NSF ChemData/AI Researcher Meeting: Evaluate Progress and Think About What the Future Brings

佛罗里达大学的禤浩焯·罗伊特伯格教授和佐治亚理工学院的法昆多·费尔南德斯教授在特别项目办公室化学部的支持下，组织了一个在线研讨会，题为《美国国家科学基金会化学数据/人工智能研究人员会议：评估进展并思考未来会发生什么。》在国家科学基金会化学部最近为鼓励数据、机器学习(ML)和人工智能(AI)科学在化学研究中的应用而进行的投资的背景下，PI再次吸引一线研究人员来催化讨论和确定研究方向，这些研究方向可能会激发现代数据科学工具的更具创造性的使用或适应新的化学理解和研究方向。其目标是收集广泛定义的化学领域中AI/ML从业者的专家建议，鼓励关于数据科学在化学中的作用的讨论，并批判性地思考吸取的经验教训和未来的努力。研讨会的参与者将从研究、设施和资源以及劳动力发展的角度，探索哪些是AI/ML的关键优势领域，哪些是机会，也许更重要的是，哪些化学领域人工智能/ML尚未产生影响，但未来的努力已经成熟。研讨会的结果将是一份向化学界和NSF提供的报告，其中强调了研究方向、需求、差距和机会。AI/ML工具在化工企业中的使用尚处于初级阶段，但预计在不久的将来将开始占据核心地位。确保社区参与讨论可以加速发现，并可能影响政策。这次研讨会的结果将被广泛宣传，并将以一份文件结束，该文件将展示该领域领导者的当前想法，并可作为未来参与AI/ML的化学企业的路线图。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Professor Adrian Roitberg of the University of Florida and Professor Facundo Fernandez of the Georgia Institute of Technology are supported by the Chemistry Division - Office of Special Projects, to organize a online workshop entitled 'NSF ChemData/AI Researcher Meeting: Evaluate Progress and Think about what the Future Brings.' In the context of recent investments by the Division of Chemistry of NSF to encourage in the application of Data, Machine Learning (ML), and Artificial Intelligence (AI) sciences for chemistry research, the PIs are engaging again the frontline researchers to catalyze a discussion and identify research directions that may inspire more creative use or adaptation of modern data science tools toward new chemical understanding and research directions. The objective is to gather expert advice from AI/ML practitioners in the broadly defined chemistry arena, to stimulate discussion about the role of Data science in chemistry, and to think critically about lessons learned and future endeavors. The workshop participants will explore what are the critical areas of strength, what are the opportunities, and perhaps more importantly, what are areas of chemistry where AI/ML has yet to make an impact, and yet, that are ripe for future efforts, from the standpoints of research, facilities and resources, and workforce development. The outcome of the workshop will be a report available to the chemistry community and to the NSF that highlights research directions, needs, gaps, and opportunities. The use of AI/ML tools in the chemistry enterprise is in its infancy but is expected to start to occupy a central role in the near future. Making sure that the community is involved in discussions can accelerate discovery and potentially influence policies. The results of this workshop will be advertised broadly, and will end in a document that will present the current thoughts of leaders in the field, and can serve as a roadmap for a future AI/ML-involved chemical enterprise.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.