1、Chapter 1.Introduction1.The definition and paradigm of AI for Science2.Development and trends3.Data analysisChapter 2.Core AI1.From large language models to autonomous agents2.Embodied intelligence3.Brain-computer interface4.AI system security and safetyChapter 3.AI for mathematics1.Foundational the

2、ory2.Operations optimization3.Statistics4.Scientific computing5.Complex systemChapter 4.AI for physical sciences1.AI for physics 2.AI for chemistry 3.AI for materials4.AI for energy Chapter 5.AI for life sciences1.AI for synthetic biology 2.AI for medicine 3.AI for neuroscience 4.AI for health 5.AI-

3、driven evolutionary studies Chapter 6.AI for earth and environmental sciences 1.AI for weather forecasting 2.AI for environmental science 3.AI for ecological science Chapter 7.AI for engineering 1.AI for communications 2.AI for remote sensing 3.AI for microelectronics 4.AI for space informationChapt

4、er 8.AI for humanities and social sciences1.Computational social science2.Digital and intelligent humanities3.AI ethics and governance Chapter 9.Prospects and policies1.Future challenges and research directions1.Policy framework245121315162021222325282931333738394142464849535455566061626465CONTENT1C

5、hapter 1Zenglin Xu Fudan University,Shanghai Academy of AI for ScienceYuan Cheng Fudan University,Shanghai Academy of AI for ScienceYanqing Yang Shanghai Academy of AI for ScienceYan Xu Shanghai Academy of AI for ScienceChapter 2Xipeng Qiu Fudan UniversityYanwei Fu Fudan UniversityShouyan Wang Fudan

6、 UniversityMin Yang Fudan UniversityHong Zou Fudan UniversityChapter 3Shuai Lu Fudan UniversityLei Shi Fudan UniversityKe Wei Fudan UniversityXuening Zhu Fudan UniversityWeiguo Gao Fudan UniversityYingzhou Li Fudan UniversityWei Lin Fudan UniversityWei Yang Fudan UniversityChapter 4Hongjun Xiang Fud