professional capabilities
n Physical augmentation and embodied interaction: Redefining human labor and operational boundaries
n Human passive adaptation, trust dynamics, and socio-technical transitions during agentic deployments
n Theoretical frameworks, psychological dimensions, and empirical evaluations of human-AI integration in engineering systems
l Organizational adaptation to AI agents and embodied AIs
n Human-Human organizational dynamics: Redefining team collaboration, communication patterns, and decentralized management in AI-integrated projects
n Human-AI mingled teams: Accountability, performance evaluation, leadership, and trust inside hybrid working units
n AI-AI interoperability networks: Conflict resolution and the alignment of epistemic authority among autonomous machine networks
n Organizational transformations: Reshaping enterprise structures, workflows, and cultures through agentic and embodied AI technologies
l Challenges and opportunities in real-world engineering scenarios
n Intelligent manufacturing and industrial systems: Scaling barriers and human-robot synergy in complex production lines and resilient supply chains
n Smart transportation and urban mobility: Navigating uncertainties, human-AI traffic control, and multi-mode logistics optimization
n Energy, environment, and critical infrastructures: Risk management, safety assurance, and resilience of agent-driven Cyber-Physical Systems
n Healthcare and intelligent medical services: AI-augmented professional workflows, human-AI empathetic care, and the resilience of novel medical service systems
n Systematic challenges and transformative opportunities of integrating AI agents across diverse engineering management domains
l Lifecycle applications of AI agents and embodied AIs
n Design and Planning stage: Agent-driven generative conceptualization, multi-objective parameter optimization, and automated compliance checking
n Production and Construction stage: Human-robot physical coordination, real-time progress tracking, and autonomous anomaly remediation
n Service, Operations, and Maintenance (O&M) stage: Predictive upkeep, digital twin-coupled fault diagnosis, and autonomous facility adjustments
n Lifecycle integration: Comprehensive paradigms, methodologies, and multi-stage case studies evaluating AI agency across the lifespan of engineered systems
Submission Guidelines
To submit a manuscript, please visit https://mc.manuscriptcentral.com/engm. Under “Manuscript Type”, please select “Human-AI Collaboration in Complex Engineering System”. All manuscripts will be peer-reviewed in accordance with the established policies and procedures of the journal. Papers will be selected for publication following the outcome of the peer review process.
Important Dates
l Submission deadline: September 30, 2026
l Final decision notification: January 31, 2027
l Expected publication date: March 31, 2027 or June 30 2027