【学术讲座】高寒宇:A Multi-Agent System for Complex Chemical Reaction Information Extraction

发布日期:2025-10-15     浏览次数:次   

学术讲座

报告题目: A Multi-Agent System for Complex Chemical Reaction Information Extraction

报告时间:2025-10-17 14:30

报告人: 高寒宇 助理教授

香港科技大学

报告地点:曾呈奎楼B311会议室

报告摘要:

The extraction of structured chemical information from literature is essential for constructing reaction databases that drive data-driven and AI-powered chemical research. A major challenge lies in the multimodal and complex nature of chemical data. In order to convert the raw data into structured, machine readable datasets, a modeling framework is needed with the ability to comprehend text, tables, and graphical representations of molecular structures. Existing approaches predominantly focus on single tasks, limiting their ability to fully capture reaction details and leading to incomplete datasets. To overcome this, we present ChemEagle, a multimodal large language model (MLLM)-based multi-agent system that integrates diverse chemical information extraction tools. By integrating seven expert-designed tools and six chemical information extraction agents, ChemEagle not only processes individual modalities but also utilizes MLLMs' reasoning capabilities to unify extracted data, ensuring more accurate and comprehensive reaction representations. We demonstrated the model’s capability in parsing chemical reaction diagrams, converting molecular structures to SMILES, and substituting functional groups or molecular fragments from tabulated lists. In all these tasks our model performed better than existing methods by a significant margin. Our approach presents a significant step towards automated chemical knowledge extraction, facilitating more robust AI-driven chemical research.


报告人简介:

   高寒宇是香港科技大学化学与生物工程系助理教授。2012年,他毕业于清华大学化学工程系,2017年于美国西北大学化学与生物工程系取得博士学位,师从美国工程院院士Linda J. Broadbelt教授,之后在麻省理工学院Klavs F. Jensen教授(美国科学、工程院院士)课题组从事博士后研究。

他的主要研究方向为高分子反应工程以及机器学习指导的有机合成路线设计,具体包括大语言模型和化学信息处理、聚合反应模拟优化、高分子材料设计等。他在化学化工主流期刊ACS Central Science、Chemical Engineering Journal、Macromolecules等发表多篇论文。

他在人工智能辅助化学合成和材料设计方面的研究涉猎颇广,包括有机合成、高分子材料、蛋白质材料等。他曾获国际基础科学大会前沿科学奖(2024年)、香港研究资助局杰出青年学者计划(2022年)等荣誉。


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