Title: Transforming Sensor Time Series with AI

报告人：Xiaoli Li教授, IEEE/AAIA Fellow, 新加坡科技设计大学

报告时间：2025年09月21日（周日）16:00

报告地点：色情网站 潇湘校区信息楼535报告厅

报告摘要: The rapid proliferation of sensors in manufacturing, aerospace, healthcare, and many other domains has created vast opportunities—and pressing challenges—for time series analytics. Traditional approaches are increasingly inadequate to meet the demands of predictive maintenance, equipment health monitoring, and large-scale operational optimization. In this keynote, I will discuss how recent advances in artificial intelligence are reshaping the way we analyze and leverage sensor data. I will highlight innovations in self-supervised representation learning that enable robust feature extraction from unlabeled time series, unsupervised domain adaptation methods that address distribution shifts across multivariate sensor environments, and model compression strategies that bring real-time intelligence to the edge. Finally, I will examine the emerging role of foundation models in time series analysis, considering their potential to unify diverse tasks and open up new industrial applications. By drawing on both research insights and real-world examples, this talk will showcase how next-generation AI techniques are not only advancing predictive analytics but also transforming how industries operate, innovate, and evolve in the era of intelligent sensing.

个人简介: Xiaoli is currently Head of the ISTD Pillar at SUTD. He previously led A*STAR’s Machine Intellection Department, where he built and directed Singapore’s largest AI and data science research group. He is also an Adjunct Full Professor at Nanyang Technological University, and a Fellow of both IEEE and AAIA. His research spans AI, data mining, machine learning, and bioinformatics, and has produced more than 380 peer-reviewed publications with over 30,000 citations, an h-index of 84, and more than ten best paper awards. He serves as Editor-in-Chief of the Annual Review of Artificial Intelligence and as an Associate Editor for leading journals such as IEEE Transactions on Artificial Intelligence and Knowledge and Information Systems. He has also played key leadership roles as conference chair or area chair at premier venues including AAAI, IJCAI, ICLR, NeurIPS, KDD, and ICDM. Beyond academia, Xiaoli brings extensive industry engagement experience, having established and led multiple joint labs and spearheaded more than ten major R&D collaborations with global partners in aerospace, telecommunications, insurance, and professional services. His contributions have earned him international recognition as one of the world’s top 2% scientists in AI (Stanford University) and as a Clarivate Highly Cited Researcher.