《Frontier Seminars in Computer Science and Technology（计算机科学与技术前沿研讨会）》Joseph Sifakis 教授：工业AI

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  • 题目: 工业AI
  • 主讲人：Joseph Sifakis 教授 @ Verimag
  • 时间：2026年10月16日 16:20-18:10
  • 地点：Lecture Hall of Research Building 1（一科大阶梯教室）

主讲人简介

Professor Joseph Sifakis is Emeritus Research Director at Verimag. He has been a full professor at Ecole Polytechnique Fédérale de Lausanne (EPFL) for the period 2011-2016. He is the founder of the Verimag laboratory in Grenoble, a leading laboratory in the area of safety critical systems that he directed for 13 years. Joseph Sifakis has made significant and internationally recognized contributions to the design of trustworthy systems in many application areas, including avionics and space systems, telecommunications, and production systems. His current research focuses on autonomous systems, in particular self-driving cars and autonomous telecommunication systems. In 2007, he received the Turing Award, recognized as the "highest distinction in computer science", for his contribution to the theory and application of model checking, the most widely used system verification technique. Joseph Sifakis is a member of the French Academy of Sciences, the French National Academy of Engineering, Academia Europaea, the American Academy of Arts and Sciences, the National Academy of Engineering, the National Academy of Sciences, and the Chinese Academy of Sciences. Joseph Sifakis is a frequent speaker at international scientific, technical and public forums. He is the author of the book “Understanding and Changing the World” published in English and Chinese.

讲座简介

Despite impressive recent advances, a clear-eyed analysis leads to a sobering conclusion: AI remains in its infancy. Yet numerous applications in science, services, and industry remain underserved. These domains demand greater automation, higher reliability, and interaction modes beyond conversation. As a result, AI's real-world impact is still limited, leaving a vast field of applications wide open. Industrial AI, in particular, requires autonomous agent systems with guaranteed trustworthiness, as envisioned by the Internet of Things. Although 2025 was heralded as the year of AI agents, their industrial deployment remains confined to digital and predictable environments. Autonomous systems can be regarded as the ultimate stage of AI development: they comprise agents, each pursuing its own goals while cooperating to achieve the goals of the larger system to which it belongs. Current AI falls far short of this vision—a gap starkly illustrated by the setbacks of the autonomous vehicle industry, a prime example of the magnitude of the challenge posed by autonomy. This talk examines the technical challenges of developing autonomous agent systems for industrial applications from two perspectives: 1. Reference architectures that could serve as a foundation for developing autonomous agents. 2. Trustworthiness evaluation, particularly with respect to the two types of properties that characterize it: behavioral and cognitive. We conclude with a discussion of future developments in industrial AI, focusing on two aspects: 1. An analysis of the current state of the art in agent-based AI. 2. An analysis of issues related to risk management and the absence of regulatory frameworks to address them.

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