报告人：Seán McLoone

工作单位：英国贝尔法斯特女王大学

报告题目：人工智能驱动的预测建模：从软测量到人机协同

报告时间：2025年10月14日（周二）9：30

报告地点：文理楼290

内容摘要：

本报告概述了演讲者三十年来在人工智能驱动的预测建模领域的研究成果，其背景是人工智能技术三十五年来的整体发展历程 —— 从 20 世纪 90 年代的浅层神经网络，到过去十年的深度学习。这些人工智能技术进步催生了软测量、自动检测、预测性维护和故障诊断等众多成功的工业应用，同时为从工业 3.0 向工业 4.0 的转型提供了支撑，并且在以人为主导、可持续发展为目标的工业 5.0 进程中，其核心地位日益凸显。报告还梳理了演讲者的研究轨迹：早期将浅层神经网络用于软测量，近期利用深度神经网络开展预测性维护与故障诊断相关项目，以及目前在女王大学开展的、借助人工智能预测人体动作的研究 —— 该研究旨在将这一技术与先进控制技术结合，以优化人机协作。

个人简介：

肖恩·麦克卢恩教授现任贝尔法斯特女王大学应用计算智能教授、智能自主制造系统中心主任。他拥有超过30年的专业经验，其研究核心集中于计算智能与人工智能在先进制造、能源及可持续发展领域的应用，特别专注于工业4.0/5.0技术，如协作机器人、状态监测与过程优化。他已培养超过30名博士生，并发表了270余篇经同行评审的论文。作为特许工程师、英国工程与技术学会会士及IEEE高级会员，麦克卢恩教授曾担任重要领导职务，包括IEEE英国与爱尔兰分会主席（2006-2009年）及爱尔兰制造研究院董事会成员（2014-2021年）。他目前担任《Engineering Applications of Artificial Intelligence》和《Transactions of the Institute of Measurement and Control》期刊编委，同时是IFAC计算智能与控制技术委员会副主席。其在学术界的卓著声誉进一步体现于近期获任英国科研卓越框架（REF2029）工程学科分委会成员。

Speaker: Seán McLoone

Title:AI Enabled Predictive Modelling: From Soft Sensing to Human

Time: 9:30 AM, October 14, 2025 (Tuesday)

Location:290 Arts and Science Building

Abstract:  

This talk offers an overview of the speaker’s 30-year research in AI-enabled predictive modelling, set against the broader evolution of AI over 35 years—from 1990s shallow neural networks to the past decade’s deep learning. These AI advances have driven successful industrial applications like soft sensing, automated inspection, predictive maintenance, and fault diagnosis, while underpinning the shift from Industry 3.0 to 4.0 and growing central to Industry 5.0’s human-centric, sustainable manufacturing goals. The talk traces the speaker’s work: early use of shallow neural networks for soft sensing, recent deep neural network projects for predictive maintenance and fault diagnosis, and ongoing Queen’s University research using AI to anticipate human motion, aiming to pair this with advanced control for better human-robot collaboration.

Personal Introduction:

Professor Seán McLoone is Professor of Applied Computational Intelligence and Director of the Centre for Intelligent Autonomous Manufacturing Systems at Queen's University Belfast. With over 30 years of expertise, his research centers on computational intelligence and AI, with applications in advanced manufacturing, energy, and sustainability, particularly focusing on Industry 4.0/5.0 technologies such as collaborative robotics, condition monitoring, and process optimization. He has graduated over 30 PhD students and authored more than 270 peer-reviewed publications. A Chartered Engineer, Fellow of the IET, and Senior Member of the IEEE, Professor McLoone has held significant leadership roles including Chairman of the UK & Ireland IEEE Section (2006-2009) and Member of the Board of Directors for Irish Manufacturing Research (2014-2021).He currently serves on the Editorial Boards of Engineering Applications of Artificial Intelligence and Transactions of the Institute of Measurement and Control, and is a Vice-Chair of the IFAC Technical Committee on Computational Intelligence and Control. Demonstrating his standing in the field, he has recently been appointed to the Engineering sub-panel for the UK's Research Excellence Framework (REF2029).