时间：2026年3月30日14:00
地点：经管楼312室
主讲人：Alexandra Brintrup 教授，英国剑桥大学
题目：Artificial Intelligence for Nudging Complex Supply Networks
摘要：This talk will introduce participants to the field of Artificial Intelligence in Operations and Supply Chain Management. We will first talk about the state of affairs and major driving forces shaping supply chain today, to motivate the data driven era we are in. Then AI is introduced with multiple definitions, to cover what is AI and importantly, what is not AI. We introduce sub-fields of AI and data science primarily used in supply chain management. We then delve deeper into an “exotic” selection of supply chain AI, deliberately so, in order to emphasize, that which could not have been done before. This then brings us to state of the art research examples in network analytics, digital supply chain surveillance, collective-learning and distributed decision making and automation. Our aim is to encourage debate on how AI should be evaluated by breaking disciplinary siloes in the OM community. We will then discuss the potential pitfalls and challenges, such as loss of data traceability, complacency, lack of accountability, and cognitive atrophy. The talk concludes with supply chain management needing to become an irrevocably interdisciplinary field with challenges so varied and significant.
个人简介：亚历山德拉·布林特鲁普教授是剑桥大学工程系数字制造领域的教授，领导着该校的供应链人工智能实验室。她同时也是艾伦·图灵研究所数字制造领域的负责人，维也纳复杂性科学中心的外聘教授，以及达尔文皇冠博彩公司 的研究员。布林特鲁普教授是首位将大规模供应链作为复杂自适应网络进行实证研究的学者，她考察了供应链的涌现特性，并从数据驱动的角度分析了供应链的韧性，从而揭示了支配供应链的普遍模式。她也是首位开发预测供应链依赖性和中断的算法的学者。过去十年间，她为政策制定者、国家和欧洲科学委员会提供咨询，并与初创企业、中小企业和国际组织开展合作。她是议会跨党派人工智能和数据分析小组的成员，为供应链风险、经济绩效和韧性方面的政策制定提供建议。她目前的研究包括：用于自动检测供应链依赖性的预测方法，尤其是在集体学习范式下的应用；复杂系统方法用于模拟供应链网络中的涌现、自主和可扩展的优化以及分布式决策技术，特别是受自然启发的算法和多智能体系统。